Wastewater treatment using an iron nanocatalyst supported

Wastewater treatment using an iron nanocatalyst supported on Fique

fibers

Karen Giovanna Bastidas Gómez

Universidad Nacional de Colombia

Facultad de Ingeniería

Departamento de Ingeniería Química y Ambiental

Bogotá, Colombia

2016

Tratamiento de aguas residuales usando un nanocatalizador soportado

en fibras de Fique y fase activa de hierro





Bogotá, Colombia

2016

Tratamiento de aguas residuales usando un nanocatalizador soportado

en fibras de Fique y fase activa de hierro


Tesis presentada como requisito parcial para optar al título de

Magister en Ingeniería – Ingeniería Química

Director:

Hugo Ricardo Zea Ramírez, Ph.D.

Codirector:

Cesar Augusto Sierra Ávila, Ph.D.

Línea de investigación:

Materiales y tratamiento de residuos acuosos

Grupo de Investigación:

Materiales, Catálisis y Medio Ambiente




Bogotá, Colombia

2016

“Research is to see what everybody has seen and think what nobody has thought”

Albert Szent-Györgyi

Acknowledgements

Without God, it would not have been possible to carry out what it may be one of the best

times of my life. Thank you for providing so much joy, patience, courage and conviction to

do what I like so much, for never letting me fall and always shedding light on the path I

have to take.

I would also like to thank the best medicine anyone can have: Fannytidina, you are and

you will always be my example to follow, you're the superheroine who taught me to be the

woman that I am, thank you for teaching me to never give up and have faith despite

adversity. When I was cold and hungry doing experiments, you always had a big smile and

a hug for me, I love you with all the strength in my heart. Fo, thanks for the many dawns

when our songs and desire to succeed motivated us to work in that makes us happy, for

helping me to dream and believe about what is invisible to our soul. To my family, who

always reminded me our love for each other is the biggest treasure we have, no matter

where we are, our hearts are always together full with best wishes.

Thanks to my advisor Professor Hugo Ricardo Zea Ramírez, for the countless lessons I

learnt from you, not only from the great academic training that I received, but also because

I have learnt the value of living with tranquility and peace, thank you for all the support, for

believing in me when I arrived to that unknown world called Universidad Nacional de

Colombia. I can now say that it possible for everyone to fly from the creativity and freedom

of doing science through the mind and heart with the research group of Materials,

Catalysis and Environment.

Likewise, I’m grateful to Professor Cesar Augusto Sierra Avila and the Macromolecules

research group, for taking me in with arms wide open, thank you for that little family we

have, for the Friday Group cultural meeting and all those moments we shared, regardless

of occupations and distance.

Day by day I met people who made more enjoyable my path and who helped me

accomplish this research, you gave me more than just pieces of knowledge, you gave me

a part of your heart: Cristo, Tati, Andre, Snorkey, Alejo, Figaro, Pocho, Ruby, Eevee, Fran,

Peter, Geral, Carito, Darks and Loretto, thank you for the unconditional support, for the

countless laughter that we shared and brought so much joy to my spirit. Especially

Chucks, thank you for giving so much color the days that seemed gray and unlit, for loving

me in this supernatural way you only do; thanks for always having the perfect words and

know how to fix everything, thanks for giving me the chance to get to know you. You'll

always have a place in my heart.

Thanks to Anita and Davidcito “my children”, to make the best working group. You were

always ready to learn, thanks for all your energy and willingness to help in some way to

achieve our goals, for allowing me to dream with you and show you that flying high is only

a matter of desire, that if we work together with a clear goal, we will always shine. Thanks

for these times in which the laughter were our engine to keep moving.

I thank all the faculty members, administration and laboratory staff of the Chemical and

Environmental Engineering Department, who stretched their hands and contributed to my

personal and professional training. Thanks to the Research Division in Bogota (DIB) for

providing financial resources through the project "Tratamiento de aguas residuales usando

un nanocatalizador soportado en fibras de fique y fase activa de hierro." Finally, thanks to

the Universidad Nacional de Colombia, for giving me the opportunity to learn a way to

interpret reality from the concept of science, to provide solutions to different problems for

our country and for the world.

Resumen

El tratamiento de aguas residuales industriales para la decoloración y la remoción de

metales pesados utilizando procesos heterogéneos, económicos y factibles ha sido un

tema de interés a escala industrial. Actualmente ciencias como la nanotecnología han

potencializado las propiedades de materiales compuestos, los cuales han permitido

incursionar en el uso de nanopartículas, como fase activa para catalizadores.

Particularmente, las nanopartículas de hierro se han utilizado en la remoción de metales

pesados como el mercurio y el arsénico a través de operaciones como la adsorción y han

sido utilizadas en procesos avanzados de oxidación en los cuales, a partir del proceso

Fenton, se realiza la degradación y mineralización de aguas provenientes de industrias

textiles. Adicionalmente, la necesidad actual de generar productos y procesos de carácter

sostenible ha hecho posible la implementación del uso de fibras naturales como matrices

potenciales de materiales compuestos. Es por esta razón que hoy en día mucha de la

investigación se ha focalizado en el uso de materiales lignocelulósicos, con el fin de

aprovechar las propiedades mecánicas, físicas y químicas que posee la celulosa. En esta

tesis de maestría, se obtuvo un material catalítico a partir del uso de la fibra de fique como

soporte de nanopartículas de hierro. Con el objetivo de hacer posible el proceso del

anclaje de nanopartículas, se realizó una preparación de la fibra la cual consistió en una

funcionalización del soporte para posteriormente depositar las nanopartículas de hierro

por medio de un método fácil y económico de síntesis de nanopartículas como lo es la

impregnación húmeda; así mismo, para conocer las propiedades relativas al material se

realizó una caracterización fisicoquímica por medio de métodos analíticos gravimétricos,

volumétricos e instrumentales. Esta tesis de maestría también exploró potenciales

aplicaciones en el tratamiento de aguas residuales, dentro de las cuales se encontraron

resultados prometedores en relación a la degradación y mineralización de colorantes tipo

azo como el Orange II y en la remoción de metales pesados como el mercurio. Ambas

aplicaciones fueron analizadas con el fin de comprender las variables fundamentales de

los procesos de adsorción y reacción involucrados.

Palabras clave: Furcraea andina, nanopartículas de hierro, mercurio, Orange II,

tratamiento aguas residuales.

Abstract

Treatment of industrial wastewater for bleaching and removal of heavy metals using

heterogeneous, economic and feasible processes has been a topic of interest at industrial

scale. Currently, sciences such as nanotechnology have potentiated the properties of

composite materials, which have enabled the use and implementation of nanoparticles as

active phase in catalysts and adsorbent materials. Particularly, iron nanoparticles have

been used in the removal of heavy metals such as mercury and arsenic through

operations such as adsorption and they have been used in advanced oxidation processes

in which, Fenton process of degradation and mineralization of water from textile industries

is performed. In addition, the current need to generate products and processes with

sustainable basis has made possible the implementation of the use of natural fibers as

potential matrices of composite materials. For this reason today much of the research has

focused on the use of lignocellulosic materials, in order to exploit the mechanical, physical

and chemical properties of cellulose. In this MSc thesis, a catalytic material was developed

from the use of fique fiber as support of iron nanoparticles. A pretreatment of the raw fiber

was performed in order to create the appropriate chemical an physical conditions on the

fiber surface to support the iron; a functionalization process was carried out to further

improve the anchorage to the surface; finally, wet impregnation was used to incorporated

iron nanoparticles on the support surface. A detailed characterization of the synthesized

material was performed via by gravimetric, volumetric and instrumental analytical methods.

This MSc thesis also explore potential applications in the treatment of wastewater, in

which promising results were found with respect to degradation and mineralization of

azodyes such as Orange II and the removal of heavy metals such as mercury. Both

applications were analyzed in order to understand the relevant variables involved during

the adsorption and reaction processes.

Keywords: Furcraea andina, iron nanoparticles, mercury, Orange II, wastewater

treatment.

Preface

The research developed in the MSc thesis is the continuation of a work that Chacón,

Combariza and Hinestroza [1], in the year 2013 began at the Universidad Industrial de

Santander (UIS). They performed a material for degradation of the dye indigo carmine

using a biocomposite of nanostructured from MnO2 and fique fibers. It was interesting for

me, because since my undergraduate thesis I found possible applications that might add

value to a residue as the fique fiber, accepting challenges from the social point of view

(waste water treatment to increase access to the natural resource and time to help the

fiquer community increasing their motivation in the crop), economic (synthesis of an

economic and feasible catalyst from composite materials that the process of scaling to

render practicable), environmental (contribution to issues such as the use of waste and

decontamination of liquid effluent) and technical (implementation combined with the use of

natural fibers and nanotechnology).

The general objective of this thesis is to develop an active, stable and inexpensive

catalytic material, using iron nanoparticles, supported in fique fiber for water treatment

processes of aqueous liquid effluents contaminated with metals and organic compounds

and the specific objectives are: 1) Synthesizing an iron nanoparticles catalyst supported on

fique fiber, 2) to characterize structural, thermal and mechanically the catalyst

obtained, and 3) to evaluate the ability of the catalyst on the removal of mercury ions and

dye Orange II. The first and second specific objectives were accomplished in the work

presented in Chapters 2 and 3, while the third specific objective was achieved in Chapters

4 and 5. One of the underlying goals of this thesis is to provide the research group and

anyone who want to research on this field with the basic knowledge about the main

concepts. This is why the Chapter 1 of this thesis is a general introduction to the topics

developed in this thesis.

The final point to address in this preface is the language of this document and the

structure of the chapters. All chapters, except for the introduction, were written as

individual papers with the aim to be submitted to international journals for publication.

Contents

Page

Acknowledgements ............................................................................................................ XIX

Resumen............................................................................................................................. XXI

Abstract ............................................................................................................................. XXIII

Preface.............................................................................................................................. XXVI

List of Figures ....................................................................................................................... 21

List of Tables ........................................................................................................................ 25

Chapter 1. Introduction ......................................................................................................... 27

Decontamination treatments of water-dye systems ......................................................... 35

Catalysts supports ............................................................................................................ 37

Iron nanoparticles ............................................................................................................. 44

References ........................................................................................................................ 47

Chapter 2. Physochemical treatment and characterization of Furcraea andina ................. 54

Abstract: ............................................................................................................................ 54

Keywords: ......................................................................................................................... 55

Introduction ....................................................................................................................... 55

Materials and methods ..................................................................................................... 56

Materials ........................................................................................................................ 56

Fiber pretreatment ......................................................................................................... 56

Fiber functionalization ................................................................................................... 56

Characterization ............................................................................................................ 57

Humidity ......................................................................................................................... 57

Chemical structural components .................................................................................. 57

Surface characterization ............................................................................................... 58

Structural characterization ............................................................................................ 59

Morphological and textural characterization ................................................................. 59

Thermal characterization............................................................................................... 60

Results and discussion ..................................................................................................... 60

Fiber pretreatment ......................................................................................................... 60

Fiber functionalization ................................................................................................... 63

Surface characterization ............................................................................................... 63

Contents XVIII

Structural characterization ............................................................................................ 67

Morphological and textural characterization ................................................................. 70

Thermal characterization............................................................................................... 73

Conclusions....................................................................................................................... 74

References ........................................................................................................................ 75

Chapter 3. Impregnation of iron compounds on natural and modified fique fiber ............... 79

Abstract: ............................................................................................................................ 79

Keywords: ......................................................................................................................... 79

Introduction ....................................................................................................................... 80

Materials and methods: .................................................................................................... 81

Catalyst Preparation ...................................................................................................... 81

Characterization ............................................................................................................ 83

Results and discussion ..................................................................................................... 84

Impregnation process .................................................................................................... 84

Mechanical characterization ......................................................................................... 95

Conclusions....................................................................................................................... 98

References ...................................................................................................................... 100

Chapter 4. Heterogeneous Fenton oxidation of Orange II using iron supported on modified fique catalysts ..................................................................................................................... 104

Abstract: .......................................................................................................................... 104

Keywords: ....................................................................................................................... 104

Introduction ..................................................................................................................... 104

Materials and methods ................................................................................................... 107

OII degradation ............................................................................................................ 107

Effect of chloride ion .................................................................................................... 109

Total Organic Carbon (TOC) and Total Nitrogen (TN) analysis ................................. 109

Identification of intermediate products resulting from the treatment of OII ................ 110

Results and discussion ................................................................................................... 110

OII degradation ............................................................................................................ 110

Effect of chloride ion .................................................................................................... 122

Total Organic Carbon (TOC) and Total Nitrogen (TN) analysis ................................. 123

Conclusions..................................................................................................................... 126

References: ..................................................................................................................... 127

Chapter 5. Studies on adsorption mercury from aqueous solution on biocomposite material from fique fiber and iron nanoparticles ............................................................................... 131

Abstract: .......................................................................................................................... 131

Contents XIX

Keywords: ....................................................................................................................... 131

Introduction ..................................................................................................................... 131

Materials and methods ................................................................................................... 133

Conclusions..................................................................................................................... 145

References ...................................................................................................................... 146

Conclusions and recommendations ................................................................................... 150

Annex .................................................................................................................................. 153

Annex 1 ........................................................................................................................... 153

Annex 2 ........................................................................................................................... 160

Annex 3 ........................................................................................................................... 163

Annex 4 ........................................................................................................................... 164

Annex 5 ........................................................................................................................... 166

Annex 6 ........................................................................................................................... 167

Annex 7 ........................................................................................................................... 168

List of Figures

Figure 1.1. Structural formula of the azo dye Orange II [ ................................................... 28

Figure 1.2. Details of the cellulosic fiber structure 2 ........................................................... 38

Figure 1.3. Molecular structure of hemicellulose 3 ............................................................ 38

Figure 1.4. Molecular structure of Lignin4 ........................................................................... 38

Figure 1.5. Furcraea andina (Personal archive) 5 .............................................................. 40

Figure 1.6. Potential uses of the products resulting from fique 6 ....................................... 41

Figure 2.1. Route used for functionalization of pretreated fique fiber 7 ............................. 57

Figure 2.2. pHzpc for the fiber according to treatment 8 .................................................... 64

Figure 2.3. FTIR - ATR spectrum of raw fique fiber, pretreated and functionalized .......... 65

Figure 2.4. EDS profile of raw, pretreated and functionalized fique fibers 10 .................... 67

Figure 2.5. XRD of raw and pretreated fiber (30, 60 and 90 minutes of sonication) 11 ..... 67

Figure 2.6. XRD of raw and functionalized fiber (1, 2 and 3 hrs of functionalization) 12 ... 68

Figure 2.7. SEM micrographs of the raw fiber 13 ............................................................... 71

Figure 2.8. SEM of the pretreated fiber M60 14.................................................................. 72

Figure 2.9. SEM of functionalized fiber MC3 15 ................................................................ 72

Figure 2.10. TGA for raw, pretreated and functionalized fiber 16 ...................................... 74

Figure 3.1. Mechanism of formation of iron nanoparticles 17 ............................................. 82

Figure 3.2. Color change on impregnated fibers 18 ........................................................... 84

Figure 3.3. Amount of Fe species impregnated on raw, pretreated and functionalized fiber

as a function of impregnation days 19 ................................................................................. 85

Figure 3.4. Chemical synthesis of nanoparticles by the impregnation method 20 ............ 86

Figure 3.5. XRD diffractogram profiles of functionalized fiber after 1, 2 and 3 days of

impregnation.21 .................................................................................................................... 89

Figure 3.6. FTIR spectrum of functionalized fiber after three different days of impregnation

(1, 2 and 3 days) and without impregnation 22 .................................................................... 91

Figure 3.7. Morphological analysis of the functionalized fiber surface after 1 day of

impregnation 23 .................................................................................................................... 93

Figure 3.8. SEM pictures of the functionalized fiber surface after 2 days of impregnation

25 .......................................................................................................................................... 94

Figure 3.9. Size distribution leached of iron nanoparticles (1day of impregnation) in

aqueous solution (Malvern Zetasizer Software)26 .............................................................. 95

Contents XXII

Figure 3.10. Curves stress vs strain of a) raw fiber b) catalyst with 1 day of impregnation

c) catalyst with 2 day of impregnation d) catalyst with 3 day of impregnation 27 ............... 97

Figure 4.1. OII degradation after 4 hours of catalytic activity performed under the following

conditions: Experiment 1 (Catalyst Fe10.9 wt.% and Dye 𝐶𝑂𝐼𝐼0: 2𝑥10 − 4𝑀), Experiment 2

(Dye 𝐶𝑂𝐼𝐼0: 2𝑥10 − 4𝑀 and oxidizing agent 𝐶𝐻2𝑂20: 5.05𝑥10 − 3𝑀), Experiment 3

(Catalyst 10.9 Fe wt.%, Dye 𝐶𝑂𝐼𝐼0: 2𝑥10 − 4𝑀, catalyst contained in aromatic bag28 ... 111


conditions: pH: 2.5, 𝐶𝑂𝐼𝐼0: 1.1𝑥10 − 4𝑀, 𝐶𝐻2𝑂20: 5.05𝑥10 − 3𝑀 and 10.9𝑤𝑡. % 29 ....... 111

Figure 4.3. Experimental and calculated results of the experimental design for Orange II

oxidation. Degradation Response (%)30 ........................................................................... 114

Figure 4.4. Residual plots for kapmod 31 ............................................................................. 114

Figure 4.5. Contour plot of Degradation (%) vs H2O2 and pH 32 ..................................... 116

Figure 4.6. Contour plot of Degradation (%) vs %Fe and pH 33 ...................................... 117

Figure 4.7. Contour plot of Degradation (%) vs COIIo and pH 34 ...................................... 117

Figure 4.8. Degradation OII, the left part initial color and the right the color after the

treatment under the conditions: pH: 2.5, COII0: 1.1x10 − 4M, CH2O20: 5.05x10 − 3M and

10.9 Fe wt. %)35 .................................................................................................................. 118

Figure 4.9. Effect of temperature ions in OII degradation after 4 hours of catalytic activity

under these conditions: pH: 2.5, 𝐶𝑂𝐼𝐼0: 1.1𝑥10 − 4𝑀, 𝐶𝐻2𝑂20: 5.05𝑥10 − 3𝑀 and

10.9 𝐹𝑒 %𝑤𝑡 36 ................................................................................................................... 120

Figure 4.10. Cycle number of use of OII degradation after 4 hours of catalytic activity


10.9 𝐹𝑒 𝑤𝑡. % 37 .................................................................................................................. 121

Figure 4.11. XRD of catalyst before and after Orange II treatment38 .............................. 122

Figure 4.12. Effect of chloride ions in OII degradation after 4 hours of catalytic activity


10.9 𝐹𝑒 𝑤𝑡%39 .................................................................................................................... 123

Figure 4.13. Structural formula of the azo dye Orange II 40 ............................................ 124

Figure 4.14. Chromatogram obtained with a UV-Vis detector at 483 nm of OII dye before

and after degradation 41 .................................................................................................... 125

Figure 4.15. Chromatogram obtained with a UV-Vis detector at 230 nm related with

benzene 42 ......................................................................................................................... 125

Figure 4.16. Chromatogram obtained with a UV-Vis detector at 310 nm related with

naphthalene 43 ................................................................................................................... 126

Contents XXIII

Figure 5.1. Percentage of removal at different loads of adsorbent material (pH=10, initial

concentration of mercury = 10ppm and 10.9 wt.% Fe)44 .................................................. 135

Figure 5.2. Final removal percentage of removal at different loads of adsorbent material

(pH=10, initial concentration of mercury = 10 ppm and 10.9 wt.% Fe) 45 ........................ 136

Figure 5.3. Mercury removal using raw fique fiber (pH=10, initial concentration of

mercury =10ppm).46 .......................................................................................................... 137

Figure 5.4. Experimental and calculated results of the experimental design for mercury

removal. Responses considered removal % 47 ................................................................ 142

Figure 5.5. Residual plots for qe 48 ................................................................................... 143

Figure 5.6. Contour plot of qe (mg/g) vs. pH and mercury initial concentration 49........... 144

Figure 5.7. Contour plot of qe (mg/g) vs. Fe wt% and mercury initial concentration 50 ... 145

List of Tables

Table 1.1. Degradation treatment of Orange II (OII) ........................................................... 28

Table 1.2. Influence factors on the adsorption .................................................................... 31

Table 1.3. Most common adsorbent materials .................................................................... 32

Table 1.4. Mechanisms used in mercury removal 4 ............................................................ 34

Table 1.5. Removal of mercury with residual biomass 5..................................................... 34

Table 1.6. Conventional treatment for water decontamination 6 ........................................ 36

Table 1.7. Methods of cellulose fibers preparation 7 .......................................................... 39

Table 1.8. Average weight distribution of the fique leave components, usable percentage

and applications 8 ................................................................................................................. 40

Table 1.9. Main components of fique fiber 9 ....................................................................... 41

Table 1.10.10Fique fiber quality standards classification .................................................. 42

Table 2.1. Fique fiber proximate analysis and structural carbohydrates and lignin (NREL)

analyses 11 ........................................................................................................................... 61

Table 2.2. Lignin content in fique fiber pretreated at different times 12 .............................. 61

Table 2.3. Carbohydrates present in raw and pretreated fique fiber 13 ............................. 63

Table 2.4. Results of the acidic and basic sites in the fique fiber in different stages of

analysis 14 ............................................................................................................................ 65

Table 2.5. Crystallinity index for raw, pretreated and functionalized fique fiber 15 ............ 68

Table 2.6. Calculated average crystallite size for raw, pretreated and functionalized fique

fiber 16 .................................................................................................................................. 70

Table 2.7. BET surface area of raw, pretreated and functionalized fibers17...................... 73

Table 3.1. XRF analysis of raw fique fiber and catalyst with 1 day of impregnation 18 ..... 87

Table 3.2. Acidic and basic sites determined by titration Boehm and pHzpc for the

impregnated functionalized fiber 19 ..................................................................................... 92

Table 3.3. BET surface area of functionalized fiber after impregnation 20 ......................... 92

Table 3.4. Summary of mechanical characterization for raw and impregnated fiber (1, 2

and 3 days) 21 ...................................................................................................................... 96

Table 4.1. Factors evaluated in the dye degradation of OII using iron supported on fique

catalyst 22 ........................................................................................................................... 108

Table 4.2. Experiments values of Box - Behnken experimental design, degradation

percentage obtained for each experimental conditions 23 ................................................ 112

Contents XXVI

Table 4.3. Analysis of variance (ANOVA) for percentage of degradation by MiniTab 16

Statistical Software24 ......................................................................................................... 113

Table 4.4. Simplified pseudo-first-order kinetic analysis 25 .............................................. 120

Table 4.5. Total Organic Carbon (TOC) and Total Nitrogen (TN) analysis results 26 ..... 124

Table 5.1. Factors assessed in mercury removal using a adsorbent from Fique and iron

nanoparticles27 .................................................................................................................. 134

Table 5.2. Adsorption isotherms models 28 ...................................................................... 137

Table 5.3. Langmuir and Freundlich isotherm models results for the Hg adsorption on raw

fique fiber 29 ....................................................................................................................... 138

Table 5.4. Experimental levels used in the design of experiments Box - Behnken and

values obtained for the Langmuir isotherm model and Langergren model of adsorption 30

............................................................................................................................................ 138

Table 5.5. Pseudo-second-order kinetic model of adsorption 31 ..................................... 139


values obtained for the Lagergren Pseudo-second-order kinetic model 32...................... 139

Table 5.7. Analysis of variance (ANOVA) for qe (mg/g) by MiniTab 16 Statistical Software

33 ........................................................................................................................................ 141

1. Introduction 27

Chapter 1. Introduction

The spread of a wide range of contaminants in surface and groundwater has become a

critical issue worldwide, due to population growth, rapid industrialization and development

of long-term drought. Persistent pollutants in wastewater include heavy metals, inorganic

and organic molecules, and many other complex compounds. As a result, the number of

available water resources in nature to sustain life has been decreasing over time,

becoming one of the biggest problems nowadays, because of the diversity of pollutants

and the rapid depletion of available sources. Therefore, there is the need for controlling the

harmful effects of pollutants and to improve the conditions of human life.

Industrial processes related to food and textiles, among others, use natural or artificial

dyes, which are irresponsible and constantly discharges into rivers and seas. In particular,

in Colombian, due to the presence of an active textile industry in the vicinity of the Medellín

river, regional and national authorities have shown a growing interest into have some cost

effective solutions.

The dyes and pigments industry plays an important role in several economic sectors, for

example textile and food. There are important differences between pigments and dyes; a

pigment is a colored, insoluble substance that does not adhere directly to the substrate,

but through an adherent vehicle, usually a polymer, which supports and adheres to the

substrate [1]. Dyes are chemical compounds that after applied to a substrate (textile fiber,

paper, plastic, leather or foods), they can be absorbed on it, providing a permanent color.

Dyes are usually applied in solution or emulsions that presents affinity to the substrate in

which is going to be absorb. Current world dyes production is in the order of 90 million kg

per year [2].

Dyes can be classified using different characteristics; they can be natural or artificial, also

depending on the chemical structure (organic or inorganic) [3]. Another way to classified

dyes is based on the method use to apply them: reactive, disperse, direct, sulfur, basic

cationic, anionic or acid, mordant, solvent dyes, among others.

28 Wastewater treatment using an iron nanocatalyst supported on Fique fibers

One of the most representative dye in the textile industry and also one that shows

increasing challenges for its treatment is Orange II (C16H11N2NaO4S). Orange II is a

heterocyclic anionic azo compound from the group of naphthols (Figure 1.1), use as dye in

textile, cosmetic, silk and paper industries [9]. Orange II is also known as: OII, acid orange

7, acid orange A, 2-naphthol orange, CI 15510, D&C orange 4, COLIPA C015 and sodium

4-[(2E)-2-(2-oxonaphthalen-1-ylidene)hydrazinyl]benzenesulfonate [4].

Figure 1.1. Structural formula of the azo dye Orange II [4]

Orange II is a non-biodegradable azo-dye commonly emitted by the textile industry in

waste water effluents [5, 6]. It poses a potential risk to human health and has even been

reported as carcinogenic [7, 8]. Some degradation treatment methods developed for

Orange II are listed in Table 1.1:

Table 1.1. Degradation treatment of Orange II (OII)

Heterogeneous

Fenton-like

process using a

zeolite Y-Fe

It has been investigated the effects of pH, temperature, Cl- ions

concentration, O-II initial concentration, hydrogen peroxide and

ferrous ion catalyst (Fe2+) concentrations in the degradation rate.

Also, it was validated in a continuous stirred tank reactor (CSTR),

achieving O-II final concentrations of 5.9 × 10−5 M [5].

Fenton-like

oxidation using

heterogeneous

catalyst based

on bentonite

clay

Degradation and mineralization of O-II solutions using impregnated

saponite with different iron salts (iron(II) ethyl acetate, iron(II) oxalate

and iron(II) acetylacetonate and loads of 7.5, 13.0 y 17 % in weight).

The best conditions achieved degraded 99% of dye with 91%

reduction of total organic carbon (TOC) at 70°C, using only 90 mg of

catalyst per liter of solution, and the amount of iron leached in the

final solution was less than 1 ppm [6].

Heterogeneous

Fenton-like

oxidation using

catalyst of

carbon-Fe

Heterogeneous Fenton-like oxidation process, used hydrogen

peroxide for catalyst activation with two types of carbon support

(active carbon and iron oxide aerogel) impregnated with iron (7% in

weight). The catalyst based on aerogel showed good catalytic yield,

with mineralization up to 90%. However, iron leaching is

considerable, generating a progressive deactivation [7].

However, contamination of water sources is not only due to industrial processes related

with textiles and dyes. Also, mining processes generated heavy metals residues and

transforms environmental ecosystem conditions (temperature, pH, salinity), thereby

1. Introduction 29

increasing the toxicity of effluents. Particularly, mercury has become an important vector of

contamination in areas were mining of noble metals is active (especially in illegal

extraction operations). Mercury is a high density heavy metal, silver in appearance, liquid

at room temperature, presenting toxic effects on living beings and having the capability to

accumulate in food chains [8]. It has physicochemical properties such as high thermal and

electrical conductivity, high surface tension and chemical stability, making it a useful

material in the production of thermometers and other measuring instruments, dentistry,

batteries, electronic, electrical and lighting components [9].

Mercury is found naturally in the planet, due to erosion of earth's crust and volcanic activity

[10]. Mercury occurs in deposits throughout the world mostly as cinnabar (mercury sulfide).

It is also release as a byproduct in many chemical processes such as coal burning and

chlorination plants among others; however, one of the major source of mercury

contamination is the gold extraction process [8].

Hg can exist in several forms: elemental (metallic), inorganic or organic (such as

methylmercury, which enters the human body through food) [10]. Particularly,

methylmercury presents an aggravating problem because is retained in the membranes of

autotrophs organism, then, as heterotrophic organisms feed on autotrophs it becomes an

accumulated material in the food chain; specifically fishes accumulate Hg in great

quantities as methyl mercury, which are subsequently consumed by humans [11].

This metal could be a potentially harmful substance to humans and the extent of its health

impact depends on variables as: compound state (organic, elemental, inorganic), degree

of exposure, exposure source, route of absorption, concentration and interaction with other

substances [9], [12]. Exposure to mercury in the short and long time, may cause serious

health problems, such as: brain damage, kidney damage, lung, digestive system

problems, tremors, changes in vision and hearing, insomnia, memory disorders, nausea,

vomit, diarrhea, seizures, among others [13].

The Environmental Protection Agency (EPA) has developed regulations related to the

maximum allowable concentration for methylmercury in water, estuarine fish and shellfish

tissue to ensure the safety of the population that consumes or handles this kind of food [8].

The current reference dose (RfD) is 0.1 μg/kg/day [9].


Additionally, organizations like the FDA (Food and Drugs Administration) established a

dose of 0.23μg/kg/day, recommending that pregnant women limit fish consumption,

likewise other world organizations (WHO, World Helth Organization and ATSDR, Agency

for Toxic Substances and Disease Registry) determine levels up to 0.47 μg/kg/day,

respectively [8].

According to the WHO, mercury is one of ten products or groups of chemicals that pose

special public health problem due to its high contamination potential and its widespread

use in not regulated industries [10]. This last issue is of special interest in Colombia, where

illegal mineral extraction use extensive quantities of mercury, affecting both atmospheric

and water quality [14]. This problem is particularly alarming in the small-scale gold mining

process (usually artisanal performed), where one kilogram of gold obtained released into

the environment three to five kilograms of mercury [15]. Increasing the statistics of

Colombians health problems related to neurological symptoms, decreased motor skills,

impaired hearing and vision, among others [8]. Although gold mining is an activity with

significant importance in Colombian economy (producing 30 tons per year), environmental

control is poorly structured, especially in the areas where handmade extraction is

practiced; creating at the same time environmental liabilities, turning this practice into an

unsustainable process [15] [16].

Since 2009, Antioquia have imported 520 tons of mercury, from countries such as Mexico,

Germany, Spain, United States and the Netherlands. Affecting the population health of at

least 16 municipalities, considering Antioquia the most polluted region in the world with

mercury and rivers in the Segovia and Remedios area as the third most contaminated

rivers with this metal [17]. Similarly, in Choco, gold mining is promoted through the burning

of amalgam, which is the mixture of gold with mercury. In one of the latest reports, there

are 80 municipalities in 17 departments of Colombia contaminated with mercury, cyanide

and fuels, resulting from informal gold mining [20].

Mercury pollution have caused several impacts in hydric resources such as the reduction

of dissolved oxygen in effluents, obstruction of water flow and ecosystem modifications by

environmental implications on flora and fauna [16]. There are some studies reporting

concentrations of total mercury as high as 6,118 ppm, which are above the established

values by national and international standards [18].

1. Introduction 31

The maximum allowed Hg concentration in Colombia is regulated by the National

Legislative Decree 3930 of 2010 [19], in which Article 20 considers mercury as a

substance of health interest. Articles 38 and 39, in the same decree, state that the

maximum permissible concentration for human and domestic consumption is 0.002 mg/L.

The same decree cover the maximum concentration in products of the livestock sector

(Article 41, 0.01mg/L). Additionally, Article 91 prohibited the discharge of any mercury

contaminated waste into water bodies, such as the ones used to provided potable water to

human population [19]. Decree 475 of 1998 defines 0.001 mg/L to be the maximum value

of total mercury in water permitted in Colombia; however, none of the decrees set limits for

methylmercury.

Mercury separation through “adsorption” specifically by physisorption, leverage the

physical interactions between the solid surface and the adsorbate. The adsorptive

separation is based on three different mechanisms: steric (the adsorbent has pores of

such size that allows to pass only molecules with a specific size), kinetic (different diffusion

rates of compounds in the pores) and equilibrium (adsorbents have different affinities to

accommodate different species) [20]. Depending the nature of these forces, the adsorption

can be classified into two general types:

Physical adsorption or physisorption:

Established interactions between the solid surface and the adsorbate are physical in

nature (Van der Waals force), doesn’t share or transfer electrons, reversible process,

with low heat of adsorption.

Chemical adsorption or chemisorption:

Established forces are true chemical bonds which makes the process irreversible. It

occurs only on the active centers with high values of adsorption heats. Some factors

that influence the adsorption of a given compound are presented in the Table 1.2:

Table 1.2. Influence factors on the adsorption

Solid properties

Surface (A larger adsorbent surface gives greater absorption and

greater adsorption). Pore size distribution (determine accessible

surface adsorption) and particle size of the adsorbent.

Nature of

adsorbate

Solubility of the adsorbate in the solvent, adsorbate structure

(presence of functional groups promotes solid-solute interactions),

molecular size of the adsorbate (affects the rate of adsorption) and

ionic nature of adsorbate (adsorbate net charge).


Characteristics

of the liquid

phase

pH (determine concentration of hydronium and hydroxyl ions in the

medium, setting the degree of dissociation), temperature (increasing

temperature generates a reduction in adsorption) and nature of the

solvent (affinity of the solid by the solvent and adsorbate).

Competition

between

adsorbates

The presence of multiple adsorbates can influence the adsorption

capacity and processing rate.

Different materials can be used as adsorbents, depending on the application, price,

mechanical and chemical resistance, abundance, easiness to use, easy regeneration,

adsorption capacity and surface area. Table 1.3. resumes general characteristics of some

commercially available adsorbents:

Table 1.3. Most common adsorbent materials

Carbonaceous materials

Activated

charcoal

Carbonic porous material made by treatment of charcoal with oxidizing

agents or burning of carbonaceous materials impregnated with

dehydrating agents, with high internal surface, removes residues at low

concentrations [21].

Carbon

nanofibers

(NFC)

Discontinuous carbon filaments with diameters ranging from 20 to 80 nm ,

with an internal structure similar to graphite, also similar to nanotubes in

shape and dimensions, with variations in orientation of the planes [22].

Also with low expansion coefficients and good mechanical, electrical and

thermal properties. There are 4 types of NFC, Platelet, Fishbone or

Herringbone, Ribbon and Stacked cup.

Carbon

Nanotubes

(NTC)

Long cylinders made from hexagonal graphite lattice, comprising one or

more cylindrical and concentric layers of graphite with a 0.34 to 0.36nm

spacing. It can be synthesized by means of electric arc discharge (EAD),

laser ablation (LA) and chemical vapor deposition (CVD) [22]. The

structure of the NTC confers different properties such as hardness and

stiffness, elasticity, heat resistance, and mechanical strength, specific

surface area and high thermal stability. There are single-walled nanotubes

(SWNT: Single Wall NanoTube) or multiple wall (MWNT: Multi Wall

NanoTube).

Carbon

xerogels

Materials synthesized by sol-gel method, where gravitational forces are

negligible and interactions are dominated by short-range forces like Van

der Waals and surface charges, showing Brownian motion [23].

Ordered

mesoporous

carbons

Materials with ordered porous structure and a complex chemical surface

with high surface area [24].

Clays

Mineral grains of less than 2 μm diameter, formed by silicate and aluminosilicate minerals

with sheet-like structures, with large surface areas that can absorb important amounts of

1. Introduction 33

water, having the property to change their volume by adsorption of water molecules or other

polar ions (swelling). All clays attract water to the surface (adsorption) but some of them

leading it into their structure (absorption)[25].

Bentonite Material with soapy properties and a structure of montmorillonite

(phyllosilicates added in the form of flakes), composed of two sheets of

oxygen and silicon tetrahedrons, and interlaminar spaces that can be

occupied by different cations. The final properties depend on the

production methodology [26].

Fuller's earth Clays with different mineralogical composition, mainly palygorskite,

calcium smectite and/or sepiolite, are used in bleaching and oil refining

[27].

Kaolinite Kaolin is the trade name for white clays. This clay have very low water

adsorption capacity [25].

Hydrotalcite Anionic clay with magnesium atoms tetrahedrically coordinated to six

hydroxyl groups, and some Mg2+ cations replaced by Al3+. Calcination

temperature has a very important effect on hydrotalcites and causes

changes in physical and chemical properties [28].

Sepiolite Natural and inert clay, with composition of hydrated magnesium silicate.

The raw extracted mineral is subjected to a grinding and drying processes.

It is a fibrous mineral with large surface area (900 m2/g), due to small

particle size and porosity [17].

Other adsorbents

Silicalite Zeolite with MFI structure type (tridimensional system with two types of

channels), with average pore size of 0.55 nm, useful in petrochemical

applications with an outstanding thermal and chemical stability [29].

Alumina There are many crystalline forms of alumina which can be achieved by

heating of various starting materials, it is made of aluminium oxide (Al2O3),

having surface areas of 150 – 400 m2/g with mesopores [30].

Bioadsorbent

Chitosan

Chitin is a N-acetyl-D-glucosamine linear polymer of high molecular weight

(abundant in fungal cell walls and crustaceans). Chitosan is derived from

chitin by hydrolysis, used as metal chelating polymer and for water

treatment processes in industries such as beer, wine and dairy [30].

Mixed

materials

Mixed materials are being developed to synergistically improve the

properties of its components; like clays and carbon composites for

decontaminating effluents and gaseous separation of N2 and O2 [31].

A new alternative, economic and efficient to remove mercury from aqueous effluents has

been investigated, using as a raw material waste byproducts from industrial or agricultural

processes (lignocellulosic biomass), which is used as an adsorbent [32]. A summary of

the typical mechanism involved in the mercury adsorption process are presented in Table

1.4.


Table 1.4. Mechanisms used in mercury removal 4

Mechanism Description

Complexation

or chelation

The metal attaches to the active centers onto the cell wall through

chemical bounds forming certain complexes [33].

Physical

adsorption

The phenomena associated with Van der Waals forces, in this case the

sorption is quickly and reversible [34].

Ionic

exchange

It is the proper one of the divalent metal ions that are exchanged with ions

of the polysaccharides present in the biomass. The process is also fast

and reversible [35].

Precipitation The mechanism is associated with the formation of a complex in the cell

wall subsequently it is hydrolyzed [36].

The use of different biomasses in the removal of heavy metals such as mercury has been

reported, below in Table 1.5. some examples are shown.

Table 1.5. Removal of mercury with residual biomass 5

Biomass Example

Sorption

Equilibrium of

Mercury onto

Ground-Up Tree

Fern

Ho et al.[37], studied the behavior of mercury adsorption in aqueous

solutions, using arborecenses ferns. It was found that the adsorption

capacity depends on the temperature. The maximum adsorption was

26.5 mg/g at a temperature of 25°C.

Removal of

Mercury using

eucalyptus bark

This study proposes the use of eucalyptus bark (Eucalyptus

camaldulensis) as a bioadsorbent for the removal of Hg (II) in aqueous

solutions. The performance variables studied were adsorbent dosage,

ionic strength, stirring speed, temperature, solution pH, contact time,

and initial concentration of the metal. The experiments indicated that

the adsorption capacity was dependent on the operating variables and

the process was strongly pH dependent. Kinetic measurements showed

that the process was fast and uniform. Among the kinetic equations

studied, the pseudo second order equation best described the process.

The maximum adsorption was 33.11 mg/g at 20°C [38].

Studies of guava

(Psidium

guajava) bark as

bioadsorbent for

removal of Hg

(II)

Biosorption of Hg (II) was investigated by the use of guava bark

powder. In the investigation a batch system was used, and the effects

of various parameters such as contact time, initial concentration, pH

and temperature were analyzed. It was found that the elimination of Hg

(II) is pH dependent, with maximum adsorption at pH 9.0. In the kinetic

study the pseudo-second order equation was the one that most

adjusted the experimental data. The maximum adsorption was 3,364

mg/g reaching 80 min, it has been shown that the guava bark powder

can be efficiently used as a low cost alternative for the removal of

divalent mercury from aqueous solutions [39].

Sorption of The adsorption of Hg (II) in aqueous solution under variable conditions

1. Introduction 35

Hg(II) onto

Carica papaya

of contact time, metal ion concentration, adsorbent dose and pH was

evaluated by Basha et al. [40]. The results indicate that the adsorption

equilibrium was established about 120 min. The adsorption of Hg (II)

was strictly pH-dependent, and the maximum removal of 70.8 mg/g was

observed at pH 6.5. The kinetic data fit well into the kinetic equation of

pseudo-second order. This work illustrates an alternative solution for

the use of the papaya tree, which is discarded at the end of its useful

life. Therefore, its use for the removal of heavy metals from

contaminated water can be a novel and cost-effective alternative.

Use of rice straw

as biosorbent

for removal of

Hg(II) ions

Rocha et al. [41], carried out adsorption experiments using rice ear

as a biosorbent of Hg (II) ions in aqueous solutions at room

temperature. To obtain the best adsorption conditions, the influence of

pH and contact time was investigated. This adsorption process was fast

reaching equilibrium before 90 minutes, with a maximum at pH 5.0. The

maximum adsorption capacity of Hg (II) metal ions was 0.110 mM/g. In

addition, an excellent result was shown with the use of the ear of rice

as bioadsorbent of metallic ions of mercury in industrial effluents.

Removal of

mercury from

aqueous

solutions using

waste from

Ceiba

pentandra,

Phaseolus

aureus and

Cicer arietinum

Ceiba pentandra (Ceiba), Phaseolus aureus (Jewish) and Cicer

arietinum (chickpea), are trees and plants that grow in India, mainly in

high temperature areas. The shell of the ceiba, jewish and chickpea

crop wastes, are agricultural residues that can be used as

bioadsorbents in aqueous solutions [42].

This study was carried out in a batch process, and the influence of

parameters such as pH, contact time, initial concentration of mercury

ions and the adsorbent dose were analyzed. The experiments showed

that the adsorption process corresponds to the pseudo-second order

kinetic models. With an initial concentration of Hg (II) of 40 mg/l, a

maximum removal of 25.88 mg/g was obtained for the ceiba, 23.66

mg/g for the jewish and 22.88 mg/g for the residues of Chickpea.

Decontamination treatments of water-dye systems

Currently dye contaminated water is an important environmental problem with significant

impact due to their high toxicity and the wide spread use of dyes in industry. Nowadays,

more than 100.000 types of dyes are available worldwide and more than 50% of them

have very low lethal doses (LD50) around 2x10-3 mg/kg [43]. Raising up the challenge to

develop efficient water treatment processes.

Printing, photographic, textile and paper industries are major dye pollutant industries,

generating the need for appropriate management of water waste, including treatment and

disposal systems. In order to oversee the legislation and actions to control and prevent


dye contamination in water sources the Ecological and Toxicological Association of Dyes

and Organic Pigments Manufacturers (ETAD) was created in 1974.

Today, different treatments are applicable to industrial wastewater, these can be physical

(the compound does not undergo transformation in its structure), chemical (there is a

chemical change in the compound) and biological (use of microorganisms to remove

contaminants). Conventional treatments that have been used are described in Table 1.6.

Table 1.6. Conventional treatment for water decontamination 6

Chemical oxidation [44]

Incineration Pollutant concentration is sufficiently high and the waste require high

temperatures up to 800°C.

Non catalytic

wet air

oxidation:

WAO

Oxidation with dissolved oxygen from air or oxygen-enriched gas

streams, is used to create hydroxyl radicals as oxidizing agents.

Catalytic wet

air oxidation:

CWAO

Complete mineralization of organic contaminants with inorganic

compounds such as ammonia and cyanides, using air or oxygen as

oxidizing agent, improves process costs.

Supercritic

wet air

oxidation:

(SCWAO)

Oxidation by air (enriched or not in oxygen) at high temperatures

(250-400 °C) and high pressure (200-300 atm). The water/air fluid

acts as a single phase, at industrial scale makes a total mineralization

of organic pollutants (conversion to CO2 y H2O), process with high

costs.

Advanced oxidation process (AOP) [45]

Homogeneous

Ozonation in

alkaline

medium

The decomposition of ozone in water increases, generating the

oxidation of organic pollutants in a direct way (reaction between the

organic molecule and dissolved ozone) and indirect way (hydroxyl

radicals are oxidants).

Ozonation

with hydrogen

peroxide

Hydrogen peroxide combined with ozone generate the decomposition,

forming one mole of hydroxyl radicals per mole of ozone decomposes.

Fenton

(Hydrogen

peroxide and

catalyst)

The reaction of hydrogen peroxide with transition metals (iron),

generates highly reactive radicals (hydroxyl). It is used for treatment

of pollutants such as phenol, formaldehyde, BTEX (benzene, toluene,

ethylbenzene and xylene) and pesticides.

Ozonation

and UV

irradiation

Is carried out by an electric discharge field as in the CD-type ozone

generators (corona discharge simulation of the lightning), or by

ultraviolet radiation as in UV-type ozone generators (simulation of the

ultraviolet rays from the sun).

Electro-

Fenton

Oxidative capacity of hydrogen peroxide increases in acid medium as

salts containing Fe+2 can regenerate the catalyst from Fe+3.

1. Introduction 37

Hydrogen

peroxide and

UV irradiation

The rate of photochemical reactions with organic matter can be

increased with the addition to ozone, hydrogen peroxide or both.

Photo-Fenton Production of hydroxyl radicals by Fenton's reagent and UV

irradiation, promotes Fe (III) complex formation, allowing regeneration

of the reduced form of the catalyst.

Electrochemic

al oxidation

Use electrical power to break the bonds of molecules, electrons are

transferred to the organic compound.

Heterogeneous

Catalytic

ozonation

Use of transition metal oxides (MoO3, TiO2, Cr2O3), supported metals

on oxides (Cu/Al2O3, TiO2/Al2O3), granular active carbon (GAC) and

mesoporous systems (silicates MCM or SBA).

Photocatalytic

ozonation

Photoexcitation of a solid semiconductor as a result of absorption of

electromagnetic radiation, generating excitation of electrons in the

valence band of the solid, causing the formation of voids

characterized by a very high oxidation potential.

Membranes [46]

Semi-permeable physical barriers separating two phases, prevents their intimate

contact and restricting the movement of molecules, having the capacity to provide high

flows of permeate and manufacture in compact and in some cases in inexpensive

devices.

The large flows of contaminated water necessary to treat in both cases, Orange II and/or

mercury, required catalysts/adsorbents materials that must be easily to remove from the

decontaminated water, then, heterogeneous catalysis have been extensively applied in

industrial applications because of their straightforward separation, which often results in

lower operating costs. Under this consideration a solid catalyst/adsorbents material

becomes an interesting option for this application and therefore it is important to define the

type of support and active phase that these material will be made of.

Catalysts supports

Currently there is a great interest in the use of renewable natural materials as solid

catalysts supports and as adsorbent materials. Their use could contribute to the solution of

several environmental problems, taking advantage of their physical and chemical

properties such as low density, biodegradability, flexibility, high wear resistance and

excellent thermal degradation.

Natural supports such as fibers are lignocellulosic compounds formed by cellulose,

hemicellulose and lignin. Particularly cellulose, is a highly attractive material in the

development of novel supported catalyst because its mechanical and chemical properties,


considered a "green" material and not least, presence of large number of hydroxyl groups

which are chemically available for a huge number of different functionalizations, allowing

the modification of the physicochemical properties according to the target application [47].

Figure 1.2. Details of the cellulosic fiber structure [36] 2

Figure 1.3. Molecular structure of hemicellulose [37]3

Figure 1.4. Molecular structure of Lignin [38] 4

In relation to the hemicellulose, is one of several heteropolymers, such as arabinoxylans,

present along with cellulose in almost all plant cell wall. While cellulose is crystalline,

strong, and resistant to hydrolysis, hemicellulose has a random, amorphous structure with

1. Introduction 39

little strength. It is easily hydrolyzed by dilute acid or base as well as myriad hemicellulase

enzymes [48], its molecular structure is shown in Figure 1.3.

Lignin is a group of complex organic polymers that form important structural materials in

the support tissues of vascular plants and some algae, lignin is particularly important in the

formation of cell walls, especially in wood and bark, because they provide rigidity and do

not rot easily. Chemically, lignin is a cross-linked phenolic polymer [49], its chemical

structure is shown in Figure 1.4.

Several methods have been reported to prepare cellulose nanofibers from plants as Jute,

Sisal and Kenaf [39 - 41]. Based on the mechanisms of fiber preparation, they can be

classified in three groups: chemical, enzymatic and physical extraction methods, as

presented in Table 1.7 [53].

Table 1.7. Methods of cellulose fibers preparation 7

Chemical

preparation

methods

The nanorods may be homogenized cellulose pretreated with an acid

solution of microcrystalline cellulose (MCC). Some other cellulose fibers of

approximately 200 to 400 nm long and 12 nm of wide, can be dispersed in

an organic medium of dimethylacetamide/lithium chloride (DMAc/LiCl) [54].

Another method is to disperse the cellulose (nanofibers) in water and to

add the radical 1-oxyl-2,2,6,6-tetramethylpiperidine (TEMPO) in order to

oxidate the wood pulp (Kraft). Some primary hydroxyl groups in

polysaccharides including β-glucose in cellulose are selectively oxidized to

carboxylate groups by TEMPO, with the advantage that oxidation

mediated by TEMPO can be introduced in native cellulose, maintaining the

fibrous morphology and crystalline characteristics [53].

Enzyme

preparation

methods

The bacterial cellulose of seaweed and ramie cotton can preferably

degrade by Trichoderma viride, turning waste into Iβ cellulose[55].

Nanofibers of 40 nm can be obtained, are used for reinforcement in

composite materials based on polymers.

Physical

preparation

methods

Mechanical processes can be done in a high pressure homogenizer. This

yield the division and disintegration of cellulose fibers and exposing

smaller microfibrils and nanofibrils with diameters in the range of 10-100

nm[56].

https://en.wikipedia.org/wiki/Organic_polymer

https://en.wikipedia.org/wiki/Vascular_plant

https://en.wikipedia.org/wiki/Algae

https://en.wikipedia.org/wiki/Cell_wall

https://en.wikipedia.org/wiki/Wood

https://en.wikipedia.org/wiki/Bark

https://en.wikipedia.org/wiki/Phenols


An example of a lignocellulosic material is the Fique fiber (Furcraea andina), plant from the

american continent, with more than 400 species reconigzed. It has fleshy fibrous leaves,

with or without thorns. Fique plants have long roots, bloom once per year and with a size

that varies accordimg to the specie. Since ancient times this plant have been known by the

name of “Woderland Plant”, because the varies uses that have been given to it, including

drugs extraction, production of fermented beverages, mops, among others [57].

Figure 1.5. Furcraea andina (Personal archive) 5

In Colombia fique crops are mainly located in the Andean region, in territories where the

climate is temperate. The most relevant department in terms of fique production are:

Antioquia, Boyacá, Cauca, Nariño and Santander [23]. In terms of other type of natural

fibers, fique has mainly two competitors: Jute, a soft fiber used for packaging and textiles,

and sisal which is a fiber used in cordage. However, the fique fiber has two advantages: it

is not as soft as jute, but not as stiff as sisal [22].

Furcraea andina (Fique) plant, from the Agavaceae family Andina (see Figure 1.1), is

characterized by an erect stem with an average height of 2 to 7 m and average width of 10

to 20 cm; the trunk made up of 75 to 100 leaves (1 to 3 m long), radial shape, fleshy,

pointed, well-toothed and prickly; with greenish-white flowers "margüey" only that bloom

once a year. Fique has a lifespan of 10 to 20 years and a production peak of 3 to 6 years

[58]. Table 1.8 resumes an average weight distribution of the fique leave components,

their usable percentage and some of their applications:

Table 1.8. Average weight distribution of the fique leave components, usable percentage and applications [59] 8

Part Leaves

weight (%)

Useful percentage

(weight %)

Uses

1. Introduction 41

Fiber

Juice

Tow

Marc

5

70

8

17

4

40

3

10

Textile industry, packing

Extraction

Paper pulp

Construction materials

Fique leaves undergo a defibration process (operation that separates the bark from the

inner fiber) in a shredder machine. Defibration is the initial step in the transformation of

fique leaves. The several byproducts obtained have a wide range of applications, as

summarize in Figure 1.6 [59].

Figure 1.6. Potential uses of the products resulting from fique [58] 6

Long fibers only constitute 4% (weight) of the fique leaves and form the main structure of

the cell walls, mainly composed of cellulose, hemicellulose, lignin and pigments; each fiber

filament is composed of fibrils bonded together by lignin. An average chemical compound

weight distribution of fique fiber filaments is presented in Table 1.9.

Fique fiber and its byproducts could become excellent raw materials in various chemical

and physical processes due to its compatibility with several materials and its outstanding

mechanical properties (torsional strength, bending and tensile) [60].

Table 1.9. Main components of fique fiber [58]9

FIBER Weight %

Ashes 0.7

Long fiber

Packing

Agromants

Cordage

Crafts

Textils

Chaff

Paper

Fiber-reinforced

Stuffing mattresses

Thermal insulation

Organic fertilizers

Juice

Surfactants

Detergents

Cosmetic products

Alcohol

Bioinputs


Cellulose 73.8

Ream 1.9

Waxes and fats 1.9

Lignin 11.3

Pentosanes 10.5

TOTAL 98.2

In order to classified fique fiber, ICONTEC has developed a technical standard procedure

(NTC 992) that regulates the quality of natural fibers in Colombia, including definitions and

classification, setting the humidity and fiber length requirements [61]. Table 1.10 resumes

some of fique fiber characteristics use to determine fique fiber quality.

Table 1.10.10Fique fiber quality standards classification [59]

SORT OF FIQUE CHARACTERISTICS

Fine

- Good defibration

- Length greater than 90 cm

- Spall: low

- Free of knots and tangles ropes

- Free of diseases and pests

- Variable color

Ordinary

- Regular defibration

- Length greater than 90 cm

- Free of knots and tangles ropes

- Variable color

Short

- Good to regulate defibration

- Length lower than 90 cm

- Free of knots and ropes

- Possible entanglements

- Variable color

Fique long fibers have been used in the production of textile fabrics, threads, cordages,

packaging and crafts. Particularly in Colombia, the production of added value fique fiber

products is not well developed, although is an important job generator in some regions, the

economic gain margin is low; a fine quality fiber has a marked value in the order 1230

COP/kg meanwhile a low quality fiber has a marked value in the order of 1100 COP/kg,

reducing the incentives for an appropriated production of the fiber [59].

Some companies responsible for the production of packaging materials made up of fique

fiber are Cohilados del Fonce LTDA (San Gil), Compañía de Empaques S.A (Medellín),

Empaques de Cauca S.A (Popayán) and Hilanderías Colombia LTDA (Pasto).

1. Introduction 43

Currently, the fiber is used by Colchones Spring, Colchones El Dorado and Americana de

Colchones, to produce fique sheets as a new material called “microlink ®”, which is a fiber

agglomerate of fique and cotton, used as thermal insulator and structural reinforcement of

mattresses, it has been an innovative application of this natural product taking advantage

of the excellent strength, flexibility and thermal insulation of fique fiber [58].

Some recent studies have shown that the use of fique fiber for the design of reinforced

materials is an excellent alternative due to its biodegradability, diversity, renewability,

recyclability, wide availability, low energy consumption in manufacturing, competitive cost

(low cost per unit volume), low density and mechanical properties; even if after its lifespan

is over and recycling is not an option, production of renewable energy by incineration is an

available alternative [62].

Several studies have reported the mechanical effects of using fique fiber as reinforced

materials in composite materials. Latorre et al. [63], prepared an epoxy polymer matrix

reinforced with fique fiber used both as a protection and reinforcement of dented and light

corrode pipelines. This material stopped corrosion progress and presented excellent

adhesion to the pipeline surface, resistance to cathodic processes and mechanical

strength. Hidalgo et al. [62], reported a 212% increment of the mechanical strength and a

218% increment on elasticity for composites made out short fique fiber and LDPE (low

density polyethylene). Contreras et al. [64], used fique fiber as a reinforcing material in

polyester matrices and evaluated the strength, flexibility and impact resistant of the

produced matrices, concluding that fique fiber is an excellent alternative to replace

synthetic fibers, but also highlighting that imperfections such an uneven fiber diameter and

fiber impurities could decrease the quality of the products by acting as stress

concentrators. Hybrid materials made out of fique fibers, fiber glass and polyester resin

have been explored as a suitable material for the production of autobuses bumpers

(Paredes et al. [65]), finding that fiber length is the most influential parameter in the

mechanical performance of the hybrid material. Gañan et al. [66], studied the

crystallization process and thermal degradation of a thermoplastic polypropylene matrix

reinforced with fique fibers. The study found that the reinforcing material provides

enhanced thermal stability.

Other studies have explored not only the mechanical properties of fique fiber but also have

investigated its chemical properties in order to use the fiber as an adsorbent material,

catalyst support and some other applications. Gañan et al. [66], evaluated by FTIR- ATR,


SEM and TGA the effect of chemical treatment such as mercerization and salinization on

raw fique fiber. Deposition of metallic particles on modified fique fiber surfaces was

reported by Castellanos et al. [67], particularly gold nanoparticles were synthesized using

3-chloro-2-hydroxypropyl trimethyl ammonium chloride (CHTAC) as cationization agent in

strong alkaline conditions (NaOH). The study found that the molar NaOH/CHTAC ratio has

not significant influence on the size and distribution of the gold nanoparticles, it was also

determinate that the cationization process improved the fiber mechanical properties. Some

other type of nanoparticles has been explored, Chacón et al. [68], studied the degradation

of organic dyes on nanostructured MnO2/fique fiber catalysts, finding that Coulomb

interaction play a major role on the attachment of the MnO2 particle to the fiber surface.

Nanoparticle formation on the fiber surface was corroborated via FESEM. The synthesized

catalyst was very active in the degradation of indigo carmine dye, reaching degradation

values as high as 98% in less than 5 minutes.

Currently an increasing tendency in the world is to move back into the use of renewable

raw materials free of chemicals and not harmful to human health. To continue in this path,

it is important the implementation of policies that contribute the implementation of

elements for sustainable development, soil and water use, among others. Nowadays in

Colombia, there is an interest of the entities and institutions implicated in the fique fiber

chain production to find added values applications involving green chemistry and

designing cleaner production processes [34].

Iron nanoparticles

Nanotechnology applied in the improvement of water treatment processes has become an

important tool in environmental catalysis because it could provide innovative technical

solutions to control emissions, reducing the impact of existing technologies, eliminating no-

biodegradable molecules and disabling the most resistant organisms and potentially

creating new processes.

Nanomaterials could be very reactive because of its large surface area relative to volume,

and because the presence of a greater number of reactive sites. These properties allowed

more contact with pollutants, increasing reaction rates. Also, taking advantage of their

"nano" size; they can be impregnated on very small spaces, allowing particles to travel

farther, improving dispersion [69]. Silver, zinc oxides and iron oxides nanoparticles have

been used to carry out water purification of E. coli and arsenic [70]. Dufour et al. [71],

1. Introduction 45

developed filters that act as a ceramic "sponge" (prepared with natural clay), to retain

pollutants from textiles and domestic industries, this type of materials have the advantage

of being easy to manufacture, clean and reuse [70].

Studies conducted at Rice University, found an alternative to the water treatment of

effluents polluted with arsenic by taking advantage of the magnetic interactions of iron

oxide nanoparticles with carefully placed magnets. This significantly reduces the

environmental and health impacts [72] and allows to perform environmental risk

assessment in terms of toxicity, exposure and risk characterization [73].

Nanostructured catalysts have been also applied in the destruction of chlorinated organic

contaminants in water by using low concentrations of bimetallic core/shell nanoparticles,

taking advantage of a synergetic catalytic effect of gold nanoparticles coated with

palladium [74].

Nanostructured catalyst based on TiO2 also have been developed for photocatalytic

decontamination of water, this approach can be classified in three groups: the first group is

the use of pure TiO2 nanomaterial (first generation), where the more relevant catalytic

variable is the size of the TiO2 particle; the second generation corresponds to the metallic

doping of TiO2 to incorporate impurities in the crystal structure in order to increase the

radiation absorption capacity of TiO2, and the third generation of TiO2 based catalyst but

doped with nonmetals such us sulfur-doped TiO2 [75].

Another compound which has been used for the synthesis of nanoparticles are iron oxides,

in the forms of magnetite (Fe3O4), maghemite (γ-Fe2O3) and hematite (α-Fe2O3) are the

most common [76]. A nanometer scale this compound has shown great properties as

biocompability, size, large surface area, superparamagnetism and ability of surface

modification [77].

Additionally, techniques that allow easy synthesis and properties control of iron oxides

nanoparticles has been developed; increasing the versatility of the produced nanoparticles

in terms of size distribution, morphology, surface chemistry and magnetism [78]. However,

research continues in order to improve nanoparticle stability exploiting the possibility of

iron oxide to react with different compounds, avoiding aggregation and sedimentation,

increasing mobility and reactivity [79].


Based on the wide range of chemical and physical properties reported for oxide

nanoparticles, many catalytic application have been proposed, such as adsorbents,

enzyme immobilizers and wastewater treatments [80].

Today, novel applications for iron NP Fe0 are seeking greater flexibility in treatment, reuse

treatment agents, environmental safety (sustainability), optimization of costs synthesis and

modification, and very important, the possibility of scaling and easy separation [70].

However, the use of nano zero valent iron (nZVI) have found increasing applications in

environmental technologies and hazardous waste treatment, owing to their superior

reactivity, extremely small particle size and large surface area towards a variety of

recalcitrant contaminants and their enhanced capacities for contaminant abatement [82].

Although much work was devoted to the metal sorption and reduction by nZVI particles,

the exact contaminant removal mechanisms including the particle surface chemistry are

still not fully understood [83]. In order to demonstrate a mechanism, the zeta potentials

after the adsorption of Hg (II) ions have been measured, the surface charge of the

adsorbent with nZVI after exposure to the toxic metals is approached to zero. It is believed

that toxic metals as mercury is removed by the positive interactions between the negative

charge of the immobilized nZVI and the positive charge of the mercury solution which

eventually decreases the negative charge, due to the oxidation of Fe0 to Fe+2 and Fe+3 and

also adsorption/reduction of Hg(II) ions on the surface of nZVI. Demonstrated

chemisorption of Hg (II) ions onto supports with nZVI throughout the adsorption/reduction

processes are in line with the obtained kinetic and adsorption isotherm data [84].

Aditionally, there have been numerous studies that have demonstrated the ability of iron

oxide to remove contaminants from water effluents [77] these technologies are classified

into two groups: a) technologies using nanoparticles as adsorbents or as immobilizers for

improving removal efficiency and (b) using iron oxide nanoparticles as photocatalysts to

break or convert pollutants to less toxic forms.

Then, the window is open to develop new science that contributes to sustainable solutions

to a world that is beginning to recognize the need to remedy and fix the excessive damage

that has been done to nature. Consequently, there is a need of implementing new

technologies for the remediation of water sources; this research explore the development

of a catalyst-adsorbent material containing iron species as the active phase and fique fiber

1. Introduction 47

as support, based on the facts that iron species are active for this kind of treatments and

fique is a green removable material with very attractive physicochemical characteristics

applicable in this type of processes.

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1. Introduction 51

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1. Introduction 53


Chapter 2. Physochemical treatment and

characterization of Furcraea andina

Abstract:

A physicochemical pretreatment on the natural fiber fique (Furcraea andina) was

evaluated in terms of the modification of the physical and chemical fiber properies, as an

initial stage in the process of setting appropiate condition for its later use as alternative

matrix in the synthesis of a catalyst for removal of heavy metals and dyes. The fiber was

characterized structurally using the NREL methodology, determining the percentage of

lignin, cellulose and hemicellulose, obtaining values of 22.58, 36.3 and 28.15, respectively.

In addition, the pH of zero point of charge (pHzpc), the acidic and basic sites, humidity,

total solid and ashes were measured. The studied physicochemical pretreatment seeks to

expose and enable superficial sites (functional groups) that subsequently can act as

centers of nucleation in the synthesis of nanoparticles. Exposure of functional groups was

performed by means of a procedure assisted with ultrasound, varying the sonication time

(30, 60 and 90 min) finding 60 minutes of pretreatment as the most beneficial, evidencing

an increment of cellulose and reduction in the percentage of lignin and hemicellulose.

Subsequently, chemical activation of the sonicated fiber was held at different times of

functionalization (1, 2 and 3 hours) in cycles of acid-base treatments, Fourier transform

infrared spectroscopy (FTIR) - attenuated total reflection (ATR) and Energy-dispersive X-

ray spectroscopy (EDS) equipment coupled to a SEM probed that 3 hours of treatment is

the time with the highest impact in terms of surface functionalization and the same time,

the deposition of the sodium ions was verified. X-Ray Diffraction (XRD) was used to

determine the fiber crystallinity in all stages of the pretreatment; crystal size in the final

stage was 5 nm on average. Total surface area was improved by the pretreatment and it

was determinate applying the BET method by N2 adsorption isotherms. Scanning electron

microscope (SEM) micrographs showed in the pretreatment stage a fiber clean and free

from waste from the defibration process and a superficially more homogeneous fiber for

the functionalization stage. Finally, the thermal characterization by thermogravimetric

2. Physochemical treatment and characterization of Furcraea andina 55

analysis (TGA), revelaled a futher effect of the funtionalization process when compare with

raw and pretreated fiber samples.

Keywords: Furcraea andina spp, pretreatment, functionalization, treatment wastewater,

catalyst.

Introduction

Due to its mechanical and chemical properties, cellulose is a highly attractive natural

material, especially for the presence of a large number of hydroxyl groups useful to

perform a tailor made chemical functionalization and then provide specific physicochemical

properties according to the desirable application. Pretreatment and functionalization

processes with close control over the effects on the cellulose structure can help to

improve its properties (crystallinity, length, width and aspect ratio), producing materials

with a wide spectrum of applications, such as catalysts support and absorbing material,

among others, having the aditional advantage of being environmentally friendly.

Chacón Patiño et al.[1], Wang et al.[2], and Chattopadhyay [3] have shown that the

development of technological applications from cellulose is a good alternative for the

generation of materials with enhanced chemical, mechanical, thermal and catalytic

properties. Among available vegetable materials with high percentages of cellulose, fique

fiber presents exceptional properties in comparison with some widely used synthetic

polymers: this fiber is biodegradable, flexible, low cost, low density, with excellent thermal

and mechanical properties. In addition, as a social impact, fique provides employment to

about 70,000 families, contributing in some important areas to the substitution of illicit

crops in Colombia [4].

The goal of this study was to performe a complete characterization of the raw natural fique

fiber monitoring the effect of three different physicochemical pretreatments on the surface

chemistry, morphology and textural properties, crytalline structure and structural

properties, following the Nationational Renewable Energy Laboratory (NREL methodology)

[5]. The later, in order to find the pretreatment conditions that provide enhanced properties

to the fique fiber to be used as a catalytic support for the synthesis of nanoparticles.


Materials and methods

Materials

Raw fique fibers standardized in moisture, color, length, width, free of knots, diseases and

pests was provided by Compañia de Empaques S.A, who collects it from the Colombian

coffee region.

Fiber pretreatment

In order to removed lignin, hemicellulose, carbonates, chlorophyll, saponins and any other

waste present, a physical process (ultrasound) was performed;ultrasonic pretreatment has

been also reported to decrease cellulose crystallinity and increase lignocellulosic material

porosity [6]. 1g of raw fiber was submerged in a ultrasonic bath using an erlenmeyer

containig 200mL of deionized water (0.054 μS), sonication time was performed at three

different levels (30, 60 and 90 minutes, called M30, M60 and M90 respectively) at 42 KHz

and 100 W. After sonication the fibers were removed from the deionized water and dried

overnight at room temperature. The effect on the fiber structure in this process was

assessed following the NREL methodology for the determination of structural

carbohydrates and lignin in biomass [5].

Fiber functionalization

Functionalization of surface cellulose exposed during the ultrasound pretreatment was

performed following the procedure proposed by Wang et al. [2], The pretreated fiber was

placed in 200mL of HCl (5% vol.), varying exposure time at three different levels (1, 2 and

3 hours) at room temperature, then the fiber was rinsed with distilled water. Finally, the

fiber was placed in 200mL of NaOH (6% vol.) at 60°C also at three time levels (1, 2 and 3

hours. Called MC1, MC2 and MC3 respectively)), then rinsed with distillate water and dried

at 80°C for 12 hours. Each experiment was performed in duplicate and the results for each

time of functionalization were averaged.

Figure 2.1 section a, ilustrates the initial step of functionalization on the pretreated fiber by

immersion in HCl, causing acid hydrolysis of the polymeric chains of cellulose and

breaking intermolecular hydrogen bonding, and superficially degrading cellulose to form

hydroxylated surfaces [7].


The second step of the functionalization mechanism (Figure 2.1b) is achieved by exposing

the previously formed hydroxylated surface to NaOH as cationic agent, promoting the

formation of the corresponidng salts (RCH2ONa+) on the fique’s surface and cationizing

the fiber [8].

The chemical surface functionalization process performed on the pretreated fique fiber

allows the formation of cationic sites capable to chemically interact with a variety of

chemical elements and compounds, such as the incorporation of innorganic nanoparticles

[3, 9].

Figure 2.1. Route used for functionalization of pretreated fique fiber 7

Characterization

Humidity

Humidity of raw and pretreated fiber was determinate on 1g of fique using an infrared

radiation scale (PMB53-Adam) for 25 minutes, at 100°C; samples have not undergone any

other treatment previously to the humidity determination experiment.

Chemical structural components

The NREL [5] methodology was implemented for the determination of structural

components in the fique fiber. This uses two acid hydrolysis steps to fractionate biomass.

The first step allows the determination of the acid insoluble lignin in the sample (via


standarized gravimetry procedures). The acid insoluble residue was placed in a crucible

and loaded in a oven at 105°C (Labtech Essa) until constant weight, then the samples

were removed from the oven and cooled in a desiccator and their weight was recorded;

finally, the crucibles and residue were placed in a furnace (Thermo Scientific

Lindberg/Blue Moldatherm™) at 575°C for 24 hours, the weight of cold samples were

recorded again. The second step used UV-Vis spectroscopy to determined acid soluble

lignin, the absorbance of a hydrolysis aliquot was measured at wavelength of 320 nm

using as blank a solution of sulfuric acid 4%(v/v).

A second stage of the NREL characterization involves the fragmentation of the fibers into

soluble monomerics forms (glucose, xylose, arabinose and acetic acid) and quantification

using HPLC chromatography (VWR - HITACHI ELITE Lachrom system, consisting of a

model L-2130 quaternary pump and a IR detector, Model Shodex RI - 101). A stainless

steel Shodex SC1011 (300 x 8 mm I.D.) was used in the analysis. A gradient method with

HPLC grade water, filtered and degassed as mobile phase was employed in the

separation. Elchrom Elite software Chromatography data system was used for data

processing and reporting. The injection volume was 20 µL each time to achieve

reproducible injection, which was conducted with automatic injector (Model L-2220). The

flow rate was kept at 0.6 ml/min during the run and the temperature was kept at 85°C in

the separation column. Peak identities of the degradation products were confirmed by both

retention time and spectra matching of standard compounds.

Surface characterization

One of the goals of the treatment and functionalization processes is to modified both the

physical and chemical properties of the fiber surface, as the chemical environment of the

fiber surface is modified, properties such as the pH of zero point of charge and the acidic

and basic surface sites change too.

Determination of the pH of zero point of charge (pHzpc) was obtained using a drift method,

solutions with 45mL of KNO3 (1% vol.) were adjusted to an initial pH in the range of 2 to 10

by adding HCl 0.1M or NaOH 0.1M, the volume of each solution was completed up to

50mL by adding KNO3 (1% vol.) Once the pH of the solutions were set, 0.1g of fique fiber

(raw, pretreated or functionalized) were added and the suspensions were stirred for 24

hours at 25°C and then the pH of the supernatants were registered [9].


Acidic and basic surface sites were determined by the Boehm titration method [10]: 1g of

fique fiber (raw, pretreated or functionalized) was added to 50 mL of 0.1M NaOH (for acid

sites determination) or 0.1M HCl (for basic sites determination) solutions, stirred for 5 days

at 150 rpm and 30°C, then a 10 mL aliquot from each suspension was titrated with

standard solution; pH registry was performed up to a total volume of 25mL of standard

solution added.

Fourier Transform Infrared Spectroscopy (FTIR) was used to identify changes in the fiber

functional groups at different stages (raw, pretreated and functionalized). All samples were

left at room temperature overnight before being analyzed. FTIR were determined using an

ATR (PIKE) diamond crystal accessory at an angle of 45° attached to a FT-IR Nicolete iS

10 spectrometer (Thermo Fisher Scientific). Scans of 20 readings were performed by

spectrum; the data were recorded from 4000 to 600 cm-1.

Additional superficial chemical information of the fiber was obtained using Energy-

dispersive X-ray spectroscopy (EDS) equipment coupled to a SEM, this type of chemical

elemental analysis was performed in a Zeiss Auriga FIB-SEM (GeminiSEM) attached to

the Oxford INCA EDS equipment with MAX80 SDD detector system, operating in spectrum

collecting mode under high vaccum conditions, 20kV and approximate at a 5mm of

working distance.

Structural characterization

Crystalline information of fique fibers was measured at room temperature using a XPert

Pro MPD diffractometer with monochromator of crystal graphite using Cu Kα (λ = 1.5406

Å) at 40 KV and 30 mA. Diffraction patterns were obtained in the range of 2theta =10-40°,

with a step size of 0.02° and measuring time of 50s per step. Experimental data was

analyzed using PANalytical X'Pert HighScore Plus database.

Morphological and textural characterization

The total surface area was measured by the adsorption of nitrogen (N2) at 77 K, using a

Quantachrome NOVA e-Series surface area analyzers. N2 isotherms were performed on

fique fiber samples at different stages of treatment (raw, pretreated and functionalizated);

before N2 adsorption was performed on the samples they were degased at 80oC for 8 hr;

the calculation of the total superficial area was done using the BET method [11].


Morphologycal characterization of fique fibers was achieved via Field Emission Scanning

Electron Microscope (FESEM) performed on thin film gold coated samples using a Zeiss

Auriga FIB-SEM (GeminiSEM) scanning electron microscope, coupled to a secondary

electrons (SE2) detector. The micrographs were taken at 1.5 kV, working distance (WD)

ranging from 4.9 to 5.2 mm, at different magnifications.

Thermal characterization

Thermal gravimetric analysis (TGA) was performed to compare the thermal stability of

each sample, TGA analysis was performed using a thermogravimetric analyzer (TGA1,

Mettler Toledo), in a temperature range from 25 to 580oC at a heating rate of 5ºC/min in an

inert atmosphere (N2, flow of 50 mL.min-1).

Results and discussion

Fiber pretreatment

Table 2.1 summarizes the proximate analysis, the structural carbohydrates and lignin

results of raw and pretreated fibers. There is an evident increase of the fiber humidity after

pretreatment, reaching a maximum value of 11.24% at 60 minutes of pretreatment. This

kind of behaviour has been previously reported, suggesting that a higher content of water

in the fiber constitution facilitates the movility of chemical structures, improving structural

reorganization in the fiber and increasing crystalline cellulose [1].

High moisture content have been reported to be related to the formation of carboxylic

functional groups (-COOH), increasing fiber swelling via an osmotic effects and increasing

the affinity with water -OH groups, giving the fiber a hydrophilic character. Water retention

has been also reported to be an indicator of increased fibrillation of the treated fiber [12].

Fique fiber sonicated for 60 minutes, reported a wet basis moisture content of 7.43%,

showing a reduction with respect to the humidity of all pretreatments accordingly to the

functionalization made, chemical treatment reduces the number of –OH. The acid

insoluble residue (AIR) declined sharply, indicating that the longer the pretreatment the

smaller the presence of insoluble residue in the composition of the fiber [13]. Ashes weight

percentage decreases with the pretreatment time, presenting a small reduction after 30

minutes, but reducing in a dramatic way after 60 minutes, meaning that sonication may

have a major impact in the removal of inorganic substances that could be present in the


raw fique [14]. Peinado et al.[4], reports a value of ashes of 0.7% for fique fibers from the

Santander region (north east of Colombia), different to the value obained for the fique used

in this study (0.94%), such differences in raw fique are ussually relate to non comparable

agriculture procedures and conditions that varied from region to region [4]. Total solids

decreased with increasing time of sonication, mainly due to the change in the percentage

of moisture (Table 2.1).

Table 2.1. Fique fiber proximate analysis and structural carbohydrates and lignin (NREL)

analyses 11

Component Weight Percentage (%)

Raw M30 M60 M90

Humidity 2.10 7.92 11.24 10.34

Total solids 97.90 92.08 88.76 89.66

Acid insoluble residue (AIR) 23.02 14.31 13.48 8.41

Ashes 0.94 0.83 0.04 0.02

Lignin 22.58 13.92 13.94 8.91

Hemicellulose 28.15 33.49 27.21 30.46

Cellulose 36.33 45.08 41.42 44.56

Also there is a reduction in the content of lignin of the pretreated samples at any of the

pretreatment times: 8.66% for 30 minutes, 8.64% for 60 minutes and 13.67% for 90

minutes. Table 2.2 summarizes the contribution of insoluble and soluble lignin determined

using NREL methodology, being insoluble lignin (AIL) the most abundant type of lignin

found in the sample.

Several studies have reported that lignin constitutes between 10 to 25% of the cell wall in

most natural fibers [16], the value obtained for the samples studied in this work was

22.58%, a considerable larger value to the ones reported by Peinado et al.[4], and Chacón

et al. [1], of 11.3 and 14.5%, respectively (Santander region fique).

Table 2.2. Lignin content in fique fiber pretreated at different times 12

Component Weight Percentage (%)

Raw M30 M60 M90

Acid insoluble lignin (AIL) 22.08 13.47 13.44 8.39

Acid soluble lignin(AIS) 0.50 0.45 0.51 0.51

Total lignin 2.58 13.92 13.94 8.91


During the hydrolysis, polymeric carbohydrates are hydrolyzed into monomeric forms,

which are soluble in the hydrolysis liquid. They are then measured by HPLC, the

concentration of the polymeric sugars are calcuated from the concentration of the

corresponding monomeric sugars obtained by HPLC, using a correlation between C-5

sugars (xylose and arabinose) with the hemicellulose and a correlation between C-6

sugars (glucose) with cellulose [5].

In terms of hemicellulose there is not a clear tendency of the effect of the pretreatment.

Initially after 30 minutes of pretreatment, the hemicellulose weight percentage increases

from 28.15 to 33.49% then reduces to 27.21% after 60 minutes to finally increase to

30.46% after 90 minutes, this kind of behavior has been previously correlate to a

mechanism where after an initial disrruption of microfibrils they associate into clusters or

bundles denominate macrofibrils [15]. Raw fique fiber hemicellulose composition of

28.15% is within the 15 to 30 weight % range reported by other authors as Saha [18].

All the pretreatment times increased the weight percentage of cellulose in the fiber,

obtaining the highest value for 30 minutes of pretreatment (45.08%), confirming the

positive effect of sonication treatment on the fiber. This kind of behavior has been reported

to be caused by the destructive effect that sonication has on hemicellulose and lignin since

produce glycosidic bonds dissociation, promoting the formation of weaker oligosacharides

and reducing the molecular weight [19].

The main constituent of wall cells in plants is cellulose. Fique analyzed in this study has a

36.3% of cellulose in its composition, very different from the value reported by other

authors as Peinado et.al [4], and Chacón et al. [1], (73.8% and 63%, respectively). Some

authors have attributed this difference to the type of fertilizer used during cultivation, no

comparable defibration process, different species of fique plant and even environmental

conditions of each region [20].

Table 2.3 reports the increment in glucose content for the different sonication times, due to

the increase of cellulose exposition as final aim of this pretreatment. 30 and 90 minutes

pretreatment times showed a small increase in xylose, however at 60 minutes xylose

decreased; this type of behavior was also observed for hemicellulose, confirming the

directly proportional relationship between xylose and hemicellulose. The insignificant

change in arabinose and acetic acid values indicates that the sonication had a neglectable

effect on these compounds.


Table 2.3. Carbohydrates present in raw and pretreated fique fiber 13

Molecule mg/mL

Raw M30 M60 M90

Glucose 0.212 0.249 0.222 0.228

Xylose 0.073 0.084 0.070 0.079

Arabinose 0.058 0.058 0.058 0.058

During the sonication treatment, energy is transferred to the cellulose chains by cavitation,

gradually disintegrated hydrogen bonds. However, the complexity of the fique fibers

multilayer structure limits the impact of the pretreatment mainly to lignin [21] and

hemicellulose [22], thereby increasing the exposure of cellulose and the porosity of the

fiber due to the division of fibrils on the longitudinal axis [23] and creating around the

cellulose structure repulsion forces keeping microfibrils from aggregation [6].

Based on the results obtained during the pretreatment of raw fiber, the M60 pretreatment

was selected and samples exposed to this treatment are the ones used in the process of

functionalization .

Fiber functionalization

Surface characterization

Figure 2.2 shows the pH curve used to determinate the pHzpc of the raw and pretreated

fique fibers. The raw fiber (blue dots) presents an intercept with the zero value of the

abscisa at 5.32 indicating an acid behavior most probably due to the presence of different

ionizable

functional groups such as carboxylic, phenolic, alcoholics and hemiacetal groups [24],

contained in the macromolecules of hemicellulose, lignin and cellulose.


Figure 2.2. pHzpc for the fiber according to treatment 8

For the fiber pretreated by ultrasound (M60) (orange dots), the pHzpc decreased to 4.18,

indicating that pretreatment makes the fiber more acidic by the partial removal of lignin and

hemicellulose, exposing more acidic functional groups on the surface of the fiber, feature

which is characteristic of cellulose. This result is an indication of the positive effect of the

pretreatment on the fiber surface, depending on the method used in the synthesis of

nanoparticles these activated groups serve as nucleation sites for the formation of

nanoparticles. The functionalization process increased the pHzpc of the pretreated fiber to

8.23 (gray dots), indicating that the adsorption of cations on the surface of the pretreated

fiber was achieved satisfactorily, fulfilling the purpose of functionalizing the fiber,

increasing the number of positive charges on the fiber surface and creating the conditions

for an appropiated functionalization process.

In Figure 2.2 the raw, pretreated and functionalized fiber, at pH equal to 2 have a similar

behavior attributed to the presence of carboxyl groups content of cellulose and their

degree of dissociation. About 90% of the cellulose carboxyl groups are dissociated at pH

5, at higher pH values the degree of carboxyl groups dissociation is even higher, but the

dissociation degree as a function of pH does not follow the theoretical curve, particularly,

at pH = 2, cellulose fibers become neutral. Therefore, the cationic retention depends on

the pH [25].

The quantification of acidic and basic sites by the titration method Boehm [10] (Table 2.4)

fit very well with the results obtained in the zero point charge characterization. There is an

increase in the acid sites when the raw fiber is pretreated which has been reported to be

-6

-4

-2

0

2

4

6

8

0 1 2 3 4 5 6 7 8 9 10

∆pH

pHi

Raw

Pretreated

Functionalized


related to a greater presence of carboxylic, cyclic anhydrides, lactones, and phenolic

hydroxyl groups [26].

The surface sites were calculated in miliequivalents of titrant solution using equation (1).

Consequently, the difference between initial moles of HCl and moles of HCl consumed by

NaOH titration represents the amount of acidic sites on fique fiber and the difference

between initial moles of NaOH and moles of NaOH consumed by HCl titration represents

the amount of basic sites on fique fiber, as expressed in equation (1) [27]:

𝑆𝑖𝑡𝑒𝑠 = 𝑉𝑡𝑖𝑡𝑟𝑎𝑛𝑡𝐶𝑡𝑖𝑡𝑟𝑎𝑛𝑡 − 𝑉𝑎𝑛𝑎𝑙𝑦𝑡𝑒𝐶𝑎𝑛𝑎𝑙𝑦𝑡𝑒

𝑆𝑎𝑚𝑝𝑙𝑒 𝑤𝑒𝑖𝑔ℎ𝑡 Eq (1)

Where Ctritant, Vtritant and Canalyte, Vanalyte are the concentration and volume of the titrant and

analyte solution, the sample weight represents the dry weight of fique fiber before the

procedure (raw, pretreated or functionalized) subjected to the titration.

Table 2.4. Results of the acidic and basic sites in the fique fiber in different stages of analysis 14

Sites meq/g

Raw Pretreated Functionalized

Acids 0.700 ± 0.141 0.750 ± 0.035 0.100 ± 0.071

Basics 0.050 ± 0.000 0.075 ± 0.035 0.775 ± 0.035

The surface of functionalized fiber has an increase in the basic character, with an increase

in the number of basic sites and a minimum amount of acid sites.

Figure 2.3. FTIR - ATR spectrum of raw fique fiber, pretreated (M30, M60, M90) and

functionalized (MC1, MC2, MC3) between 4000 and 600 cm-19

650100013501700205024002750310034503800

Tra

ns

mit

tan

ce

(

u.a

)

Wavenumber (cm-1)

Raw M30 M60 M90 MC1 MC2 MC3


Figure 2.3 presents the FTIR – ATR spectrum of the raw, pretreated and funtionalized

fibers. The spectrums show a significant change in the region between 3600 and 3200 cm-

1 where the OH groups are identified; also there is a noticeable decrease in the intensity of

the signals in the region between 1800 and 1500 cm–1, which is usually regarded as an

indication of water loss in the fiber and the disappearance of C=O chemical bonds [28].

The differences observed in the spectra located in a region of 2920 to 2850 cm-1, are

related with the functional group CH2, present in the general chemical formula of

monosaccharides like glucose, in this way it is evident that with the application of

pretreatments as sonication and functionalization increases the number of exposed

glucose, since they are the monomers constituents of cellulose [4]. The reduction in the

intensity of the peaks located between 1780 and 1640 cm-1 correspond to samples that

were exposed to longer pretreatment times and are related to an increase in the number of

carbonyl functional groups (C = O) present as aldohexoses (cellulose) [13].

An important peak to observe is located at 898 cm-1 where evidences of the C-O-C groups

are obseved (related to glycosidic bond β-(1→4)), this groups are the ones that interact

with Na+ during functionalization, a reduction in this peak means that the funtional group is

establishing a strong interaction with the absorbed Na+ ion [3].

Futher evidences of the presence of Na+ species on the surface of the funtionalized fiber

was obtainde by EDS analysis. Figure 2.4 presents the EDS profiles of raw, pretreated

and functionalized fibers.

The EDS Spectroscopy for raw and pretreated fibers shows large carbon and oxygen

peaks as expected for an organic material and consistent with previous reports [4].

However, the spectrum corresponding to functionalized fique fiber, additionally to the large

carbon and oxygen peaks, also shows a strong signal for Na+, related to the ion exchange

process that took place when the tretaed fiber was exposed to the cationic agent (NaOH)

used in the functionalization process, indicading a suscessfull functionalization process.


Figure 2.4. EDS profile of raw, pretreated and functionalized fique fibers 10

The spectrum of Figure 2.4. Evidence of the presence of other elements such as calcium

(Ca) and magnesium (Mg) in the raw fiber, which according to Peinado et al.[4], in a

characterization previously reported values of 0.96% and 9.4 ppm, respectively. Due to

the effect that ultrasound had on the increase of cellulose exposure of some elements that

were internally of the fiber such as magnesium (Mg) and calcium (Ca) increasses the

intensity, other peaks of elements such as silicon (Si) appeared, which are reported by

Peinado et al.[4], like trace values.

Structural characterization

Figure 2.5. XRD of raw and pretreated fiber (30, 60 and 90 minutes of sonication) 11

0 0,5 1 1,5 2 2,5 3 3,5 4keV

Raw

Pretreated

Functionalized

0

500

1000

1500

2000

2500

10 13 16 19 22 25 28 31 34 37 40

Inte

nsity a

.u.

2 tetha

Raw

M30

M60

M90

Cl

C O

Na

Mg

Ca

Si

Cl


Figure 2.6. XRD of raw and functionalized fiber (1, 2 and 3 hours of functionalization) 12

Figures 2.5 and 2.6 present the XRD profiles for raw, pretreated and functionalized fibers.

These results are consistent with cellulose’s diffractograms reporting characteristic broad

peaks, the main one centered around 22.6°, which are due to the polycrystalline cellulose

character. Peak around 16° is associated with amorphous cellulose (Iam: minimum intensity

between the peaks of the planes 200 and 110); while the peak of 22.6° is associated with

crystalline cellulose (I200) [29].

The 4 crystalline allomorphs cellulose fique analyzed present the type I (natural and

thermodynamically metastable cellulose [37]); this allomorph is a mixture of two different

crystal lattices, which change depending on the source of cellulose, plants as fique

evidence monoclinic network (Iβ), which has the planes (200), (110) and (110) [30].

Both Figures 2.5 and 2.6 allow to calculate the crystallinity index (CI), which is a

quantification of the percentage of crystalline cellulose in the sample; the results are

summarized in Table 2.5. Crystallinity index (CI) was calculated using equation (2) as the

ratio of the peak heights of I2 0 0 and the minimum intensity of Iam:

𝐶𝑖(%) = (1 − 𝐼𝑎𝑚

𝐼200) × 100 𝐸𝑞 (2)

Table 2.5. Crystallinity index for raw, pretreated and functionalized fique fiber 15

IC (%)


MC M30 M60 M90 MC1 MC2 MC3

50.30 44.62 49.89 48.49 50.33 36.33 55.11

Table 2.5 shows that the pretreatment effect on cellulose crystalinity is small for any of the

pretreatment times of exposure (30, 60 and 90 minutes). Seems like 30 minutes treatment

0

500

1000

1500

2000

2500

10 13 16 19 22 25 28 31 34 37 40

Inte

nsity a

.u

2 tetha

M60

MC1

MC2

MC3


is the one that has the major effect, but the crystalinity reduction is only in the order of 6%.

In average, the change in crystallinity was only in the order of 2% for the 3 treatments,

impliying a sligthly decrease in the amount of amorphous cellulose, which coincides with

the results reported by other authors who performed similar pretreatment processes [1, 31,

32].

These result sugested that pretreatments produce no major changes in the cellulose

structure, keeping the cellulose steric hindrance to the attack of reagents [29]. However, in

Figure 2.6 for the two-hour functionalization time (MC2), a peak shifting at 22° was seen,

the interplanar distance of the samples M60, MC1, MC2 and MC3 were calculated using

Bragg’s Law, obtaining values of 3.96, 3.95, 3.93 and 3.94Å, respectively. Confirming that

the displacement is not related to possible tensions in the crystalline structure of the

cellulose.

On the other hand, funtionalization has a major impact on the crystallinity only after 3

hours. since M60 sample was used as starting material for the functionalization process

(49.89 of crystallinity index), it is evident that after 1 hour of functionalization there was not

effect on the crystallinity of the samples. After 2 hours there was an important reduction to

a CI= 36.33 and after 3 hours an increase to CI=55.11. Taking in account that the

functionalization process is essentially of chemical nature, exposing the fibers to chemicals

such as HCl and NaOH, the CI will be dependent of the reaction rates to which each

compound of the fiber interacts with the chemical species of the functionalization

chemicals. The crystalline cellulose exposed during the ultrasound treatment is rapidly

attack by the surrounded functionalization chemicals and therefore initially there is a

reduction on the CI. However upon the time, the chemicals also attack lignin and

hemicellulose reducing their amount, exposing more cellulose and improving the

crystallinity index [30]. Increasing the amount of crystalline celulose is benificial because

this makes the fiber more accesible and susceptible to be used in specific surface

chemical reactions [33-36].

As shown in Table 2.5, after 3 hours functionalization process produce the highest

percentage of crystallinity index, cause by the realignment of cellulose molecules, this kind

of result have also reported elsewhere [37, 38].


Average crystallite size in the cellulose was calculated from XRD data using Scherrer’s

equation [20, 34, 37] (equation (3) ). Based on the line broadening effect at the full width

half maximum (FWHM) of the (002) peak.

𝐷 = 𝑘𝜆

𝛽 𝐶𝑜𝑠 𝜃 𝐸𝑞 (3)

Where D is the average crystallite size, k is Scherrer constant, λ is wavelength of X-ray, β

is the FWHM and θ is diffraction angle. Results are in Table 2.6.

Table 2.6. Calculated average crystallite size for raw, pretreated and functionalized fique

fiber 16

Average crystal size

(nm)


MC M30 M60 M90 MC1 MC2 MC3

11.81 28.2 9.18 5.92 28.21 20.68 5.08

Previous reports have demonstrated for the same peak (002) crystal size in the cellulose

calculated by this method, are around 5 to 6, 140 and 5 to 6.2nm, respectively [20, 39, 40],

average crystallite size was 28.2, 9.18 and 5.92 nm for 30, 60 and 90 minutes

pretreatment, respectively (Table 2.6). The reduction in the crystal size seems to be

related to sonication time, accordingly to the fiber degradation mechanism. During the

pretreatment, the reduction in the amount of hemicellulose and ligning exposes the

cellulose to a stronger effect of sonication, affecting the cellulose structure and size [41],

it has been observed that as a function of sonication time the fiber could be more uniform

but at the same time the damage in the crystalline cellulose increase [30].

In the functionalization stage, the crystallite size of cellulose decrease to a final size of

5.08 nm, meanly because the chemical treatment remove amorphous material from the

fiber [30]. The size of nanoparticles supported on the fiber can be affected by the amount

of amorphous cellulose present in the fiber [30], Ciolacu and collaborators reported a

similar crystallite size, between 4 to 7 nm, for other natural cellulose material pretreated

under similar conditios [29].

Morphological and textural characterization

SEM micrographs show the surface of a raw fique fiber covered of scale like structures

tidily packed and rectangular in shape, each with an average length of 80 and 25 μm of

width (Figure 2.7a). The presence of clusters and aggregates as the observed in Figure


2.7b and 2.7c are usually associated with wastes from the sheet defibration process. Also

some sort of spherical capsules are observed (Figure 2.7d), each with an approximate size

of 1μm, which have been tipically attributed to the presence of Streptococcus bacteria [42].

Figure 2.7. SEM micrographs of the raw fiber, a) 250X, b) 500X, c) 2000X, d) 5000X 13

On the other hand, the micrographs of sonicated fibers show that the pretreatment has

minor impact on the fique structure (Figure 2.8a), but reduces the roughness of the scales

in comparison to the raw fiber (Figure 2.8b), confirming the positive effect of pretreatment.

This decrease in the roughness surface is associated with the removal of lignin and

hemicellulose. Similarly, it’s clear the elimination of aggregate particles and the presence

of bacteria, making the fique fiber pretreated surface much more homogeneous and clean

(Figure 2.8c and 2.8d).

a

a

b

b

c

c

d

d


Figure 2.8. SEM of the pretreated fiber M60, a) 100X, b) 500X, c) 1000X, d) 5000X 14

Figure 2.9. SEM of functionalized fiber MC30, a) 100X, b) 300X, c) 1000X, d) 5000X 15

The functionalized fique surface becomes more uniformn and further shows the total

elimination of agglomerated particles and the disappearance of scales (Figure 2.9), which

confirms that the amount of cellulose exposed increased as a result of the reduction in

lignin and hemicellulose after the process of surface functionalization, similar to that

reported previously by Chen et al,[15].

a

a

b

b

c

c

d

d

a

a

b

b

c

c

d

d


Table 2.7 present the results for the total surface area inraw, pretreated and functionalized

fibers, obtained using the BET method from N2 isotherms. The value of the surface area

for the raw fiber is low, as is common in this type of materials, however the treatment

seems to have an impact in the development of surface area, probably due the disrruption

created in the fiber during the proccess ( for samples M30, M60 and M90), being the M60

the treatment conditions that creates the highest surface area.

The effect of the functionalization process on the surface area is minimal. M60 sample was

used as starting material for the functionalization process (3.24 m2/g), it is evident that no

major changes in the surface area of the fiber was observed, indenpendly of the time of

exposure to the funtionalization process. In Annex 1, the isotherms obtained for the data

reported in Table 2.7 are found.

Table 2.7. BET surface area of raw, pretreated and functionalized fibers17

Thermal characterization

All the fiber analyzed by TGA presented an approximate 10% mass loss between 30 to

100°C mainly due to evaporation of moisture present in the fibers (Figure 2.10). After

100oC the raw and pretreated fibers (M30, M60 and M90) follow almost overlapping TGA

profiles presenting two major mass loss sections starting at aprox. 260oC (distinguishable

by an intermedia inflection around 310oC). This first section has an approximate 18%

weight loss related to hemicellulose degradation [41]. The second between 310 and 370°C

with an approximate 40% weight loss is generally attributed to cellulose pyrolysis [43] and

beyond 370°C almost all cellulose is expected to be pyrolyzed with some remainig material

frequently related to lignin. Since lignin decomposition have been reported to happen

slowly under a wide range of temperature (from 20 up to 900oC) [41].

Sample BET surface area (m2/g)

Raw 0.77

M30 1.76

M60 3.24

M90 2.48

MC1 3.08

MC2 3.16

MC3 3.18


The functionalized fibers (MC1, MC2 and MC3) also present matching TGA profiles having

the same initial water loss showed by the other fibers and also presented almost

overlapping TGA profiles between them. However, on the contrary to the behaviour

observed for the raw and pretreated samples, the functionalized samples show only one

major mass loss starting and ending at aprox. 248 and 348oC. Both, the presence of only

one major mass loss and the tempearture shiffting of this mass loss to lower temperature

indicates that the functionalization process also modify the structure and composition

distribution of the fiber (also observed in the other characterization techniques evaluated),

creating a condition in which the hemicelluose degradation process and the cellulose

pyrolisis convolute in just one undistinguishable process (at least at the evaluated

conditions) [43, 44].

Figure 2.10. TGA for raw, pretreated and functionalized fiber 16

Conclusions

The effect of ultrasound pretreatment and cationization of fique fiber was studied.

Beneficial effects on the physicochemical properties of the fiber were found for 60 min of

ultrasound pretreatment, increasing cellulose content from 36.33 to 41.42%, while the

content of lignin and hemicellulose was reduced from 22.58 to 13.94% and 28.15 to

22.21%.

0

10

20

30

40

50

60

70

80

90

100

30 80 130 180 230 280 330 380 430 480 530 580

% W

eig

ht

T (°C)

Raw

M30

M60

M90

MC1

MC2

MC3


XRD confirms that after pretreatment and functionalization there are important amount of

crystalline cellulose exposed, after 3 hours of functionalization the CI increased. It was

corroborated by EDS and FT-IR analysis, that the functionalization proccess also

incorporated Na+ species on the fiber surface, specially the largest impact of the

functionalization process was reached after 3 hours of treatment, sugesting the formation

of a coordination bond between Na+ ions and the fiber surface carboxylic groups.

SEM pictures showed that both pretreatment and functionalization processes have effect

of the surface morphology of the fiber, producing smoother surfaces than the original raw

fiber. In terms of the textural properties, the pretreatment has a beneficial impact,

increasing the BET surface area. On the contrary, the functionalization process has not

impact on the BET area of the fibers. Thermal characterization shows the typical behaviour

of lignocellulosic material.

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3. Impregnation of iron compounds on natural and modified fique fiber 79

Chapter 3. Impregnation of iron compounds

on natural and modified fique fiber

Abstract:

A detailed study of the materials synthesized by the impregnation of iron compounds on

the surface of natural and modified fique fiber prepared in previous works was performed.

Wet impregnation in a contact time range of 1 to 5 days was evaluated in order to assess

the amount of iron compounds deposited as a function of time. The amount of adsorbed

species was determined by atomic absorption spectroscopy (AAS) and X-ray spectroscopy

(XRF). X-ray diffraction (XRD) and Fourier Transformed Infrared spectroscopy (FTIR) were

used to determine crystallography, crystallite size and chemical interaction of the iron

supported species on the fiber surface. Morphological and textural effects of the

impregnation in the fiber were determined via SEM and N2 isotherms. Other properties

such as pHzpc, acidic and basic sites and mechanical performance were determined. The

obtained results allow to conclude that the chemical functionalization of the fiber plays an

important role on the impregnation process, generating high loading density and highly

dispersed superficial nanoparticles. XRD and XRF, were used to detect the identity and

quantity of elements and compounds that are present in the sample, in this way providing

evidence of Fe2O3 (hematite) and α-Fe0 formation, also revealing that under the

impregnating conditions there is not complete evolution of the crystalline structures. No

major changes in pHzpc values of the functionalized fiber were observed, neither on the

BET surface areas calculated from N2 isotherms. SEM pictures of the impregnated

functionalized fiber revealed areas with substantial aggregation of nanoparticle and areas

where they are finely dispersed. Mechanical characterization shows that the impregnated

fibers have lower values in the tensile strength and effort to fracture, but higher values for

the Young's modulus.

Keywords: Furcraea andina, iron nanoparticles, impregnation, reduction, catalyst.


Introduction

Environmental contamination and particularly water pollution is one of the most important

global problems as a result of population increase, industrial development and limited

resource availability. This context demands solutions involving sustainable criteria, based

on the development of processes capable of combining technical efficiency, cost and

environmental effect reduction. Leading technologies to address this issues are based on

catalytic processes, particularly in the case of water treatment [1].

Currently the most widely used treatments are the combination of physical, chemical

and/or biological processes that manage to eliminate or substantially reduce water

pollution [2]. Industrial effluents have sometimes certain compounds that make it

particularly difficult to remove by conventional treatments, for example azo dyes and heavy

metals.

Biological processes are sensitive to toxic and recalcitrant compounds, while other

process as adsorption have high costs associated with the management of toxic waste. As

an alternative, catalytic processes provide effective treatment alternatives to complex

polluted effluents. Their decontamination mechanism are based on the catalytic

oxidation/reduction of organic matter employing iron, titanium, copper, manganese or

chromium catalysts [3-6].

Current efforts are center into developing new catalysts to make better use of raw

materials, reducing at the same time the amount of subproducts. Authors such as Corma

et al.[7], Ramirez et al.[8], and Chacon et al. [5], have developed catalysts based on

bogsita (zeolite), saponite (clay) and a biocomposite (nanostructured MnO2 and fique

fibers), respectively, catalysts with applications in wastewater remediation.

Additionally, nanotechnology has provided novel and efficient solutions to environmental

problems, specifically iron nanoparticles have demonstrated exceptional adsorption and

catalytic properties, due to fact that iron species are easily oxidized by organometallic

pollutants, amines and phenols [9].

In previous works, a cellulose matrix obtained from fique fiber was physical and chemically

modified as a means to provide enhanced characteristics as a catalytic support; in order to

take advantage of these enhanced properties a suitable procedure of loading the catalytic

active phase (iron compounds, in this particular case) must be developed. Supported


catalysts can be synthesized by different techniques depending on the characteristics of

the support material and the active phase to be supported. Procedures such as

precipitation and co-precipitation, are very useful in cases in which the active phase is

formed by precipitation from a precursor salt in solution. Co-precipitation is used in those

cases in which the active phase of the catalyst is composed of more than one component,

so that simultaneous precipitation occurs [10].

Impregnation is a technique used to produce supported catalysts that involves the intimate

contact of the solid support with a liquid containing the active elements (impregnating

solution) of the future catalyst; the amount of impregnating solution used may be slightly in

excess to the amount necessary to cover the support and is denominate wet impregnation

[11, 12]. Wet impregnation has greater application in cases in which chemical interaction

between the support and the impregnating solution are expected [10]. Impregnation is not

an exclusive mechanism, ie, other parallel processes can occur such as competitive

adsorption or selective deposition and ion exchange, among others [12]. Both chemical

adsorption and ion exchange, are mechanisms that involve chemical interaction at the

surface level of the active phase and the support, generally by covalent type functional

groups [13]. In particular, the anionic exchange allows to controllably impregnate a metal

from an aqueous solution on a catalyst support functionalized surface. Catalysts prepared

by impregnation are characterized by high activity, homogeneous shape, size and

dispersion, due to depending the precursor/reducing agent relation.

Materials and methods:

Catalyst Preparation

Raw, pretreated (M60) and functionalized (MC3) fique fiber were used as support for the

aqueous impregnation of iron species. A solution of Iron chloride (Merck, Darmstadt,

Germany) and deionized water (0.45 μS/cm, Milli-Q®), were used to prepare the

impregnation solutions. In situ synthesis was performed using FeCl3 as precursor, being a

precursor that doesn’t require heat treatment in the process of synthesis, then it doesn’t

affect the physicochemical properties of the support. Likewise, it is an economic precursor

and extremely soluble in water, allowing the Fe+3 ions to interact with the electrostatic

character of the support, increasing the number of anchored species [17].


The support was submerged in 50mL of a FeCl3 58mM solution varying the impregnation

time for 1, 2, 3, 4 and 5 days. Samples of the impregnated material were taken at the end

of each day, removed from the impregnating solution and washed three times with

deionized water to remove loosely bound particles and leftover species from the

functionalization and impregnation process[14]. Then, the wet impregnated fibers were

immersed in a 1M NaBH4 solution (Merck Millipore®) during 10 minutes to provide

reductive conditions, keeping the molar ratio 2:1 (BH4ˉ / Fe+3) [15]. According to the

following reaction:

2𝐹𝑒𝐶𝑙3 + 6𝑁𝑎𝐵𝐻4 + 18𝐻2𝑂 → 2𝐹𝑒0 + 6𝑁𝑎𝐶𝑙 + 6𝐵(𝑂𝐻)3 + 21𝐻2 Eq (1)

Then the reduced fibers were rinsed with abundant deionized water. Finally, the catalyst

was dried at room temperature overnight [16]. It is important to highlight that even up to

the fourth day of impregnation there was enough impregnating solution to cover the whole

support material.

The mechanism of formation in solutions by reducing Fe+3 ions is performed in two stages:

nucleation and growth. Nucleation represents the first stage during a crystallization

process, it can be defined as the process by which building blocks (metallic atoms in the

synthesis of metal nanomaterials) arrange themselves according to their crystalline

structure to form a site upon which additional building blocks can deposit over and

undergo subsequent growth. Properties of nanoparticles as size and shape are function of

the reaction rate, which at the same time is controlled by parameters such as

concentration, temperature, pHzpc, pH, reductive power, solubility and nature of metal ion

[18,20]. A general mechanism of iron nanoparticle formation is shown in Figure 3.1 [19].

Figure 3.1. Mechanism of formation of iron nanoparticles [19] 17


Characterization

The iron content of the catalysts after impregnation was determine by means of flame

atomic absorption spectrometry (FAAS) using the injection method. Before the performing

the atomic absorption the samples underwent a digestion procedure following the EPA

Method 3050B: Acid Digestion of Sediments, Sludge, and Soil [21]. Then, the material

obtained from the digestion procedure was analyzed in a Hitachi z-8000 atomic absorption

spectrometer equipped with an atomizer with air/acetylene burner used for the

determination of elemental iron. The wavelength used for the determination of the analyte

was: Fe 248.3nm. The content of iron and other element was also followed by X-ray

fluorescence spectroscopy (XRF), on pressed 36 mm in diameter tablets molded on a

hydraulic press at 120 kN per minute, using a MagixPro PW – 2440 Philips spectrometer

equipped with a tube Rhodium and maximum power of 4kW. The semiquantitative analysis

was performed with the IQ software, after 11 sweeps of X-ray fluorescence.

pH of zero point charge (pHzpc) was estimated using the pH drift method [22]. For this

purpose, 50 mL solutions of KNO3 (1% vol.) were adjusted to initial pH values between 2

and 10 with solutions of NaOH 0.1M or HCl 0.1M. Then, 0.1g of catalyst was added into

this solution, after 24 hours the final pH of the solution was determinate. Acid and basic

sites of the fibers were determined using Boehm titration method [23], the titrants solutions

were 0.1 M NaOH or HCl according to the case, the data were reported as meq of titration

solution/g.

An XPERT-PRO MPD diffractometer with monochromator of graphite crystal was used to

characterize the crystalline structure of the materials. Cu Kα radiation at wavelength of

1.54Å were used as X-rays source and were recorded over 2 theta range of 5º– 85º.

Experimental data was analyzed using PANalytical X'Pert HighScore Plus database.

Crystalline size of identified structures was calculated using Scherrer equation.

Morphological characterization was performed using a Zeiss Neon 40 Scanning

Electronmicroscope (SEM) operating between 2 to 20kV, functioning at an average 5 mm

working distance, on previously thin film Pt coated samples (1 to 3nm thick). Total surface

area was measured by the adsorption of nitrogen (N2) at 77K, using a Quantachrome

NOVA e-Series surface area analyzer. N2 isotherms were performed on samples degased

at 80oC for 8 hr; the calculation of the total superficial area was done using the BET

method [23].


Infrared spectra of the catalyst were collected on a FT-IR spectrometer (Nicolete iS 10

(Thermo Fisher Scientific)) in the range of 400 to 4000cm-1 with a resolution of 4cm-1,

using a diamond crystal ATR (PIKE) accessory.

DLS experiments were done in a Malvern Zetasizer Nano Range equipment using 1000μL

of the lixiviated solution of nanoparticles; measurements were taken by triplicate at 25°C,

54.2kcps count rate and for 50s of scanning time.

The mechanical performance of the materials was determinate using a tensile testing

machine (Shimadzu AG-IS) with a 50N cell load. Experiments were performed with a cross

head speed of 3mm/min at room temperature (18°C) and a relative humidity of 54.6%. The

results were averaged over six measurements, the statistical analysis of the data each

sample excludes outliers, employing software Matlab®.


Impregnation process

The initial observation surveyed during the impregnation process, regardless of effect of

the impregnation time, was a dramatic change of the fiber color from yellow (Figure 3.2a)

to coppery brown (Figure 3.2b), this change in coloration have been frequently related to

the chemical state and particle size of the impregnated particles. In the particular case of

nanoparticles, some authors have shown that nanoparticles in solution [20,21,24] and

anchored to supports such as cotton fibers and cellulose [5,14] show color variations due

to changes in the properties of the surface plasmon resonance of the material [22,23].

Figure 3.2. Color change on impregnated fibers. a) Before impregnation (functionalized

stage) b) After impregnation 18

a

a

b

b


Although the change of the fiber color was a primary indication of the effect of the

impregnation process on the surface, it was necessary to corroborate the amount and

chemical condition of the impregnated species on the fiber surface. Consequently the

amount of Fe species supported after impregnation on the raw, pretreated and

functionalized fique fiber was measured using FAAS following the procedure describe in

the experimental section and the results are presented in Figure 3.3.

Independently of the initial stage of the fiber before the impregnation (raw, pretreated or

functionalized) the three materials presented a fast increase in the amount of Fe supported

in the first day of impregnation, after the first day, all the materials presented a tendency of

stabilization of the amount of iron species supported.

Although, this behavior is shared for the three materials, there is an important difference

between the net amount of Fe species supported, meanwhile the raw and pretreated

sample at the end of the first day have a Fe species loading of 5.5wt %, the functionalized

fiber reached a value in the order of 10.9% after 1 day of impregnation, implying that the

functionalization treatment has an beneficial effect on the impregnation of Fe species on

the fiber surface. After 5 days of impregnation the final Fe species loading values obtained

were 6.6, 11.7 and 14.9wt% for the raw, pretreated and functionalized fibers, respectively.

Figure 3.3. Amount of Fe species impregnated on raw, pretreated and functionalized fiber

as a function of impregnation days 19

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

0 1 2 3 4 5

Fe

im

pre

gn

ate

d (

wt.

%)

Impregnation (Days)

Raw Preteated Catalyst


The results observed in Figure 3.3 determined by FAAS, highlighted the importance of the

functionalization process and the proper chemical configuration of the fiber surface to

interact with the ions contained in the impregnation solution; the initial raw fiber is

schematically presented in Figure 3.4a, once the fiber is cationized during the

functionalization process, positive charged Na+ species populate the fiber surface (Figure

3.4b), these Na+ ions interact with Fe species in the precursor solution leading to the

deposition of Fe+3 ions on the fiber surface via ion exchange, generating NaCl in solution;

a final reduction step with NaBH4 (reducing agent) is implemented with the aim of

maintaining the reduced state of the Fe species at least during the deposition of the Fe on

the fiber surface, although this reduction step does ensure the final oxidation state of the

impregnated species due to the fact that this final reduction state of the iron aggregates

particles is also depending of their interaction with the surface, environmental conditions,

among others [29].

Figure 3.4. Chemical synthesis of nanoparticles by the impregnation method (Adapted from [5]) 20

XRF was also used to verify the amount of iron species impregnated on raw and

functionalized fiber after the first day of impregnation, expresses as oxide. The results

presented in Table 3.1, confirms an important increment in the Fe related compounds (due

to the impregnation); some Na and Cl related compounds are also present, which are

leftover from the acid digestion (HCl) and the subsequent cationization (NaOH) stages of

the functionalization process. Other compounds of Si, S and Al are present in the natural

fiber and had small changes in the composition of the fiber before and after impregnation.

The functionalization of fique fiber has an appreciable effect on iron deposition as a result

of chemical bond formation between the iron nanoparticles and the sodic active groups


attached to the surface during the functionalization. In the case of the raw and pretreated

fiber, impregnated iron is lightly attached to the fiber surface as a consequence of weak

interactions (mainly Van der Waals type forces). However, comparing the amount of final

iron presented in the pretreated and raw fiber, is it clear that the ultrasound pretreatment

also have some and effect on the capability of the fiber to support iron, predominantly due

to the cellulose exposing effect that the ultrasound treatment has on the fibers, which is

also reflected in the increase of surface area observed in the fiber after the treatment;

besides the observed increment in the surface area this type of ultrasound pretreatment

has been also reported to increase the number of hydroxyl groups available for further

functionalization or chemical interaction to absorbing species [30].

Table 3.1. XRF analysis of raw fique fiber and catalyst with 1 day of impregnation 18

Element and/or

compound

Raw fiber

(wt%)

1 day of

impregnation (wt%)

Fe2O3 0.097 7.033

Na2O 0.022 2.919

Cl 0.027 0.279

SiO2 0.100 0.133

Al2O3 0.012 0.031

On the other hand, on the surface of the functionalized fiber the process of deposition is

mainly driven by an electrostatic environment created by the –CH2O-Na+ groups formed on

the surface during the functionalization process, the interaction of this group via ion

exchanges creates a strong anchoring effect on the impregnated nanoparticles and the

surface fiber through chemical bonds, the attractive forces of this mechanisms have been

described to be normal to the surface of the support [16,31]. This chemisorption process

creates real irreversible chemical bonds that do not occur homogeneously throughout the

support, but only in some active sites [32]. Also, chemical interactions take advantage of

oxygenated groups (such as hydroxyl and ether) typical of cellulosic surfaces, allowing the

anchoring of ferric ion to the cellulose fibers by ion-dipole interactions that stabilized the

nanoparticles, producing high dispersion of the active phase and assisting the formation of

iron nanoparticles on the surface of the support. It would be foreseeable that on the initial

days there is concurrent contribution of the chemical driven and of the physical driven

impregnation mechanisms, however as the amount of surface chemical active site

available is limited, it is expected that is contribution will decay upon time.


During the second day of impregnation on the functionalized fiber there was an increment

in the percentage of iron impregnated, this increment could be the result of the interaction

of the remaining available –CH2O-Na+ groups on the surface that did not readily interacted

with the Fe+3 in the impregnating solution. The physisorption mechanism has a contribution

on the amount of Fe+3 impregnated on the fiber or even on top of already impregnated

Fe+3, leading to the formation of "clusters" or new larger aggregations on the fiber surface

[5,33].

After the second day, it seems that the impregnation process is reaching an equilibrium

stage and on the subsequent days the amount of deposited iron did not significantly

change. As the available chemical active sites of functionalized fiber being covered by

impregnated species decrease as function of time meanwhile the physical impregnation

could be still happening in the available uncovered surface area or even on top of already

impregnated species (creating bigger particles or aggregates), it is expected that most of

the particles adsorbed during the final days are only physisorbed and therefore weakly

absorbed when compared to the chemisorbed ones [16]. A secondary effect of the

aggregation of particles is the reduction of the effective surface area of the particles

available for reaction [15] and generating saturation of Fe+3 ions in the active sites on the

surface of fique that can leach later on.

Few literature is available on the deposition of iron compounds on fique fiber, however

comparable procedures of the impregnation of MnCl2 solutions have been reported by

Chacón et al. [5], they reported a final amount of manganese impregnated compounds in

the order of 1 and 1.84wt %, lower than the final amount obtained for the present study.


Figure 3.5. XRD diffractogram profiles of functionalized fiber after 1, 2 and 3 days of impregnation.21

In order to establish the reduction/oxidation state of the formed particles after

impregnation, XRD profiles of selected samples were obtained. Figure 3.5 shows the

evolution on the crystallization and chemical species of the impregnated material during

the three initial days of impregnation for the functionalized fiber, there are not significant

differences in the profile observed, all of them clearly show cellulosic related peaks

(located at 2theta of 16 and 22o), a small broad peak centered around 34° related to the

Fe2O3 structure (specifically corresponding to hematite) and a tiny peak around 81.2o

which coincides with the secondary (211) plane of α-Fe0, however the main (100) peak of

the α-Fe0 structures is not observed at 44.67o [34]. The size and the shape of the iron

related peaks on the XRD profiles does not have major changes from day 1 to day 3,

supporting the observation that the main impregnation process probably happens in the

initial days of impregnation. An additional information that can be extracted from the XRD

profile is the crystal size using the Scherrer equation, due to the presence of broad peak

(characteristic of nanoparticles); the average size calculate for the Fe2O3 34° peak was

28.2nm.

The fact that only the main peak of hematite (lacking some secondary peaks) and that only

a secondary peak for the α-Fe0 are observed indicates that under the impregnating

conditions there is not a complete evolution of the crystalline structures. It is well

established that a complete crystallization of the γ -Fe2O3 (maghemite) and the α-Fe2O3

(hematite) phases occurs at temperatures around 300 and 350°C, respectively. The

5 8 11 14 17 20 23 26 29 32 35 38 41 44 47 50 53 56 59 62 65 68 71 74 77 80 83

Inte

nsity a

.u.

2 tetha

Day 1

Day 2

Day 3


transition from the maghemite to the hematite occurs at 500°C [33-35]. In the context of

this study a post treatment of the impregnated fibers was not considerate due to the low

temperatures in which the natural fiber materials start to degrade.

Some studies [34-36] have reported that supported amorphous iron oxides nanoparticles

could be stabilize due to interaction with the matrix in which are supported, in concordance

with the lack of proper crystallinity development observed in the in this study. The lack of

crystallinity in iron nanoparticles (α-Fe2O3 or γ-Fe2O3) structures have been also explained

by fact that at such small dimensions, space restrictions entail to the absence of a periodic

network could arise [35].

The results obtained by XRD, atomic absorption and XRF confirms the presence of iron on

the support´s surface and the effects of the impregnation time spam in the amount and

chemical state of the particles impregnated. Although, the values of the percentages

obtained by atomic absorption and XRF are not one to one quantitatively comparable due

to intrinsic characteristics of the techniques (XRF is a semiquantitative technique of

characterization doesn’t include the analysis of Al lighter elements), the techniques are

complementary and give a more complete picture of the phenomena.

Further evidence on the chemical interaction of the impregnated Fe species and the

functional groups on the surface of the functionalized fiber was obtained by FT-IR; Figure

3.6 shows the FT-IR spectra of the impregnated functionalized fiber for the 1, 2 and 3 days

of impregnation; these have the characteristic strong absorption bands between 450 to

600cm-1 related to the presence of iron oxide related compounds [35]. Specifically for γ-

Fe2O3 (maghemite) two peaks around 463 and 1630cm-1 were identified, the first one may

correspond to Fe-O bending vibration mode. A broad peak at 162cm-1 and two peaks in

463 and 546cm-1 were observed, which are the characteristic absorption bands of α-Fe2O3

(hematite) [36], it is important to note that the peak at 463cm-1 doesn’t allow to distinguish

between maghemite and hematite phases. Likewise, two stretching vibrations at 420 and

618cm-1 were observed, these are characteristic of Fe-O interactions bringing evidences of

the existence of zero valent iron supported species, providing additional support to the Fe0

diffraction peak observed in the XRD profiles [37].


Figure 3.6. FTIR spectrum of functionalized fiber after three different days of impregnation

(1, 2 and 3 days) and without impregnation 22

The vibration located at 898cm-1 is related to the insertion of Na+ ions on the carboxylic

groups of the fiber surface and are still observed on the functionalized fiber [33]. Also

evidences of the presence of oxyhydroxide [FeO (OH)] can be observed at 1100 cm −1 [35].

Due the important role the ion exchange process has in the mechanisms of Fe species

impregnation on the surface of the fiber and its possible effect in the modification of the

charge distribution on the fiber surface, pHzpc values were also determinate for the

impregnated material on the functionalized fiber, these results are reported in Table 3.2.

No major change in the pHzpc values were observed during the three days of

impregnation, maintaining values between 8.56 to 8.83 (average 8.71 ± 0.08), suggesting

a slightly basic character when compared to the original pHzpc value of the functionalized

fiber before exposed to the impregnation solution (pHzpc = 8.23 ± 0.08). This slight

change is related to specific properties that the iron oxide nanoparticles formed during the

impregnation process have been reported to display, regarding to their ability to change

valence to form complexes with many organic and inorganic compounds and to have an

amphoteric character when interacting to H+ and OH- ions species, as the ones present in

the precursor solution [33]. The presence of iron oxide (Fe2O3) in the forms of γ-Fe2O3

(maghemite) and α-Fe2O3 (hematite) on the surface of the impregnated functionalized fiber

explains the predominant alkaline surface. Also contributing to this alkalinity are [FeO(OH)]

groups, some reactive hydroxyls groups on the cellulose and possibly some remaining

Na+ ions.

40060080010001200140016001800200022002400260028003000320034003600

Tra

nsm

itta

nce

% (

u.a

)

Wavenumber (cm-1)

Day 1 Day 2 Day 3 Functionalizated MC3


Table 3.2. Acidic and basic sites determined by titration Boehm and pHzpc for the impregnated functionalized fiber 19

Impregnation

days

Acidic sites

(meq/g)

Basic sites

(meq/g)

pHzpc

1 0.100 ± 0.035 0.763 ± 0.053 8.73 ± 0.06

2 0.375 ± 0.071 0.825 ± 0.035 8.84 ± 0.16

3 0.200 ± 0.035 0.750 ± 0.071 8.56 ± 0.02

pHzpc values also may help to explain the differences in the amount of Fe impregnated

observed for the raw and pretreated fibers when compared with the functionalized fiber; as

the adsorption mechanism involved in the impregnation of the raw and pretreated sample

is essentially due to physisorption, the acidic condition of the impregnating solution (pH =

1.96 ± 0.14) affect the charge distribution on the raw and pretreated fiber surfaces (pHzpc

of 5.39 and 4.18, respectively), creating the conditions to have fiber surfaces positive

charged, hindering the ability of the impregnating Fe+3 cations to interact with the surface

[38].

Table 3.3. BET surface area of functionalized fiber after impregnation 20

Surface area of the impregnated functionalized fiber was obtained from N2 isotherms data

and calculated using the BET equation, the result are reported in Table 3.3. It could be

concluded that for the functionalized fiber the impregnation process has little or none effect

on the surface area. The BET area of the functionalized fiber before the impregnation

process was 3.18 m2/g and after the impregnation oscillates between 3.08 to 3.21m2/g.

Significant changes, particularly reduction, on surface area supported materials due to

impregnation process is usually the effect of pore mouths blockage by impregnated

particles, obstructing the diffusion and further adsorption of N2 molecules during the

isotherm determination (and effectively, any other molecule that tries to diffuse into the

pore); the effect of pore blockage is neglectable on low surface area materials, as the

functionalized fiber. In Annex 2, the isotherms obtained for the discussed samples are

reported in Table 3.3.

Impregnation days BET surface area (m2/g)

1 3.12

2 3.08

3 3.21


Figure 3.7. Morphological analysis of the functionalized fiber surface after 1 day of impregnation a) SEM 5000X, b) SEM 5000X, c) backscattering 30000X,

d) backscattering 30000X 23

Morphological characterization of the impregnated material can be observed in the SEM

pictures shown in Figure 3.7. Figure 3.7a and 3.7b correspond to low magnification SEM

pictures of the functionalized fiber surface after 1 day of impregnation, this pictures seems

to indicate that the fiber surface is unevenly covered by impregnated nanoparticles, some

areas look denser populated by micron size cluster of nanoparticles meanwhile others

seems to look uncovered (Figure 3.7a and 3.7b); however, at higher magnification (Figure

3.7c) it is possible to observed that the surface is covered by two types of nanoparticles,

some of them are clearly conforming large aggregates of clustered nanoparticles (red line

enclosed area) and some others are finely dispersed nanoparticles (blue line enclosed

area). Backscattering analysis was performed on the surface of the fiber corresponding to

the Figure 3.7c and the results are presented in Figure 3.7d, confirming that both the

aggregates and the fine particles are iron compounds, this backscattering analysis allows

to do an estimation of particle size of the nanoparticles, some of them are in the range of

100 to 200nm, especially the ones conforming the aggregates, on the contrary the one that

seem to be finely dispersed have particle size below 100nm, some of them even below

50nm.


Figure 3.8. SEM pictures of the functionalized fiber surface after 2 days of impregnation

a) 3000X, b) 10000X, c) 35000X, d) 70000X 24 25

Figure 3.8 shows the SEM pictures of the functionalized fiber surface after 2 days of

impregnation. Figures 3.8a and 3.8b correspond to low magnification SEM pictures where

the fiber surface seems to be more densely covered, which may be a reflection of the

higher Fe wt% determinate by atomic absorption for the second day of impregnation when

compare to the value obtained for the first day. Figure 8b also shows some aggregation of

particles that are loosely attached to the surface, almost peeling off from it. Figures 3.8c

and 3.8d are high magnification pictures of the aggregates that confirms that those

aggregates are clusters made out of smaller particles, most of them in the order of 100nm

or smaller.

The aggregates loosely attached to the surface would be the result of the particles

impregnated mainly by physical forces and will be prone to uncouple from the surface. In

order to evaluate the capability of the particles to stay attached to the surface a lixiviation

experiment was performed simulating the reaction conditions in which the catalyst would

be evaluate, the resulting lixiviated solution was analyzed by atomic absorption and


dynamic light scattering (DLS) in order to establish the amount and size of the lixiviated

particles.

Figure 3.9. Size distribution leached of iron nanoparticles (1day of impregnation) in aqueous solution (Malvern Zetasizer Software)26

Figure 3.9 shows the particle size distribution for the three runs, all of them presented a

broad normal distributed peak ranging from around 50 up to around 500nm, with a

polydispersion index (PDI) 0.408 and an average particle size of 147nm. Some of the

particles size distribution plots showed an extra small peak at higher particle size (around

8 microns), probably coming from the big loosely aggregates observed on Figure 3.7b.

Atomic absorption results indicates that only 5.38% of the impregnated Fe lixiviated from

the fiber surface, meaning that the impregnated particles are strongly attached to fiber

surface.

Mechanical characterization

Maximum force and maximum displacement were measured, while maximum stress and

maximum strain were determine for the raw fiber, pretreated and functionalized fibers (1, 2

and 3 days of impregnation). A summary of the obtained data is presented in Table 3.4,

where the fique density value (0.72g /cm3) used for calculations of cross sectional area

was taken from Amoy et al. [39].


Table 3.4. Summary of mechanical characterization for raw and impregnated fiber (1, 2 and 3 days) 21

Sample Cross

sectional area (mm2)

Maximum force (N)

Stress strain (MPa)

Young’s Modulus (MPa)

Strain to failure (%)

Raw 0.036±0.015 7.586 ± 3.828 177.18±73.01 3267.40 ± 838.86 8.57 ± 3.20

Day 1 0.052± .024 3.761 ± 1.240 90.76 ± 49.07 924.61 ± 446.08 10.97± 2.99

Day 2 0.054± .016 4.192 ± 0.984 77.86 ± 10.79 2775.00 ± 463.09 5.27 ± 2.07

Day 3 0.083± .057 5.237 ± 1.870 71.40 ± 29.09 4518.9 ± 1322.67 6.25 ± 2.99

Based on the maximum force (F max) and cross sectional area (N) was determined for

each fiber using the equation (2):

𝜎 (𝑀𝑃𝑎) =𝐹 𝑚𝑎𝑥 (𝑁)

𝐴 (𝑚𝑚2) 𝐸𝑞 (2)

Test Shapiro-Wilk was applied, confirming the normality of the data, in terms of variance

homogeneity data series was found that the data series is homoscedastic through Levene

test. Statistically through an analysis of ANOVA there is no evidence that the more days

soaking decrease the stress - strain of the impregnated samples with iron nanoparticles,

but evidence was found that all catalysts generally have less stress – strain in relation with

the raw fiber (see Table 3.4); strain was calculated from the equation (3).

𝜀 =∆𝑙 (𝑚𝑚)

𝐿𝑜 (𝑚𝑚) (3)

Using the stress-strain slope in the initial elastic regimen (between 10% to 30% shown in

Figure 3.10), the elastic modulus (E) was calculated for each tensile tested fique fiber.

Concerning the influence of surface treatments on the stress properties of natural fibers,

was possible to appreciate a reduction in the maximum strength and the deformation

capacity of the catalysts regarding raw fiber (Figure 3.10), while the elastic modulus

increased.

This mechanical behavior catalysts, not only is attributed to the presence of nanoparticles

but also the chemical and physical treatments explained in Chapter 2, which generate an

apparent stiffening of the fiber, as a result of changes in the bionanocomposite structural

chemistry (percentage of lignin, hemicellulose and cellulose) [40].


Figure 3.10. Curves stress vs strain of a) raw fiber b) catalyst with 1 day of impregnation c) catalyst with 2 day of impregnation d) catalyst with 3 day of impregnation 27

The crystal lattice of the matrix in this case cellulose, strongly influences the overall

mechanical properties affecting the reduction in the stress strain as a consequence to the

cationization stage in the surface functionalization. Altering the orientation of the cellulose

chains which in turn defines the structure of the crystals and the crystallinity percent,

resulting in a change in the crystalline structure of cellulose I type II to type [41]. In

addition, the effect of bonding strength of each iron nanoparticles also influences the

reduction in this property.

As for the reduction in the percentage of strain to failure (deformation) is associated with

the presence of defects in the fiber, caused by low interfacial properties between iron

nanoparticles or nanoparticle-support, own properties of the support and nanoparticles,

morphology, size and low crystallinity of the nanoparticles. Increasing the likelihood of

finding these irregularities in the filaments, and thus the generation of inferior mechanical

properties [42].

In the other hand, the increased elastic modulus may be related to intra and intermolecular

bonds of H2, generated because crystal size bulk aligned in parallel along the axis of the

fibrils. Causing the number of fibrils of cellulose significantly influences the properties of


the resulting compounds, in other words, amongst finer the structure as nanocellulose is

Young's modulus and greater stiffness [40].

It is important to clarify that the standard deviations obtained for maximum strength, the

elastic modulus and percent strain at maximum load, are allocated to the area of the cross

section and geometry varies along fique filaments, conditioning the mechanical dispersion

of the material results. This heterogeneity of natural fibers constitutes one of the

drawbacks when employed as reinforcement in composite materials [42].

Conclusions

A study of the materials synthesized by the impregnation of iron from aqueous solutions on

the surface of natural and modified fique fiber was performed. Initially it was observed that

the impregnation process is influenced by the condition of the fique fiber; raw, pretreated

and functionalized fiber presented a fast increase in the amount of Fe supported in the first

day of impregnation followed by a stabilization tendency of the amount of Fe supported in

the following days of impregnation (up to 5 days). However, the net amount of

impregnated Fe differs depending of the fiber condition being the functionalized fiber the

one with the higher amount of impregnated Fe all along the impregnation process, the final

amount of Fe impregnated was 6.2, 11.1 and 14.9 wt % for the raw, pretreated and

functionalized fibers, respectively. This results highlighted the importance of the

functionalization process and the proper chemical configuration of the fiber surface in the

impregnation process. FT-IR confirmed the presence of Na+ on the functionalized fiber

surface promoting the chemical bonded adsorption of Fe species. Meanwhile on the

functionalized fiber the chemically driven adsorption has an important role, the physical

driven adsorption is the dominant one in the raw and pretreated fibers

XRD profiles of the functionalized fiber after the impregnation process allowed to conclude

that iron species supported on the fiber surface correspond to Fe2O3 (hematite) and α-Fe0.

The size and the shape of the iron hematite peak indicates that these are essentially iron

nanoparticles (28.2nm calculated using the Scherrer equation). The fact that only the main

peak of hematite (lacking some secondary peaks) and that only a secondary peak for the

α-Fe0 are observed indicates that under the impregnating conditions there is not a

complete evolution of the crystalline structures.


Further evidence on the chemical interaction of the impregnated Fe specie and the

functional groups on the surface of the functionalized fiber was obtained by FT-IR where

the characteristic stretching vibrations between 450 to 600cm-1 revealed the presence of

iron oxide compounds. Specifically for γ-Fe2O3 (maghemite) two peaks around 463 and

1630cm-1 were identified, the first one corresponds to Fe-O bending vibration mode. A

broad peak at 162 cm-1 and two peaks in 463 and 546cm-1 were observed, which are the

characteristic absorption bands of α-Fe2O3 (hematite). Two additional stretching vibrations

at 420 and 618cm-1 revealed the presence of Fe-O interactions confirming the existence of

zero valent iron supported species observed in the XRD profiles [31].

No major change in the pHzpc values of the functionalized fiber was observed during the

three days of impregnation, maintaining values between 8.56 to 8.83 (average 8.71 ±

0.08), suggesting a slightly basic character when compared to the original pHzpc value of

the functionalized fiber before exposed to the impregnation solution (pHzpc = 8.23 ± 0.08).

In terms, of the raw and pretreated fibers the acidic condition of the impregnating solution

creates positive charged surface hindering the ability of the impregnating Fe+3 cations and

explaining the differences in the amount of Fe impregnated observed for the raw and

pretreated fibers when compared with the functionalized fiber.

BET area of the functionalized fiber is not affected by the impregnation process mainly due

to initial low surface are of the sample (characteristic of materials lacking meso and

microporosity) prevents any surface area loss due to pore mouth blockage.

SEM pictures of the impregnated functionalized fiber after 1 and 2 days showed that the

fiber surface is unevenly covered by impregnated nanoparticles, high magnification SEM

pictures allow to verify that densely populated area correspond to finely dispersed

nanoparticles, this conclusion was confirmed via backscattering analysis. SEM pictures of

the 2 days impregnated functionalized fiber shows some aggregation of particles that are

loosely attached to the surface; lixiviation experiments were performed showed that the

amount of lixiviated particles is minor (only 5.38% of the impregnated iron) and the particle

size distribution of these particles present a broad normal distributed peak ranging from

around 50 up to around 500 nm, with an average particle size of 147 nm. Some of the

particles size distribution plots showed an extra small peak at higher particle size (around

8 microns), probably coming from the big loosely aggregates.


Mechanically the impregnated fibers were shown to have lower values in the tensile

strength and effort to fracture, but higher values for the Young's moduli, which could be a

reflection of the interactions between the fiber matrix and the nanoparticles, as well as

characteristics of each of the constituent elements of the impregnated material.

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Chapter 4. Heterogeneous Fenton oxidation of

Orange II using iron supported on modified

fique catalysts

Abstract:

Degradation and mineralization of the dye Orange II (OII) was performed with

nanoparticles supported on fique as catalysts in reactions conditions that promotes the

heterogeneous Fenton reaction. A Box-Behnken experimental design was used to

evaluate the effect of: pH (2.5 - 3.5), initial OII concentration: 𝐶𝑂𝐼𝐼0 (2𝑥10−5 - 2𝑥10−4M),

initial hydrogen peroxide concentration 𝐶𝐻2𝑂20 (1𝑥10−4 - 10𝑥10−3M) and load of iron in the

catalyst (10.9, 14.9 𝑎𝑛𝑑 13.2) wt.% in the degradation of OII. A 93.23% of degradation was

obtained after 4 hours of catalytic activity under following conditions: pH: 2.5, 𝐶𝑂𝐼𝐼0:

1.1𝑥10−4𝑀, 𝐶𝐻2𝑂20: 5.05𝑥10−3M and 10.9 𝐹𝑒 %𝑤𝑡. pH was determinate to be the most

influential variable in the degradation process, reporting to have better degradation at

lower pH. A simplified pseudo-first-order kinetic model was proposed and described 16 of

the degradation conditions with a R2 above 0.9; a very remarkable result for such a simple

model. Catalyst deactivation was tested for 7 consecutive cycles, showing that the

catalysts kept high activity up to 4 cycles. The effect of Cl- ion in the OII degradation was

determinate to be damaging in term of degradation rates for concentration as low as

0.05M and damaging both, degradation rate and final degradation value for 0.1 M.

Keywords: Fenton, water treatment, Orange II, fique, iron nanoparticles.

Introduction

Recalcitrant compounds are chemically resistant to degradation, reason why it is an

important topic of current research to find a process that safely convert these contaminant

4. Heterogeneous Fenton oxidation of Orange II using iron supported on modified fique catalyst s 105

compounds into components with the higher stable oxidation state through a

mineralization process. Industrial activities generate high percentages of wastewater,

which in some cases are directly discharged into effluents, affecting the environment [1].

Azo dyes, extensively use in industry, are potentially carcinogenic and toxic because

aromatic amines are present in their chemical structure. OII (C16H12N2NaO4S), is a

heterociclyc anionic azo compound from the group of naphthols, use as dye in the textile,

cosmetic, silk and paper industries [9]. Additionally, OII is a non-biodegradable compound

that poses a potential risk to human health [7,8].

Treatment of effluents contaminated with dyes used physical, chemical and biological

processes and frequently they are not completely effective [6], as only they change the

pollutant from one stream to another (physical processes) or may have very slow

degradation rates (biological processes) [7]. In addition, currently there are alternatives

such as activated charcoal [8], ozone [9] and hypochlorite [4], but are inefficient

alternatives for secondary waste generated (residual chlorine) and costly in terms of

operation, equipment and production.

Advanced oxidation processes (AOPs) has been proposed as an alternative solution;

AOPs used oxidation Fenton's reagent to degrade and mineralize effluents contaminated

with dyes, it is a particular case of wet oxidation with hydrogen peroxide (CWHPO) and

has the advantage of being efficient even at ambient temperature and pressure, it is a also

a simple and economic process [10].

The reaction between iron and hydrogen peroxide (an important mechanism in the Fenton

oxidation process), increases the amount and reactivity of hydroxyl radicals produced in

acid solution by peroxide decomposition, these species attack the organic matter present

in the reaction medium, due to oxidative power that the radicals generated on the surface

of the solid [11]. The effectiveness of the catalyst in the oxidation of dyes is influenced by

the synthesis variables (explained in previous works) and the reaction conditions

discussed in this chapter.

Homogeneous processes have the disadvantage of requiring about 50 to 80 ppm of iron in

solution to be effective, concentration in many cases above of the permitted regulation

(European Union allows maximum of 2 ppm Fe in the water treatment) [12], this strict

regulation in the amount of dissolved Fe, implies that most of the time it is necessary to


have a secondary treatment to reduce the contaminant or to use higher concentration of

dissolved Fe but implementing further processes to recover the remainder iron, turning the

homogeneous processes into a costly treatment, suitable only under very specific

conditions.

On the other hand, heterogeneous catalysis using solid supports allow to deposit the

active phase (iron compounds) on their surface, facilitating the retrieving of the catalyst

from the reaction solution, improving the mechanical resistance and in many case creating

a synergetic effect that improves the chemical activity of the material. There have been

reports of the use of different types of catalytic supports in the degradation of OII, ie. clays

[13], silica [14], alumina [15], aluminosilicates [16], cation exchange resins [17], chelants

[18], zeolites [19] and activated charcoal [20]. Nowadays the use of natural products as

catalytic supporting materials is a trend, due to the interesting properties that these type of

materials could have.

The use of nanosized iron compounds in the treatment of wastewater, takes advantage

the high reactivity, increase surface area and synergic support-particle effects [21].

Particularly, the use of nanometric iron species in industrial water treatment have been

reported to present the following advantages: i) efficiency in the treatment of effluents, ii)

nanoparticles usage cycles, iii) environmental safety, iv) low cost of iron, v) strong

adsorption capacity, vi) easy separation and vii) good stability [22].

The aim of this chapter was to evaluate the effect of crossed factors: pH, 𝐶𝑂𝐼𝐼0, 𝐶𝐻2𝑂20

and 𝐹𝑒 𝑤𝑡. % the efficiency of OII dye degradation. A Box - Bhenken experimental design

surface was used to identify the most important factors that affect the process, allowing

obtain statistically significant empirical models.

In addition, under the most favorable operating conditions the effect of temperature,

inhibitory concentration of chloride ions and stability of the catalyst, were evaluated. In

order to analyze the obtained percentage of mineralization the total organic carbon (TOC)

and the total nitrogen (TN) were determinate.



OII degradation

Based on the physicochemical properties characterized in the material synthesized in

previous works, the impregnated material obtained on the functionalized fiber MC3

(denominated catalysts hereinafter) was selected to be tested in the catalytic experiments

on the degradation of OII. The resulted catalysts have iron loadings of 10.9, 13.2 and

14.9wt%, quantified by FAAS.

The catalytic oxidation reaction was performed in a jacketed glass batch reactor (500 mL),

kept under constant agitation (240 rpm). Each run lasted 240 minutes; used 800 mg of

catalyst contained in paper bags (with pore size: 0.45μm, dimensions: 450x500x0.8mm,

permeability: 1500 L/m2.s, material: thermosetting filter paper for tea bags [23]) in contact

with 250 mL of an OII solution (C16H11N2NaO4S, Sigma -Aldrich®), experiments were

performed at 20oC; Values of the experimental pH, OII solution concentration, hydrogen

peroxide concentration and iron loading on the catalyst were set according within the limits

of the ranges reported in Table 4.1 and the design of experiments summarized in Table

4.2.

All experiments were performed ensuring that the predominant mechanism of the process

was the oxidation reaction and not mass transfer [24,25]. For this, the Weisz – Prater

criterion was used [26], which establishes that for CWP << 1 there are not internal diffusion.

The agitation level was kept 240 rpm because ensures the Weisz – Prater criterion and

was not strong enough to caused mechanical damage to the catalyst. In order to meet the

criterion Cwp the catalyst size was reduced to a particle size of 8mm in which Cwp << 1

was fulfilled. Agitation and catalyst particle size was also set to ensure that the effect of

diffusion resistances from the bulk of the reaction solution to the catalyst surface were

eliminated.

A set of experiments was performed implementing a Box- Bhenken design of experiments

(DOE) with response surface, which used the maximum and minimum levels of the four

factors evaluated in the degradation of the dye Orange II (see Table 4.1), with triplicate on

the center point, for a total of 27 experiments. The ranges considered for the operating

variables were chosen after making an intensive literature review [19,27-29], these

conditions are representative of those founded in industrial wastewater effluent.


MiniTab 16 Statistical Software served to identify the contribution of each variable and its

interaction in the degradation of the dye OII through the respective statistical analysis of

the data obtained. Statistical regression was used to fit a second order polynomial

experimental data and identify relevant terms of the model (equation (1)).

𝑌 = 𝛽0 + ∑ 𝛽𝑖𝑥𝑖 + ∑ 𝛽𝑖𝑖𝑥𝑖𝑖2 + ∑ 𝛽𝑖𝑗𝑥𝑖𝑥𝑗 𝐸𝑞 (1)

Where β0 is the compensatory term; βi is dependent term or the linear effect of factor input

xi; ii is the quadratic effect input factor xi and βij is the effect of interaction between the

linearly linear input factor xi and xj.

Table 4.1. Factors evaluated in the dye degradation of OII using iron supported on fique catalyst 22

Factor

Level

Low Medium High

pH 2.5 3 3.5

[OII]o (M) 2𝑥10−5 1.1𝑥10−4 2𝑥10−4

[H2O2]o (M) 1𝑥10−4 5.05𝑥10−3 1𝑥10−2

Fe wt.% 10.9 13.2 14.9

For each run the values of the variables pH, temperature and initial concentration of dye

were set then reaction was started by adding the hydrogen peroxide solution (Merck). The

pH was measured with a pH meter (Toledo LE427), the initial pH of the solutions to be

treated was adjusted with the addition of 0.1M NaOH or 0.1M HCl.

The reaction advance was continuously monitored using an UV-vis spectrophotometry to

track the absorbance the OII molecule in a quartz cell; OII concentrations were assessed

through a calibration curve obtained at a wavelength of 486nm (See annex 3).

The degradation percentage of the dyes was expressed as the equation (2):

𝐷𝑒𝑔𝑟𝑎𝑑𝑎𝑡𝑖𝑜𝑛 (%) = 𝐶𝑜 − 𝐶

𝐶0𝑥 100% 𝐸𝑞 (2)

where C0 is the initial concentration of the dye (mg /L) and C is the residual concentration

of the dye (mg /L).


Upon completion of each experiment an aliquot of the treated solution was taken in order

to assess the stability of the catalyst, the amount of iron leached was quantified by flame

atomic absorption spectrometry (FAAS) using the injection method in a Hitachi z-8000

atomic absorption spectrometer equipped with an atomizer with air/acetylene burner used

for the determination of elemental iron. The wavelength used for the determination of the

analyte was: Fe 248.3nm.

The DOE conditions that provided one of the highest OII degradation were used to perform

two new sets of experiment, the first once investigates the effect of temperature in the

degradation reaction, in this case, degradation experiment were done at 30, 50 and 70oC.

The second set of experiments comprised continues cycles of reaction at 20oC (up to 7

cycles), in which the very same catalyst was reuse.

Effect of chloride ion

Several studies have reported contradictory effects of the concentration of ions in the

reaction solution for the oxidation of Orange II, in particular the effect of Cl- ion have been

reported to both to have beneficial and detrimental effects that seem to be dependent of

the ion concentration and the type of catalyst used [27-29]. Based on this evidences a set

the experiments run under the pH, H2O2 and Orange II concentration and iron catalyst

loading that give the third highest Orange II degradation in the DOE, along with three

different level of chloride ions in concentrations ranging from 0 to 1𝑥10−2M were

performed.

Total Organic Carbon (TOC) and Total Nitrogen (TN) analysis

Considering that OII degradation monitored by UV-vis spectrophotometry does not enable

to determine if there was complete oxidation of the dye molecule. Two type of analysis

were implemented to verify the advance of the chemical oxidation in the degradation

process, TOC and TN analysis were performed on a Shimadzu TOC-VCHS/CSN

analyzer following the Clean Water Act Analytical Methods 352.1 [30], 353.2 [31] and

410.4 [32] approved by EPA (US Environmental Protection Agency). TOC and TN were

done on sample taken from the reaction solution (before and after reaction) of an

experiment performed at the operating conditions the DOE showed to be the third highest

terms the Orange II degradation.


Identification of intermediate products resulting from the

treatment of OII

High pressure liquid chromatography (HPLC) was used to identified the possible

intermediate compounds generated during the reaction of Orange II degradation, an

Agilent Technologies 1260 Infinity chromatograph was used; the chromatograph was fitted

with a Jupiter 5μm C18 300Å column, made of stainless steel with measures of 250 x 4.6

mm. The separated compounds were analyzed by a detector 325 Dual Wavelength UVVis.

The mobile phase used was a methanol and water in relation 95:5, flow was set as

1 mL.min-1 with injection volumen of 20 μL and the linear gradient shown below was

established: t = 0, H2O = 95, metOH = 5 ; t = 20, H2O = 30, metOH = 70; t = 25, H2O =

95, metOH = 5; t = 28, H2O = 95, metOH = 5.


OII degradation

Preliminary experiments were performed to verify if any percentage of degradation could

be attributed to dye adsorption on the catalyst and/or on the paper bags containing the

catalyst (Experiments 1 and 3 in Figure 4.1). Neglectable degradation values were

obtained, 0.1 and 0.03% degradation for the catalyst contained in the tea bag experiments,

respectively. This small values demonstrated that dye adsorption or oxidation on the

catalyst and/or on paper bags is not important in the degradation process. Also, Figure 4.1

shows the important effect of H2O2, without the presence of H2O2 the advance of the

reaction is essentially null, indicating that the sole presence of Fe+3 in the catalyst is not

enough to drive the degradation of OII.

Additionally, the homogenous H2O2 oxidation capability was determine by performing an

experiment in which not catalyst was added (Experiment 2, Figure 4.2); it was conclude

that for the operating condition of the experiment the H2O2 has a contribution in the order

of 0.3%. The results of the experiments presented in Figure 4.2 shows that the variables

H2O2, catalyst and paper bags applied independently have not major effect in the


degradation OII.


conditions: Experiment 1 (Catalyst Fe10.9 wt.% and Dye 𝐶𝑂𝐼𝐼0: 2𝑥10−4𝑀), Experiment 2

(Dye 𝐶𝑂𝐼𝐼0: 2𝑥10−4𝑀 and oxidizing agent 𝐶𝐻2𝑂20

: 5.05𝑥10−3𝑀), Experiment 3 (Catalyst 10.9

Fe wt.%, Dye 𝐶𝑂𝐼𝐼0: 2𝑥10−4𝑀, catalyst contained in aromatic bag28

Figure 4.2 shows a typical OII degradation curve under the typical experimental conditions

used in this study. Two stages in the degradation process are identified, an initial very fast

degradation section for reaction time before 30 minutes, characterized by the conversion

of Fe+2 into Fe+3 [26]. Followed by a long and slow degradation process after 30 minutes

where Fe is found primarily in the Fe+3, denominated Fenton – Like. The first stage is an

unstable state that depends of the initial catalyst characteristics and reaction solution

characteristics (iron loading, iron compound reduction/oxidation state, ions dissolved in the

solution, among others) and is frequently considered to be a catalyst conditioning period.

Essentially, the possible mechanisms of reaction are limited to those proposed in the

literature which take into account ferric and ferrous ions, then the effect may have been

zero valent iron was not analyzed, as it is beyond the scope of this investigation.


conditions: pH: 2.5, 𝐶𝑂𝐼𝐼0: 1.1𝑥10−4𝑀, 𝐶𝐻2𝑂20

: 5.05𝑥10−3𝑀 and 10.9𝑤𝑡. % 29

0,0

0,1

0,2

0,3

0,4

0 30 60 90 120 150 180 210 240

Deg

rad

ati

on

(%

)

Time (min)

Experiment 1Experiment 2Experiment 3

0,0

0,2

0,4

0,6

0,8

1,0

0 30 60 90 120 150 180 210 240

CO

II/C

OIIo

Time (min)


The characteristic shape of the degradation curve reported in Figure 4.2 is typical of

materials with low surface area and low porosity, as the ones characterized in this work.

This behavior is due to the easy accessibility of Fe+3 ions to react with OH• radicals and

promotes immediate oxidation reaction and therefore degrading the contaminating dye.

Table 4.2 summarizes the experimental conditions of each one of the 27 runs (pH, 𝐶𝑂𝐼𝐼0,

𝐶𝐻2𝑂20, Fe wt.% has 3 different levels: high (1), medium (0) and low(-1)), included tests to

determine crossed factor effects and also include the three center point runs. These

experiments were performed randomly to minimize possible systematic errors that can be

generated (All experimental results are in the Annex 4).

Table 4.2. Experiments values of Box - Behnken experimental design, degradation percentage obtained for each experimental conditions 23

Run Ph COIIo (M) H2O2 (M) Fe wt.% %Deg

1 0 -1 1 0 5.91

2 0 0 0 0 6.83

3 -1 0 0 1 81.94

4 1 0 0 -1 19.67

5 1 0 0 1 1.22

6 0 1 -1 0 1.28

7 0 1 1 0 0.56

8 -1 0 0 -1 93.23

9 0 -1 -1 0 53.30

10 1 1 0 0 0.23

11 -1 -1 0 0 94.50

12 -1 1 0 0 62.96

13 0 0 0 0 27.98

14 1 -1 0 0 5.43

15 0 0 1 -1 60.19

16 0 0 -1 1 4.31

17 0 0 1 1 3.49

18 0 0 -1 -1 40.31

19 0 -1 0 1 49.05

20 1 0 1 0 4.23

21 0 1 0 1 0.30

22 0 0 0 0 20.08

23 -1 0 -1 0 86.72

24 1 0 -1 0 20.27

25 -1 0 1 0 95.61

26 0 1 0 -1 2.24

27 0 -1 -1 -1 7.28


Eq (3)

(3)

The statistical adjustment of the equation decribed previously (equation (1)) to the data

summarizes in Table 4.3, leads to the experimental description of the degradation

(equation (3)); where A:pH, B: COIIo, C: H2O2 and D: Fe wt.%.

𝐷𝑒𝑔 (%) = 1571.83 − 755.377A − 306406B + 13859.4C − 47.2442D + 114.042𝐴2

− 846940966𝐵2 + 195140𝐶2 + 2.04457𝐷2 + 146307AB

− 2517.69AC − 0.68625AD + 26190702BC − 15441.8BD

− 843.564CD

Table 4.3. Analysis of variance (ANOVA) for percentage of degradation by MiniTab 16

Statistical Software24 Source DF Seq SS Adj SS Adj MS F P

Regression 14 27807.8 27807.8 1986.3 6.45 0.003

Linear 4 19908.6 13143.6 3285.9 10.67 0.001

A: pH 1 17933.4 11805.3 11805.3 38.35 0.000

B: COIIo 1 1823.4 950.6 950.6 3.09 0.109

C: H2O2 1 109.2 15.1 15.1 0.05 0.829

D: Fe wt.% 1 42.6 372.7 372.7 1.21 0.297

Square 4 6500.8 6500.8 1625.2 5.28 0.015

AA 1 5681.9 4335.2 4335.2 14.08 0.004

BB 1 343 251 251 0.82 0.388

CC 1 199.5 121.9 121.9 0.40 0.543

DD 1 276.4 276.4 276.4 0.90 0.366

Interaction 6 1398.4 1398.4 233.1 0.76 0.619

AB 1 173.4 173.4 173.4 0.56 0.470

AC 1 155.3 155.3 155.3 0.50 0.494

AD 1 3.2 3.2 3.2 0.01 0.921

BC 1 544.6 544.6 544.6 1.77 0.213

BD 1 52.1 52.1 52.1 0.17 0.690

CD 1 469.9 469.9 469.9 1.53 0.245

Total 26 30957.0

Additionally, the interaction A2 also related to the pH indicates the presence of a curvature

in the model and thereby the possible existence of maximum degradation value within the

range of variables studied (Show in the Annex 5). Given the high efficiency obtained in the

degradation, it was concluded that the levels analyzed were adequate. The model shows a

good fit of the experimental and the calculated data, reflected by the correlation coefficient

R2 = 90.06% and R2 adjusted = 74.15%.


Figure 4.3. Experimental and calculated results of the experimental design for Orange II

oxidation. Degradation Response (%).30

In order to determine the appropriate fitting data regression and analysis of variance

(ANOVA), analysis of residual plots that are defined as the difference between the set

values (model) and the observed values (experimental) was performed.

Figure 4.4. Residual plots for kapmod a) Normal probability plot, b) Versus fits, c) Histogram and d) Versus order31

As shown in Figure 4.4a residues, follow a normal distribution, half of data takes positive

values (over 50%) and the other half negative values (below 50%), which allows to

conclude that there are no significant deviations of residuals from the normal distribution.

Figure 4.4b, 4.4c and 4.4d allow to verify the homocedasticity of the residuals (constant

variance) meaning they are symmetrically distributed and are not interdependent to each

other.

0

20

40

60

80

100

0 20 40 60 80 100

Deg

(%

) c

alc

Deg(%) exp

30150-15-30

99

90

50

10

1

Residual

Pe

rce

nt

1007550250

30

15

0

-15

-30

Fitted Value

Re

sid

ua

l

24120-12-24

8

6

4

2

0

Residual

Fre

qu

en

cy

2624222018161412108642

30

15

0

-15

-30

Observation Order

Re

sid

ua

l

Normal Probability Plot Versus Fits

Histogram Versus Order

Residual Plots for % Deg

a)

a)

b)

b)

c)

c)

d)

d)


Figures 4.5, 4.6 and 4.7 allows to observed the combined effect of the experimental

variables catalyst loading (Fe wt.%),H2O2 and COIIo concentration when paired with the pH

variable, a local maximums is always observed at pH = 2.5. although most of the literature

reports that for pH values below 3 Fenton oxidation becomes less effective due to the

regeneration of Fe+2 is inhibited by the formation of intermediate products such as

hidroxiperoxonium radicals (H3O2+) [26]. This low pH catalytic activity seems to be unique

for the combination of iron supported on fique fiber and turning this catalyst into a very

attractive catalyst for specific applications at low pH.

In pH values between 3 and 3.5 degradation did not achieved good results (just in the

range between 0 to 20%), which could be related to the great dependence of the iron

oxidation state as a function of pH; indicating that under these pH conditions Fe+2 may not

be present in enough concentration, hindering its reaction capability with hydroxyl groups

and affecting the Fe+2 to Fe+3 cycle necessary for the degradation reaction to take place,

and boosting the formation of competitive intermediates such as FeOOH [19].

Although the effect of the concentration of H2O2 it was determine to be a factor with not

statistical significance, it can be observed in Figure 4.5 that the combination of factors pH

and H2O2 is particularly important at low pH levels, emphasizing the significant effect the

low pH has for this type of catalyst (Figure 4.5).

𝐶6𝐻11𝑁2𝑁𝑎𝑂4𝑆 + 42𝐻2𝑂2 → 2𝐻𝑁𝑂3 + 𝑁𝑎𝐻𝑆𝑂4 + 46𝐻2𝑂 + 16𝐶𝑂2 𝐸𝑞 (4)

Equation (4) relates the theoretical number of moles of oxidizing agent required to degrade

1 mol of OII dye [35], all concentrations used in the experimental design have values

above to the stoichiometric amounts required for complete mineralization.

So the concentration of H2O2 and the percentage degradation are directly proportional as a

result of competition by hydroxyl radicals, Figure 4.5 shows that even the lowest amount of

peroxide managed to have good performance in the percentage degradation. At low pH

value for any H2O2, the degradation obtained is above 80%, which implies, in terms of

application, that using low H2O2 concentration will render high degradation, while keeping

H2O2 at the minimum possible.

From Table 4.2 can be observed that the H2O2 medium level concentration (5.05x10-3 M)

generates high degradation percentages in combination with low pH level (runs 3, 8 and

11), rendering degradation values of 81.94, 93.23 and 94.5%, respectively.


Figure 4.6 shows the combine effect of the catalyst Fe loading and pH; once again, only at

low pH value (pH = 2.5) the catalyst Fe loading showed significant OII degradation,

emphasizing the pivotal role pH has in the reaction. Although the iron loaded to the

catalyst could be significant different (from 10.9 to 14.9 wt.%), the degradation obtained for

any catalyst at low pH is also above 80%, being this an additional evidence of the complex

network of reactions happening in the Fenton process. Iron role in the Fenton reaction

have been related to the net balance of OH• radicals available to react, a low iron

concentration available to react, will have a negative effect in the degradation because

there will be also low concentration of OH• ready to react, and the opposing effect will

happen as the iron available to react increases, however an excess of iron could also

interfere negatively with the Fenton reaction [19].

Figure 4.5. Contour plot of Degradation (%) vs H2O2 and pH 32


Figure 4.6. Contour plot of Degradation (%) vs %Fe and pH 33

Figure 4.7. Contour plot of Degradation (%) vs COIIo and pH 34

OII initial concentration showed a negative effect on the degradation process (Figure 4.7),

because at higher initial concentrations of dye more time is required for degradation, the

degradation percentage decreases and increases the formation of intermediates, which is

consistent with results obtained by other authors [16,25]. If the initial concentration of dye


Figure 4.8. Degradation OII, the left part initial color and the right the color after the

treatment under the conditions: pH: 2.5, COII0: 1.1x10−4M, CH2O20

: 5.05x10−3M and

10.9 Fe wt. %)35

is high (2𝑥10−5 − 1.1𝑥10−4𝑀 ), the amount of available H2O2 molecules could be

considered to be constant, reducing the possibility of interaction between OII/ OH• [25].

The extensive work performed on the determination of OII degradation on iron/modified

fique fibers catalysts and the robust and rigorous statistical support provided by the Box –

Behnken DOE allow to identified a potential set of operating conditions that would reach

high degradation percentages, while reducing the consumption of H2O2, iron loading,

examining the effect of Orange II initial concentration and optimizing pH (pH: 2.5, COII0:

1.1x10−4M, CH2O20: 5.05x10−3M and 10.9 Fe %wt). This operating condition will be used in

the chloride ions, temperature effect and deactivation experiments.

Many attempts have been made to described the reaction mechanisms of the

heterogeneous Fenton reactions, but due to intricate interaction of intermediate species,

effect of pH in the net balance of OH• in solution and the simultaneous action of

consecutive, parallel and in some case competitive reactions, not a clear kinetic equation

that broadly describe this phenomena has been tested.

Relevant approaches have been done in order to produce semi-empirical equations useful

for scaling up and reactor design. Kinetic model based on Fermi’s function has shown to

properly describe Fenton processes in which the degradation evolution shows a sigmoidal

characteristic curve, related for particular reaction conditions, type of catalyst and


contaminant molecule [16]. None of the degradation curve in this study showed a

sigmoidal curve, on the contrary the behavior for most of them was some sort of

exponential decay, for this case a simplified pseudo-first-order kinetic could be proposed

[36].

The catalytic degradation of OII based in Fe+3/H2O2, can be described from the mass

balance corresponding to a batch reactor relative to the concentration of OII, considering

perfect mixing, as follows equation (5):

−𝑑𝐶𝑂𝐼𝐼

𝑑𝑡= 𝑘𝐶𝑂𝐻∎𝐶𝑂𝐼𝐼 𝐸𝑞 (5)

where k is the rate constant, t is the degradation time, 𝐶𝑂𝐻∎ is the hydroxyl radicals

concentration and 𝐶𝑂𝐼𝐼 is the dye concentration at a given time. Like other authors [32, 35],

Fenton oxidation studies is assumed that the concentration of OH• is constant along each

of the runs, which allows to write the equation (6):

(−𝑟𝑂𝐼𝐼) = 𝑘𝑎𝑝𝐶𝑂𝐼𝐼 𝐸𝑞 (6)

kap values can be calculated from the experiments performed by the DOE, after linearizing

the data from the integration of the mass balance equation (equation (5)), evaluated

between the limits (t0=0, C0) and (t, C). The integrated expression is:

−ln (𝐶

𝐶0) = 𝑘𝑎𝑝𝑡 𝐸𝑞 (7)

The pseudo-first order rate constants of degradation were calculated from linear

regression - ln (COII / COIIo) vs time plots. The type of oxidation process studied occurs

when H2O2 is brought into contact with Fe2+ ions in solutions at acidic pH. The ferrous and

ferric ions initiates the reaction of peroxide decomposition, which gives as results the

generation of highly reactive radicals OH• and perhydroxyl (𝐻𝑂2∎), being the hydroxyl

radicals the ones with greater oxidizing power (equations (8) and (9)) [39].

𝐹𝑒+2 + 𝐻2𝑂2 → 𝐹𝑒+3 + 𝑂𝐻− + OH • 𝐸𝑞 (8)

𝐹𝑒+3 + 𝐻2𝑂2 → 𝐹𝑒+2 + 𝐻𝑂2∎ + 𝐻+ 𝐸𝑞 (9)

Fenton's reactions are highly complex chemical combination of sequential and/or

simultaneous reactions involving initiation, propagation, termination stages in which


oxidation and reduction cycles, simultaneous formation radical species with lower oxidizing

power, in addition to the multiple radical species may be present at once; making the

development of a mechanistic kinetic expression a very convoluted task. The results of the

simplified pseudo-first-order kinetic analysis is reported in Table 4.4.

Table 4.4. Simplified pseudo-first-order kinetic analysis 25

Run kap (min-1) R² Run kap (min-1) R² Run kap (min-1) R²

1 2.31x10-4 0.951 11 9.78 x10-3 0.899 21 1.12 x10-5 0.719

2 2.90 x10-4 0.917 12 3.53 x10-3 0.942 22 8.08 x10-4 0.940

3 5.89 x10-3 0.997 13 1.10 x10-3 0.885 23 7.20 x10-3 0.962

4 5.76 x10-4 0.526 14 1.85 x10-4 0.760 24 9.99 x10-4 0.909

5 5.17 x10-5 0.954 15 3.41 x10-3 0.925 21 1.12 x10-5 0.719

6 4.17 x10-5 0.726 16 1.84 x10-4 0.979 25 1.17 x10-2 0.971

7 2.15 x10-5 0.918 17 1.56 x10-4 0.967 26 6.55 x10-5 0.700

8 9.20 x10-3 0.863 18 1.80 x10-3 0.919 27 2.53 x10-4 0.693

9 2.60 x10-3 0.673 19 1.82 x10-3 0.452

10 8.69 x10-6 0.908 20 1.91 x10-4 0.986

The simplified pseudo-first-order kinetic model is able to describe 8 of the degradation

conditions with a R2 above 0.95, an additional set of 8 degradation conditions are describe

by the simplified pseudo-first-order kinetic model a with a R2 above 0.90. It is quite

remarkable that such a simple model could fit such a complex kinetics; out of the

remaining 11 set of condition, 3 of them have R2 above 0.85; the remaining 8 degradation

conditions have R2 below 0.75.

Figure 4.9. Effect of temperature ions in OII degradation after 4 hours of catalytic activity

under these conditions: pH: 2.5, 𝐶𝑂𝐼𝐼0: 1.1𝑥10−4𝑀, 𝐶𝐻2𝑂20

: 5.05𝑥10−3𝑀 and 10.9 𝐹𝑒 %𝑤𝑡 36

In order to evaluate the influence of temperature on the degradation process, experiments

were performed at different temperatures (30, 50 and 70oC), under the conditions that

0

20

40

60

80

100

0 30 60 90 120 150 180 210 240

Deg

rad

ati

on

(%

)

Time (min)

30°C

50°C

70°C


were found to generate the third highest OII degradation in the DOE (run 8): pH: 2.5, 𝐶𝑂𝐼𝐼0

:

1.1𝑥10−4𝑀, 𝐶𝐻2𝑂20: 5.05𝑥10−3𝑀 and 10.9 𝐹𝑒 𝑤𝑡. %. The results of this experiment are

shown in Figure 4.9.

The OII degradation profiles for 30 and 50oC have overlapping behavior reaching a 57% of

degradation up to 30 minutes of reaction, form that point forward the profile obtained at

50oC shows a better performance, reaching almost 89% of degradation after 60 minutes

of reaction, meanwhile the 30oC profile at the same time only reaches 67%. The 70oC

profile over performs both the 30 and 50oC, reaching close to 94% of degradation in the

initial 30 minutes. It is not surprising that temperature accelerates the degradation process,

due to the exponential dependency of the Arrhenius factor with temperature, probably

enhancing the OH• production and iron regeneration [25,34]. However, due to the large

volume of wastewater usually generated with this type of contaminant, the option to use

temperature to reduce the degradation time is not practical in terms of operating costs.

Catalyst stability was determine performing repetitive degradation cycles with the same

catalyst and by taking samples, to be analyzed by FAAS, from the reactive solution at the

end of each cycle.

Figure 4.10. Cycle number of use of OII degradation after 4 hours of catalytic activity


: 5.05𝑥10−3𝑀 and 10.9 𝐹𝑒 𝑤𝑡. % 37

The result of the catalyst deactivation (continue degradation cycles, for a total de 28 hrs of

reaction) are presented in Figure 4.10, out of the 7 cycles performed only cycle 1, 5 and 7

are shown, because the reduction in degradation between run 1 to 4 were small; from

cycle 1 to 5 there was a reduction in the final degradation value in order of 10%, however

0

10

20

30

40

50

60

70

80

90

100

0 30 60 90 120 150 180 210 240

Deg

rad

ati

on

(%

)

Time (min)

Cycle 1

Cycle 5

Cycle 7


the reduction in the seventh run was considerable, reaching only 45% percent of

degradation.

In terms of Fe lixiviated from the catalyst to the reaction solution, the average value of the

amount of iron in solution for each run, corresponds to 0.822ppm (approximately 5.38% in

weight of the impregnate iron), which is below the allowed by the European Union value

which sets a maximum value of 2ppm [9], the Annex 6 reports the data obtained through

FAAS. The low concentration of iron lixiviated found in the final reaction solution implies

that the degradation reaction could be considerate essentially happening in the

heterogeneous phase, on the contrary the amount of iron leached (in terms of percentage

of impregnated Fe).

Figure 4.11 shows not significant changes in the crystallinity, iron phase and crystal size of

both the before and after catalysts, meaning that deactivation observed in the reaction

cycles it is not due to changes of the iron phase supported on the fiber.

Figure 4.11. XRD of catalyst before and after Orange II treatment38

Effect of chloride ion

Real wastewater could containing a mixture of inorganic anions that significantly affect the

degradation of OII. In literature the most reported effect is for the chloride ions; the results

of a set the experiments run under the pH, H2O2, OII concentration and iron catalyst

loading that give the second highest OII degradation in the DOE, along with three different

levels of chloride ions concentrations are presented in Figure 4.12.

0

200

400

600

800

1000

1200

5 8 11 14 17 20 23 26 29 32 35 38 41 44 47 50 53 56 59 62 65 68 71 74 77 80 83

Inte

nsi

ty a

.u.

2 tetha

After

Before


Figure 4.12. Effect of chloride ions in OII degradation after 4 hours of catalytic activity


: 5.05𝑥10−3𝑀 and 10.9 𝐹𝑒 𝑤𝑡%39

Figure 4.12 shows the significant influence the concentration of chloride ions have on the

degradation of OII, especially in the initial 30 minutes of reaction, being this another

evidence of the previous mentioned catalyst condition stage. For the time range from 0 to

180 minutes the free chloride ion experiment outperforms the 0.005 M experiment, form

that time on both experiments follow almost an overlapping behavior; meanwhile in the

case of the 0.01 M the free chloride ion experiment outperforms it in the whole reaction

time.

There have been reports related to the reduction in the OH• oxidative capability caused by

chloride ions inhibition, resulting in an increment of H2O2 consumption (equation 10 and

11) affecting the iron species reducing cycle and generating products containing chloride

ions [41].

𝐶𝑙− + 𝐻𝑂• → 𝐶𝑙𝐻𝑂•− (10)

𝐶𝑙𝐻𝑂•− + 𝐹𝑒+2 → 𝐶𝑙− + 𝐻𝑂− 𝐹𝑒+3 𝐸𝑞 (11)

Total Organic Carbon (TOC) and Total Nitrogen (TN) analysis

The extent of OII mineralization (the process through which an organic substance

becomes CO2 and water) [42] was determinate by TOC and TN. Table 4.5 summarizes

the TOC and TN results obtained; the total nitrogen reduction only reached 28.6% and

TOC value was reduced in a 55.4%, the fact that the Orange II molecule is a molecule with

extensive organic chemical groups units (nitro, hydroxyl, sulfonic, as shown in Figure 4.13)

made the mineralization of OII a very demanding process.

0

20

40

60

80

100

0 30 60 90 120 150 180 210 240 270

De

gra

da

tio

n (

%)

Time (min)

Chlorides 0M

Chlorides 0.005M

Chlorides 0.01M


Table 4.5. Total Organic Carbon (TOC) and Total Nitrogen (TN) analysis results 26

Sample TN (mg/L) TOC (mg/L)

Dye Orange II in solution (0.2mM) 1.739 44.89

Water treatment 2.437 20.04

Reduction (%) 28.6 55.4

Figure 4.13. Structural formula of the azo dye Orange II [38]40

The result of the TOC and TN indicates that, although there was an important fractioning

of the OII molecule, not a 100% of dye mineralization was achieved meaning that the azo

bond (-N=N-) was in fact attacked by the oxidizing species, however intermediates species

generated by the (-N=N-) breaking were not totally oxidized, on the contrary TOC and TN

results reveal that intermediates.

In order to identify which intermediates are presented after dye degradation, HPLC

chromatography was performed, Figure 4.14. shows the main absorbance band of OII in

the UV-Vis region is situated at 483nm, these are chromatograms of before and after

reaction using the catalyst of iron nanoparticles supported on fique fiber. Clearly the strong

absorption at 483 nm was drastically reduced after the treatment, confirming that the

chromophore bond N = N bond is completely broken, its decrease is due to degradation of

the aromatic portion of the dye, as these are easier to destroy compared to aromatic rings

[43].


Figure 4.14. Chromatogram obtained with a UV-Vis detector at 483 nm of OII dye before and after degradation 41

Figure 4.15. Chromatogram obtained with a UV-Vis detector at 230 nm related with benzene 42

0

10

20

30

40

50

60

70

80

0 5 10 15 20 25

mU

A

Time (min)

Before

After

0

20

40

60

80

100

120

140

0 5 10 15 20 25

mA

U

Time (min)

Before

After


Figure 4.16. Chromatogram obtained with a UV-Vis detector at 310 nm related with naphthalene 43

Two other bands at 230 nm and 310 nm are attributed to another intermediates as

benzene and naphthalene rings adjacent, as shown in Figure 4.15 and 4.16 respectively.

However, Figure 4.15 does not show a significant change in the presence of benzene,

while the Figure 4.16 evidences the apparition of a new peak after the reaction took place,

which allows to conclude that the amount of naphthalene present in solution increases

[44].

Conclusions

The effects of the reaction conditions on the degradation of OII on iron supported on

modified fique fiber catalysts was studied. A Box-Behnken design of experiments allowed

to determine the individual and the combined interaction of the main factor studied (pH,

𝐶𝑂𝐼𝐼0, 𝐶𝐻2𝑂20

and 𝐹𝑒 𝑤𝑡. %). A maximum OII degradation of 95.61% was obtained operating

at pH: 2.5, 𝐶𝑂𝐼𝐼0: 1.1𝑥10−4𝑀, 𝐶𝐻2𝑂20

: 1.1𝑥10−2𝑀 and 13.2 %𝐹𝑒 𝑤𝑡., the second highest

degradation value (93.23%) was obtained working at the same pH, 𝐶𝑂𝐼𝐼0 but at lower

𝐶𝐻2𝑂20 and %𝐹𝑒 𝑤𝑡; the second operating conditions generated a slighter lower

degradation but using half of the H2O2 and with a catalyst of only 10.9% of iron, making it

an interesting option from the engineering point of view. The presence of inhibitory chloride

ions had a not so significant negative effect (reduction only 10% compared to the

maximum degradation reached), temperature show to have a positive effect on the

degradation process. However TOC and TN experiment showed that not complete

mineralization was achieved in any of the experimental conditions tested.

0

5

10

15

20

25

30

0 5 10 15 20 25

mA

U

Time (min)

Before

After


Contour plots allowed to have a better understanding of the combined effects of 𝐶𝑂𝐼𝐼0

,

𝐶𝐻2𝑂20 and 𝐹𝑒 𝑤𝑡. % as a function of pH, which was statically determinate to be the variable

whit the highest impact in the process. Low pH level (2.5) was found to be the most

favorable condition for Orange II degradation, being this some of the lowest pH values

found in literature for heterogeneous Fenton reactions, converting the novel iron/modified

fique fiber catalyst into a very attractive alternative for specific applications at low pH.

A simplified pseudo-first-order kinetic model was proposed and was able to describe 16 of

the degradation conditions with a R2 above 0.9; a very remarkable result for such a simple

model.

The effect of the presence of chloride ions in the reaction solution were evaluated, results

show that concentrations as low as 0.005 M reduces the rate of OII degradation but after 4

hrs of reaction reaches the same OII degradation that the chloride ions free experiment.

On the contrary, the 0.01 M of chloride ions OII degradation test underperforms in the

whole extension of the experiment.

Catalyst stability was outstanding up to the initial 4 reaction cycles, but strongly decreased

after subsequent cycles; Fe lixiviation from the catalyst to the reaction solution was in the

order of 5.38% of the impregnated iron and may explain the loss of catalytic activity after

several reaction cycles.

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[32] “EPA METHOD 410.4.” [Online] US, 2014. Disponible: http://www.caslab.com/EPA-Method-352_1/.

[33] E. Neyens, J. Baeyens, “A review of classic Fenton’s peroxidation as an advanced oxidation technique” J. Hazard. Mater., vol. 98, no. 1–3, pp. 33–50, 2003.


[34] J. Feng, X. Hu, P. L. Yue, “Effect of initial solution pH on the degradation of Orange II using clay-based Fe nanocomposites as heterogeneous photo-Fenton catalyst” Water Res., vol. 40, no. 4, pp. 641–646, 2006.

[35] L. Bounab, O. Iglesias, E. González-Romero, M. Pazos, M. Ángeles Sanromán, “Effective heterogeneous electro-Fenton process of m-cresol with iron loaded actived carbon” RSC Adv, vol. 5, no. 39, pp. 31049–31056, 2015.

[36] S. Wang, “A Comparative study of Fenton and Fenton-like reaction kinetics in decolourisation of wastewater” Dyes Pigments, vol. 76, no. 3, pp. 714–720, 2008.

[37] H. Gallard, J. De Laat, “Kinetic modelling of Fe(III)/H2O2 oxidation reactions in dilute aqueous solution using atrazine as a model organic compound” Water Res., vol. 34, no.

12, pp. 3107–3116, 2000.

[38] M. Panizza, G. Cerisola, “Removal of organic pollutants from industrial wastewater by electrogenerated Fenton’s reagent” Water Res., vol. 35, no. 16, pp. 3987–3992, 2001.

[39] M. A. Blesa, "Eliminación de contaminantes por fotocatálisis heterogénea: texto

colectivo elaborado por la Red CYTED VIII-G : Usos de óxidos semiconductores y materiales relacionados para aplicaciones ambientales y ópticas" CIEMAT, 2004.

[40] J. Kiwi, A. Lopez, V. Nadtochenko, “Mechanism and Kinetics of the OH-Radical Intervention during Fenton Oxidation in the Presence of a Significant Amount of Radical Scavenger (Cl-)” Environ. Sci. Technol., vol. 34, no. 11, pp. 2162–2168, 2000.

[41] M. Vert, “Terminology for biorelated polymers and applications (IUPAC Recommendations 2012)” Pure Appl. Chem., vol. 84, no. 2, pp. 377–410, 2012.

[42] Sigma-Aldrich, “Orange II sodium salt (Certified by the Biological Stain Commission)” [Online] Colombia, 2016. Disponible:http://www.sigmaaldrich.com/catalog/product/ALDRICH/195235?lang=en&region=CO. [43] L. Chen, C. Deng, F. Wu, N. Deng, “Decolorization of the azo dye Orange II in a

montmorillonite/H2O2 system” Desalination, vol. 281, pp. 306–311, 2011. [44] G. Li, N. Wang, B. Liu, X. Zhang, “Decolorization of azo dye Orange II by ferrate(VI)–hypochlorite liquid mixture, potassium ferrate(VI) and potassium permanganate” Desalination, vol. 249, no. 3, pp. 936–941, 2009.

5. Studies on adsorption mercury from aqueous solution on biocomposite material from fique fiber and iron nanoparticles 131

Chapter 5. Studies on adsorption mercury

from aqueous solution on biocomposite

material from fique fiber and iron

nanoparticles

Abstract:

The adsorption of mercury ions from aqueous solution onto an adsorbent (fique fiber with

iron nanoparticles) is studied. In particular, were analyzed the effect of pH, initial

concentration of mercury ions ([Hg+2]) and load of iron in the adsorbent material (Fe wt%).

It is evident from a design response surface experiments (Box-Behnken) that in the

mercury adsorption, the chemisorption mechanism predominates respect to physisorption.

Langmuir and Freundlich isotherms were used to describe the physical adsorption of

mercury, however they failed to properly described most of the experimental isotherms

obtained. One simplified kinetic models, pseudo-second order, was tested to investigate

adsorption mechanisms. It was found that the kinetics of adsorption of mercury onto the

surface of the fique fiber with iron nanoparticles is described by the pseudo-second order

model supporting chemisorption (chemical reaction) as rate controlling mechanism which

indicates that the adsorption process is irreversible. pH has no apparent effect on

adsorption In the range of pH 4 to 7; however, for pH greater than 8, the adsorption

capacity increases as the pH value also increase.

Keywords: Furcraea andina, iron nanoparticles, mercury, adsorption, removal

Introduction

Mercury is considered one of the most harmful metals in the environment due to their

toxicity on a wide spectrum of flora and fauna, affecting human health as a result of

bioaccumulation in the food chain [1], accumulation of mercury on human organs and


tissue cause critical disabilities, such as Minamata disease [2]. Mercury in the environment

has two major sources, the first is one is denominate naturogenic (eruptions and

geothermal activities) and provides a minimum percentage in relation to the total amount

of pollutant mercury; the second form is the anthropogenic sources, which includes

combustion, mining and disposal of industrial processes.

Indiscriminate and in many cases illegal gold mining in Colombian Amazonas river have

showed to affect Amazonian ethnic groups, which have been tested to have the highest

level of mercury poisoning in Colombia, having bioaccumulate Hg between 15.4 and 19.7

parts per million (ppm) [3], when the EPA has set a maximum contaminant level of this 2

parts per billion (ppb) [4].

It is of great interest to remove this pollutant from wastewater and several types of

processes have been proposed such as: precipitation [5], coagulation [6], cementation [7],

ultrafiltration [8], solvent extraction [9], photocatalysis [10], adsorption[11] and ion

exchange [12], have been implemented within the possible alternatives to solve this

problem. However, currently mercury removal remains a problem due to the lack of

effective and economical, technologies that minimize energy and reagents consumption

while increasing the selectivity towards mercury removal [13]. Out of the mercury removal

technologies listed above, adsorption is the most used due to its simple operation, removal

efficiency, selectivity, high adsorption rate and availability of materials with favorable

properties to perform the process [14]. Many solid materials have been used as

adsorbents such as extracellular biopolymers [15], cellulosic materials [16], zeolites [17],

aluminosilicates [18], nanomaterials [19] and activated carbons [14].

Particularly materials such as iron nanoparticles have been reported to have magnetic

properties, electrostatic charge, size, dispersion and homogeneity, which make them

excellent choices for the adsorption of heavy metals. Likewise, the lignocellulosic materials

enhance its adsorption capacity by the surface modification through loads or ligands that

improve stability of the adsorbate and selectivity, these two alternative adsorbents are

effective and inexpensive for quick removal and recovery of ions metal in sewage effluent.

The main goal of this study was to investigate the removal of Hg+2 from an aqueous

solution using as adsorbent iron nanoparticles supported on fique fiber. Evaluating the

influence on the removal of important factors such as initial concentration of mercury,


solution pH and the iron loading in the adsorbent material. Chemical and physical

adsorption models were used to adjust the experimental data.


Mercury solutions of 150mL and adsorbent material (iron nanoparticles supported on fique

fiber) were arranged in a jacketed glass batch reactor, with continuous agitation (240rpm)

controlled by the motor IKA 260. Each run lasted 30 minutes; all experiments were

performed at 20°C and 551mmHg. The concentration of mercury remnant in the solution

was determined by cold vapor atomic absorption spectrometry (CVAAS) using the injection

method of an aliquot of 1000µL, in a Hitachi z-8000 atomic absorption spectrometer

equipped with hydride generator. The wavelength used for the determination of the analyte

was: Hg 253.7 nm.

Preliminary experiments were performed in order to determine the proper amount of of

adsorbent material to use in the experiments (400, 800, 1000 and 1500 mg). The tested

amount of material was submerged in a 150mL solution of 10 mg.L-1 mercury (II) with an

initial pH = 10, at 20°C and 551mmHg, samples of the solution were taken upon time and

analyzed via cold vapor atomic absorption spectrometry.

A Box- Bhenken design of experiments with response surface (DOE), which used the

maximum and minimum levels of the three factors evaluated in the mercury removal was

implemented, this type of DOE includes a triplicate center point, for a total of 15

experiments. A summary of the experimental condition for the DOE area presented in

Table 5.1.

MiniTab 16 Statistical Software served to identify the contribution of each variable and its

interaction in the removal of mercury through the respective statistical analysis of the data

obtained. A linear regression method as the one described in equation (1) was used to set

the second order polynomial experimental data and to identify relevant terms of the model.

𝑌 = 𝛽0 + ∑ 𝛽𝑖𝑥𝑖 + ∑ 𝛽𝑖𝑖𝑥𝑖𝑖2 + ∑ 𝛽𝑖𝑗𝑥𝑖𝑥𝑗 𝐸𝑞 (1)

Where β0 is the compensatory term; βi is dependent term or the linear effect of factor input

xi; ii is the quadratic effect input factor xi and βij is the effect of interaction between the

linearly linear input factor xi and xj.


Table 5.1. Factors assessed in mercury removal using a adsorbent from Fique and iron

nanoparticles27

Factor

Level

Low Medium High

pH 4 7 10

[Hg]o (ppm) 1 10 14

Fe wt.% 10.9 13.2 14.9

Before the adsorption experiments were started, the solution initial Hg concentration and

pH was measured via vapor atomic absorption spectrometry and a Toledo LE427

pHmeter, respectively. The initial pH of the solution was adjusted with the addition of

different buffers: citrate (pH=4), phosphate (pH=7) and ammoniacal (pH =10). Then the

adsorbent material was added to the solution .

The adsorption capacity of the metal ion in solution was determined for each value of initial

concentration, with experimental data equilibrium concentration and initial concentration,

using the following equation (2):

𝑞𝑒 = (𝐶𝑖− 𝐶𝑒)𝑉

𝑤 𝐸𝑞 (2)

Where qe is the adsorption capacity (mg/g), Ci is the initial concentration of solute

(adsorbate) in solution (mg/L), Ce is the solute concentration in the equilibrium (mg/L), V is

the mercury solution and W is the adsorbent mass (g).

The removal percentage of the mercury was expressed as the equation (3):

𝑅𝑒𝑚𝑜𝑣𝑎𝑙 (%) = 𝐶𝑜 − 𝐶

𝐶0𝑥 100% 𝐸𝑞 (3)


Figure 5.1 shows the results obtained in the evaluation of the adsorbent dosage in Hg

removal; the smallest mass of adsorbent material (400mg) achieved just a 15% mercury

removal. It was found that an increase in the amount of adsorbent material (with pH and

Hg concentration constant) has a positive effect on mercury removal, which agrees with


other studies in which the same trend has been evident removing pollutants from waste

water [20,21], this behavior is explained as a result of greater availability of surface area

and functional groups.

Figure 5.1. Percentage of removal at different loads of adsorbent material (pH=10, initial concentration of mercury = 10ppm and 10.9 wt.% Fe)44

Experiments ran with 800, 1000 and 1500mg of adsorbent material showed approximated

final removal values of 53, 56.7 and 66.5%, respectively. However, when the final Hg

removal obtained for each experiments is plotted as a function of the amount of adsorbent

(Figure 5.2), it shows an apparent saturation point, which is an unexpected behavior not

common for physisorption processes in which the only variable changing is the amount of

adsorbent material, where a more lineal behavior would be expected.

0

10

20

30

40

50

60

70

0 10 20 30 40 50 60

Rem

ova

l (%

)

Time (min)

400 mg 800 mg 1000 mg 1500 mg


Figure 5.2. Final removal percentage of removal at different loads of adsorbent material

(pH=10, initial concentration of mercury = 10 ppm and 10.9 wt.% Fe) 45

Analyzing the results obtained for the 800 and 1500mg experiments, the 1500 mg (using

almost the double of 800mg) shows just a 13% of mercury removal when compare against

the 800 mg experiment; in terms of industrial application would imply a reduction in the

amount of material required and possibly a decrease in costs; under this perspective the

800mg of adsorbent material was the chosen amount to perform the upcoming

experiments.

The first of them is to determine the adsorption capacity of the raw fique fiber and to have

it as baseline experiment, Figure 5.3 shows the typical profile adsorption isotherm with a

final removal value in the order of 24%, below the 53.7% reported for the same amount of

adsorbent material (10.9% Fe on modified fique fiber) under the very same conditions, of

pH, initial Hg concentration, temperature and agitation, implying a positive effect of the

fiber modification and the presence of iron nanoparticle son the fiber surface.


Figure 5.3. Mercury removal using raw fique fiber (pH=10, initial concentration of

mercury =10ppm).46

With the purpose to evaluate the experimental data obtained, two typical physisorption

model were fitted, Langmuir [22] and Freundlich [23], this type of model, if properly

describe the experimental data, could provide information about aspects such as

adsorption mechanism, surface properties and affinity between adsorbate and adsorbent.

Table 5.2. Adsorption isotherms models 28

Model Linealization form

Langmuir 𝑞𝑒 =

𝑞𝑚𝐾𝐿𝐶𝑒

1 + 𝐾𝐿𝐶𝑒 (4)

𝐶𝑒

𝑞𝑒=

1

𝑞𝑚𝑏+

1

𝑞𝑚 𝐶𝑒 (5)

Freundlich 𝑞𝑒 = 𝐾𝑓𝐶𝑒1/𝑛

(6) log 𝑞𝑒 = log 𝐾𝐹 + 1

𝑛 𝑙𝑜𝑔𝐶𝑒 (7)

where qe is the adsorption capacity (mg/g), Ce is the equilibrium concentrations of mercury

(mg/l) in the solution, qm (mg/g) is the amount of adsorption corresponding to complete

monolayer coverage and b (L/mg) is the Langmuir constant related to the energy or net

enthalpy of adsorption. Kf and n are Freundlich constants related to adsorption capacity

and adsorption intensity.

The essential features of the Langmuir isotherm can be expressed in terms of a

dimensionless constant separation factor or equilibrium parameter RL (equation (8)):

𝑅𝐿 = 1

(1 + 𝑏𝐶𝑜) 𝐸𝑞 (8)

The value of RL indicates the adsorption process to be either unfavorable (RL > 1) or linear

(RL = 1) or favorable (0 < RL < 1) or irreversible (RL = 0). The Hg removal data obtained for

the raw fique fiber was fitted to the two proposed model and the results are summarized in

Table 5.3.

0

5

10

15

20

25

30

35

0 10 20 30 40 50 60

% R

emo

val

Time (min)


Table 5.3. Langmuir and Freundlich isotherm models results for the Hg adsorption on raw

fique fiber 29

pH [Hg]0 mg/L

Fe wt.%

Removal (%)

Langmuir Freundlich

qm b RL R2 Kf n R2

1 0 -1 24.4 0.13 123.82 0.0321 0.863 1.167 27.027 0.0026

From the data reported in Table 5.3, it can be interpreted that the predominant mechanism

of mercury adsorption on the raw fique fiber approaches to a physisorption (described by

the fit of experimental data with Langmuir isotherm); from the RL factor can be concluded

that the adsorption process on the raw fique fiber is a feasible operation. The Freundlich

isotherm fitting was extremely poor.

Once the adsorption baseline experiment has been analyzed, a Box – Behnken design of

experiment (DOE) was proposed in order to identify the effect of operating conditions on

the Hg adsorption on the adsorbent material (iron nanoparticles on fique fiber), these

experiments were performed on a random basis to minimize possible systematic errors

that could generated. At the same time, the experimental conditions of each run and the

percentages of removal achieved are described. The whole results of this experiment are

presented in Annex 7; Table 5.4 shows the results of the DOE experiment adjusted to the

Langmuir and the Freundlich isotherms.

Although some of the R2 fitting values for the Freundlich isotherms are relative good

(above 0.90), 12 of the 15 “n” values calculated are negative which does not have any

physical meaning, the 3 remaining “n” values are positive but their R2 fitting values are too

small to considered the isotherm properly fitted. In conclusion, the Freundlich isotherm

does not properly describe the Hg adsorption on the adsorbent material.

Table 5.4. Experimental levels used in the design of experiments Box - Behnken and values obtained for the Langmuir isotherm model and Langergren model of adsorption 30

Run pH [Hg]0

mg/L

Fe

wt.%

Removal

(%)

Langmuir Freundlich

qm b RL R2 Kf N R2

1 0 1 -1 71.73 84.75 -59 -0.001 0.988 107.72 -16.69 0.827

2 -1 0 -1 92.43 72.46 -345 -0.00003 0.998 78.31 125.00 0.006

3 0 -1 1 76.02 10.11 38.04 0.019 0.987 8.60 -3.88 0.036

4 -1 0 1 71.76 80.00 31.25 0.004 0.998 79.14 17.07 0.321

5 1 1 0 67.29 68.03 -1 -0.080 0.910 193.87 -2.58 0.862


6 0 0 0 75.78 62.89 -53 -0.002 0.998 70.76 -42.37 0.385

7 1 0 1 51.44 42.02 1190 0.000 0.988 50.79 -9.22 0.123

8 0 -1 -1 86.32 11.21 223 0.003 0.996 11.45 26.38 0.566

9 1 -1 0 93.14 2.79 -6 -0.139 0.845 5.99 -2.67 0.351

10 0 1 1 74.44 227.27 15 0.004 0.998 249.34 -5.12 0.858

11 -1 1 0 71.73 172.41 -12 -0.005 0.997 205.97 -13.76 0.701

12 0 0 0 71.46 54.95 182 0.001 0.995 69.82 -2.20 0.942

13 1 0 -1 55.41 23.75 -35 -0.005 0.985 41.81 -15.80 0.166

14 0 0 0 71.58 57.80 16 0.008 0.994 41.81 192.31 0.002

15 -1 -1 0 39.09 2.54 -141 -0.013 0.976 4.11 63.69 0.010

In terms of the Langmuir isotherms, most of the R2 fitting values area above 0.90, however

8 of the RL values are negative which does not have any physical meaning. The other R2

values are relative small (below 0.019) meaning a close to irreversible adsorption, not a

very common feature of physisorption type processes.

Under the fact that neither the Langmuir or Freundlich isotherms showed a good fitting for

the experimental data of Hg adsorption on the adsorbent material and that the adsorbent

material is made out of iron nanoparticles supported on modified fique fiber and could be

chemically active, a pseudo-second-order kinetic model as Lagergren equation was

proposed [24], Table 5.5, shows the differential and linearized form.

Table 5.5. Pseudo-second-order kinetic model of adsorption 31

Model (pseudo-second-order) Linealization form

Langergren 𝑑𝑞(𝑡)

𝑑𝑡= 𝑘2[𝑞𝑒 − 𝑞(𝑡)]2 (9)

𝑡

𝑞(𝑡)=

1

𝑘2𝑞𝑒2 +

1

𝑞𝑒 𝑡 (10)

where k2 [g/mg-1min-1] is the rate constant of pseudo-second-order model, qt (mg/g) is the

amount of adsorbed Hg on the adsorbent at time t and qe is the equilibrium sorption uptake

(mg/g). The result of the data fitting from DOE with Lagergren model is summarized in

Table 5.6.


values obtained for the Lagergren Pseudo-second-order kinetic model 32 Run pH [Hg]0 Fe wt.% Removal (%) Lagergren

mg/L qe (mg/g) K2 (g/mg/min) R2

1 0 1 -1 71.73 10.20 0.1396 0.997


2 -1 0 -1 92.43 14.82 0.0448 0.999

3 0 -1 1 76.02 -41.15 0.0009 0.987

4 -1 0 1 71.76 -8.98 0.1079 0.994

5 1 1 0 67.29 2.16 3.2460 0.975

6 0 0 0 75.78 21.19 0.0205 0.999

7 1 0 1 51.44 5.31 0.2397 0.996

8 0 -1 -1 86.32 11.47 26.385 0.566

9 1 -1 0 93.14 0.151 69.809 0.997

10 0 1 1 74.44 -151.52 0.0009 0.997

11 -1 1 0 71.73 22.272 0.0363 0.999

12 0 0 0 71.46 133.33 0.0005 0.999

13 1 0 -1 55.41 3.09 0.6374 0.999

14 0 0 0 71.58 96.1538 0.0009 0.996

15 -1 -1 0 39.09 0.1795 18.6474 0.987

The fitting results obtained for the pseudo-second-order kinetic model were very good, 14

of the 15 experiments shown R2 above 0.987. 12 of the 15 experiment present qe and K2

positive (with physical significance). This result indicates that the process of Hg adsorption

on iron nanoparticles supported on modified fique fiber could be described as a

chemisorption process, which would explain the odd behavior of the final removal of Hg as

a function of adsorbent amount (Figure 5.2).

The equation of statistical adjustment coefficients second order (equation (11)) calculates

the value of the final removal % based on the sample data of Table 5.6 where A:pH, B:

CHgo and C: Fe wt.%.

𝑟𝑒𝑚𝑜𝑣𝑎𝑙 (%) = 488.122 − 18.0308A − 0.360682B − 51.5658C − 0.822002𝐴2

+ 0.0242588𝐵2 + 1.16096𝐶2 − 0.505189AB + 2.51977AC

+ 0.239131BC

The conditions under which the best percentage degradation (93.14%) was achieved was

to: pH=10, mercury initial concentration = 1ppm and iron loading on the adsorbent

material 13.2 wt%. Table 5.7 shows the results of the statistical analysis model from

equation (11), evaluated by ANOVA, this is evidence that pH factor is statistically

significant with a confidence level of 95% (p> 0.05). Additionally, pH interactions with the

Eq

(11)

(11)


other factors (initial concentration of mercury in solution and loading of iron nanoparticles),

also are statistically significant, the efficiency obtained in the mercury removal, it is

concluded that the levels analyzed were adequate.

Table 5.7. Analysis of variance (ANOVA) for qe (mg/g) by MiniTab 16 Statistical Software 33

Source DF Seq SS Adj SS Adj MS F P

Regression 9 2503.63 2503.63 278.18 3.49 0.091

Linear 3 139.29 1305.80 435.27 5.46 0.049

A: pH 1 7.47 1138.40 1138.40 14.28 0.013

B: CHgo 1 9.87 127.2 127.20 1.60 0.262

C: %Fe 1 121.95 41.13 41.13 0.52 0.505

Square 3 251.67 259.69 86.56 1.09 0.435

AA 1 196.54 201.93 201.93 2.53 0.172

BB 1 20.24 17.58 17.58 0.22 0.658

CC 1 34.89 34.89 34.89 0.44 0.538

Interaction 3 2112.66 2112.66 704.22 8.83 0.019

AB 1 774.05 774.05 829.68 10.40 0.023

AC 1 1227.59 1227.59 1227.59 15.39 0.011

BC 1 111.02 111.02 111.02 1.39 0.291

Residual Error 5 398.70 398.70 79.74

Total 14 2902.33

An adjustment highly satisfactory between the calculated data and experimental data is

reflected on the correlation coefficient values of R2 = 86.26% and R2 - adjust = 61.54%.

Figure 5.4 shows how the model is very accurate to predict the removal percentage in the

whole range of the studied variables.


Figure 5.4. Experimental and calculated results of the experimental design for mercury removal. Responses considered removal % 47

In order to determine the appropriate fitting data regression and analysis of variance

(ANOVA), analysis of residual plots that are defined as the difference between the set

values (model) and the observed values (experimental) was performed. As shown in

Figure 5.5a residues, follow a normal distribution, half of data takes positive values (over

50%) and the other half negative values (below 50%), which allows to conclude that there

are no significant deviations of residuals from the normal distribution. Figure 5.5b, 5.5c and

5.5d allow to verify the homocedasticity of the residuals (constant variance) meaning they

are symmetrically distributed and are not interdependent to each other.

0

20

40

60

80

100

0 20 40 60 80 100

Rem

ova

l p

erc

en

tag

e (

ca

lc)

Removal percentage (exp)

100-10

99

90

50

10

1

Residual

Pe

rce

nt

9080706050

10

5

0

-5

-10

Fitted Value

Re

sid

ua

l

1050-5-10

4

3

2

1

0

Residual

Fre

qu

en

cy

151413121110987654321

10

5

0

-5

-10

Observation Order

Re

sid

ua

l



Residual Plots for Removal (%)

a)

b)

b)

b)


Figure 5.5. Residual plots for qe a) Normal probability plot, b) Versus fits, c) Histogram and

d) Versus order 48

In general, it is accepted that adsorption phenomena on lignocellulosic materials (like the

raw fique fiber) is mainly governed by the physisorption mechanism through surface

properties such as the presence of functional groups containing oxygen, proving to be an

important factor in mercury adsorption [27]. Mercury adsorption in this type of surface has

been described in terms of two fundamental driving forces. The first one is related to the

mercury Lewis structures, which could bind to basic groups on the surface of the fique

fiber. The second, is the affinity of the superficial functional groups to ionize when

immersed in aqueous solution, allowing to the oxygen from the functional group to

exchange charges with mercury [28]. However, the pH in which is located the solution is a

factor that affects the ionization of the surface functional groups and disturbing the

adsorption capacity because it directly affects the net balance of charges on the surface of

the adsorbent material.

Models of physisorption isotherms and chemical kinetic models showed in Tables 5.4 and

5.6, allow to analyze that the main mechanisms of Hg on iron nanoparticles supported on

modified fique fiber is mostly chemisorption (probably convolute with an small contribution

from physisorption), several studies have reported important chemical and magnetic

interactions of iron nanoparticle with mercury in adsorption processes, however most of

them are reported for unsupported nanoparticles [25,26], some on supported nanoparticles

[27,28], but none using fique fiber as supporting material.

In terms of the physical adsorption of Hg from aqueous solutions some Langmuir qm

values have been reported: for activated carbon reported qm=10 mg/g [29], activated

carbon of palm oil qm = 52.9 mg/g [30] and peanut hulls qm=109 mg/g [31], however not all

the adsorption variables are comparable.

100-10

99

90

50

10

1

Residual

Pe

rce

nt

9080706050

10

5

0

-5

-10

Fitted Value

Re

sid

ua

l

1050-5-10

4

3

2

1

0

Residual

Fre

qu

en

cy

151413121110987654321

10

5

0

-5

-10

Observation Order

Re

sid

ua

l



Residual Plots for Removal (%)

c)

c)

d)

d)


Figure 5.6 shows that mercury adsorption is a process that depends largely on the pH, the

greater adsorption is achieved at higher pH; it has been reported that increasing the pH

improves the solubility of mercury species and promoting the effective contact between

adsorbate molecules and adsorbent [32]. Hilson et al. [13], and Sreedhar, et al. [33],

stated how the solution pH plays an important role in the adsorbent superficial functional

groups by promoting their ionization, those ionized groups become focal point for

adsorption. Therefore, the pHzpc value of the adsorbent material becomes an important

property in the adsorption capacity; as it was determined in previous works the pHzpc

value of the adsorbent material is 8.23. Subjecting the adsorbent material to a pH below

8.23, the high concentration of hydronium ions (H3O+) in the solution will cause the

material surface to charge positively, thereby hampering ion exchange with the metal ions

Hg+2 and cations Fe+3 present in the nanoparticles.

When the pH of the solution increases above 8.23 the hydronium ion concentration

decreases allowing the ionization the surface of fique fiber with iron nanoparticles

anchored, increasing the adsorption of mercury and even generating exchange between

charges Fe+3 and Hg+2 (chemisorption). In general, the adsorption efficiency of Hg (II)

decreases with lowering pH, effect of pH is demonstrated in Figure 5.6 wherein the

maximum adsorption at pH=10 and for solutions of pH 4 is observed and 5.7 removal

performance was reduced.

Figure 5.6. Contour plot of qe (mg/g) vs. pH and mercury initial concentration 49

[Hg] (ppm)

pH

2015105

10

9

8

7

6

5

4

>

–

–

–

–

–

< 40

40 50

50 60

60 70

70 80

80 90

90

(%)

Removal

Contour Plot of Removal (%) vs pH. [Hg]


Figure 5.7. Contour plot of qe (mg/g) vs. Fe wt% and mercury initial concentration 50

There is a direct relation between adsorption of mercury and the initial concentration of

metal ions present in solution at low concentrations of mercury, the adsorption capacity of

the adsorbent material is low, while increases by increasing the initial concentration, the

above statement consistent with the results obtained in the present investigation shown in

Figure 5.6. Other authors [21,34] have reported the same behavior, which is related to the

fact that initially all the active sites on the surface of the fibers and fiber loaded with iron

nanoparticles were vacant and the concentration gradient of metal ions is relatively high

[35]. The extent of adsorption of ions decreases significantly with increasing contact time

depending on the rate of reduction of vacant surface sites of the adsorbent material.

Conclusions

The effects of the experimental conditions on the removal of Hg on raw and iron supported

on modified fique fiber was studied. A Box-Behnken design of experiments allowed to

determine the individual and the combined interaction of the main factor studied (pH, 𝐶𝐻𝑔0,

and 𝐹𝑒 %𝑤𝑡). A maximum Hg removal of removal of 93.14% was obtained operating at

pH: 10, 𝐶𝐻𝑔0: 1 𝑝𝑝𝑚, and 13.2 %𝐹𝑒 𝑤𝑡. DOE results and the ANOVA analysis allow to

conclude that the main factor in the operating conditions is pH; pH values above 8.23

benefit the removal process. Iron loading on the material adsorbent material was found to

have a positive effect on adsorption.

[Hg] (ppm)

Fe w

t.%

2015105

14,5

14,0

13,5

13,0

12,5

12,0

11,5

11,0

>

–

–

–

–

–

< 40

40 50

50 60

60 70

70 80

80 90

90

(%)

Removal

Contour Plot of Removal (%) vs %Fe. [Hg]


The adjustment of the obtained experimental data to the different chosen model indicates

that pseudo-second order chemical kinetic and Langmuir are the ones that better fit the

experimental data, these were efficiently used to predict the adsorption of mercury on raw

fique fibers and on iron nanoparticles supported on modified fique fiber; these models may

indicate that main mechanism of adsorption on raw fique fiber is physisorption, meanwhile

in the case of the iron nanoparticles supported on modified fique fiber the predominant

mechanism is chemisorption.

According to the results obtained in this research, it was confirmed that fique fiber and iron

nanoparticles present a high potential for removing Hg (II) from synthetic water due to the

presence of hydroxyl and carbonyl groups in the surface of biomasses, which has great

affinity to metal ions.

The results obtained could be applied to remove mercury from waste water using an

organic material loaded with iron nanoparticles. Proved to be a promising solution because

the combination of properties provided by each of the elements of the adsorbent material.

The effects of functional groups on the adsorbent material surface may have a significant

effect on mercury adsorption. Increasing sequestration capacity of Hg may also be

enhanced by chemical and magnetic properties reported for iron nanoparticles.

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Conclusions and recommendations

The principal achievements within this master thesis are:

1) Chemical and physical improvements due to pretreatment and functionalization

were observed in the raw fique, among the enhanced physical characteristics are:

reduced crystal size, homogeneous fique surface by ultrasound pretreatment and

increased surface area. In term of the chemical changes obtained on the treated

fiber is worth to mention, exposure and activation of functional groups, cationization

of the fiber surface with chemically active Na+ cations.

2) The synthesis of composite material made out of modified fique fiber and iron

nanoparticles, was successfully achieved, concluding that functionalized fiber has

better characteristics to exchanges iron species with the impregnating solutions

that the raw fiber; it can be concluded that the cationized sites interact with iron

specie to create well dispersed nanoparticles, that evolved to form aggregates.

Crystallographic analyses show mainly the presence of iron oxide species, along

with some iron zero valent, which haven reported to be chemically active for

oxidation process and is in agreement with Orange II oxidation experiments

performed.

3) The composite material from fique and iron nanoparticles, is a material with great

potential to be carried on an industrial scale, because of the easy synthesis

methodology and the low costs involved in their preparation.

4) Orange II degradation experiment showed the catalyst to be an excellent material

to degrade the azo group in the Orange II molecule and therefore reducing the

color of the contaminated water. In term of mineralization only partial mineralization

was obtained, implying that remaining intermediates such as benzene,

naphthalene, NH4+

, NO-3 and other intermediaries could persists. A simplified

pseudo-first-order kinetic model was proposed and was able to describe 16 of the

degradation conditions with a R2 above 0.9; a very remarkable result for such a

simple model.

Conclusions and recommendation 151

5) From the operating conditions analyzed in the degradation of dye OII, the

synthesized catalyst shows remarkable catalytic activity at low pH, feature that has

not been reported for other catalyst in these type of reaction. It turns this catalyst

into a great choice to treat contaminated effluents with very acidic conditions (pH =

2.5), pH where the best value of degradation percentages were achieved

6) Mercury removal demonstrated very interesting results as the predominant

mechanism was the chemical adsorption, as determined by adjusting a kinetic

model of pseudo-second-order, which makes the removal process more efficient,

this can be attributed the combination of properties of the support and the iron

nanoparticles.

In order to continue this study, are proposed as recommendations:

1) At the time of synthesis of nanoparticles in Chapter 3 the molar ratio 2:1 (BH4ˉ / Fe+3)

were maintained, there are different reports in which the ratio reducing agent / agent

precursor allows for different properties in the characteristics of nanoparticles, so

would be ideal an evaluation on the variation of the relationship to see which the best

condition is. It is also important to explore new alternative synthesis of nanoparticles,

in order to obtain for example nano zero valent iron (nZVI), a type of nanoparticles

with properties that further accelerate the oxidation process.

2) From the treated wastewater it is important to identify the possible intermediaries

produced as a result of mineralization of the dye OII, which would in turn important

information when the challenge of proposing a reaction mechanism arises, this

reaction mechanism will be also of great support in the derivation of a complete

kinetics equation necessary to perform any scaling process and real application.

3) The analysis regarding the removal of mercury opens a new an interesting study,

which is, the removal of Mercury via highly selective chemisorption processes. Among

the recommendations made regarding the removal of mercury, it should be noted that

when using a synthetic water mercury is mainly found in its ionic form (Hg+2), however,

in real waters mercury may not necessary be in this form, creating complexes and

interacting with other materials in the contaminated water.


4) It is appropriate to assess the regeneration of the adsorbent material of Fique fiber

and iron nanoparticles, through the study of the magnetic properties of iron

nanoparticles to improve its economic viability, so its future is not just limited to

laboratory scale but also applicable to industrial scale.

Finally, it is open to continue exploring new alternatives for wastewater treatment base in

the biomaterial synthesized in this thesis, for example photocatalysis and testing the

catalyst with other pollutants molecules and elements (dyes with other structures, other

heavy metals, phenols, hormones and even pesticides).

Wastewater treatment using an iron nanocatalyst supported on Fique fibers 153

Annex

Annex 1

Table 1. Nitrogen adsorption isotherm for raw fique fiber

P/Po Volume

[cc/g] STP

0.01325 0.07197

0.04348 0.10496

0.07503 0.13275

0.10729 0.15346

0.13951 0.16688

0.16927 0.18645

0.20508 0.20301

0.23525 0.21357

0.26831 0.22607

0.29779 0.23757

0.33395 0.25094

3.65E-01 0.26311

3.97E-01 0.27485

4.29E-01 0.28432

4.62E-01 0.29752

4.94E-01 0.31146

5.26E-01 0.32402

5.58E-01 0.33815

5.91E-01 0.34821

6.23E-01 0.36182

6.56E-01 0.3763

6.87E-01 0.3923

7.20E-01 0.41023

7.44E-01 0.42487

8.58E-01 0.49995

8.90E-01 0.52553

9.22E-01 0.55137

9.49E-01 0.58178

9.73E-01 0.64644

9.85E-01 0.68558

9.88E-01 0.71607

9.90E-01 0.73601


Table 2. Nitrogen adsorption isotherm for pretreated fique fiber (M30)

P/Po Volume

[cc/g] STP

0.01901 0.08765

0.04501 0.19796

0.08523 0.28448

0.11752 0.33696

0.14992 0.37174

0.18313 0.39136

0.21503 0.42354

0.2473 0.44594

0.27963 0.45497

0.31124 0.48343

0.34343 0.51236

3.77E-01 0.52075

4.09E-01 0.53072

4.41E-01 0.54034

4.74E-01 0.54668

5.06E-01 0.55426

5.39E-01 0.55997

5.71E-01 0.56748

6.03E-01 0.57578

6.35E-01 0.58425

6.67E-01 0.59483

7.00E-01 0.60247

7.32E-01 0.61032

7.64E-01 0.6169

7.97E-01 0.62624

8.29E-01 0.63983

8.61E-01 0.65467

8.93E-01 0.66947

9.25E-01 0.69289

9.56E-01 0.72392

9.67E-01 0.76199

9.74E-01 0.79767

9.82E-01 0.84129

9.89E-01 0.88087

9.90E-01 0.92201


Table 3. Nitrogen adsorption isotherm pore pretreated fique fiber (M60)

P/Po Volume

[cc/g] STP

0.00382 0.07701

0.00847 0.14001

0.02111 0.22501

0.04369 0.34301

0.0745 0.45001

0.08781 0.52001

0.10868 0.58601

0.15701 0.74001

0.218 0.82901

0.25344 0.87001

0.29591 0.89501

3.42E-01 0.93901

3.75E-01 0.96001

4.08E-01 0.96001

4.45E-01 0.96001

4.84E-01 0.96801

5.21E-01 0.99201

5.71E-01 1.00801

6.31E-01 1.03201

6.63E-01 1.04001

7.03E-01 1.07101

7.45E-01 1.09501

7.79E-01 1.12701

8.12E-01 1.15901

8.56E-01 1.21401

8.90E-01 1.25401

9.20E-01 1.30001

9.40E-01 1.33301

9.49E-01 1.36501

9.60E-01 1.43701

9.78E-01 1.54001

9.89E-01 1.67501

9.96E-01 2.15901


Table 4. Nitrogen adsorption isotherm for pretreated fique fiber (M90)

P/Po Volume

[cc/g] STP

0.00779 0.04701

0.03601 0.16301

0.08609 0.32001

0.12455 0.40001

0.16236 0.47401

0.20117 0.51601

0.23666 0.58001

0.26111 0.60801

0.30965 0.69501

0.34331 0.73701

0.37826 0.77701

4.11E-01 0.79601

4.44E-01 0.80801

4.75E-01 0.83001

5.03E-01 0.83801

5.43E-01 0.84501

5.75E-01 0.85701

6.27E-01 0.86801

6.45E-01 0.88301

6.94E-01 0.90201

7.38E-01 0.91301

7.83E-01 0.94701

8.22E-01 0.96001

8.66E-01 1.00401

8.96E-01 1.05301

9.20E-01 1.09101

9.40E-01 1.13201

9.56E-01 1.15501

9.68E-01 1.22301

9.74E-01 1.26901

9.78E-01 1.33976

9.82E-01 1.43609

9.87E-01 1.53701

9.93E-01 1.79601


Table 5. Nitrogen adsorption isotherm for fuctionalizated fique fiber (MC1)

P/Po Volume

[cc/g] STP

0.01603 0.08012

0.03801 0.17602

0.06002 0.26901

0.08421 0.36003

0.11604 0.46015

0.15167 0.56001

0.19405 0.66403

0.23365 0.72001

0.27815 0.77403

0.30626 0.81201

0.35005 0.83191

0.38495 0.83191

0.43555 0.85475

0.45803 0.86616

0.51425 0.90042

0.53673 0.90042

0.59857 0.92326

0.62667 0.93467

0.68851 0.96893

0.71661 0.98202

0.77845 1.01461

0.82389 1.02602

0.87401 1.06028

0.89651 1.08026

0.94756 1.16304

0.96958 1.24297

0.97722 1.33801

0.98401 1.44405

0.98925 1.59203

0.99206 1.68306

0.99872 1.92301



P/Po Volume

[cc/g] STP

0.02302 0.11601

0.04805 0.22001

0.07201 0.29604

0.09802 0.38403

0.12778 0.47601

0.15776 0.54003

0.19731 0.64601

0.23927 0.71304

0.27401 0.78004

0.31188 0.82901

0.35186 0.87304

0.39058 0.87003

0.44117 0.85803

0.46365 0.86401

0.51425 0.87405

0.53673 0.87803

0.59857 0.89501

0.63229 0.90207

0.68711 0.92897

0.72901 0.94901

0.77845 0.99405

0.82904 1.03744

0.87963 1.09453

0.90212 1.11737

0.93001 1.17446

0.95403 1.23503

0.96705 1.30302

0.97942 1.40506

0.98628 1.50708

0.99075 1.59804

0.99507 1.67703

0.99861 1.77309



P/Po Volume

[cc/g] STP

0.02285 0.20006

0.04601 0.29609

0.07302 0.38436

0.10603 0.49415

0.14604 0.63119

0.18305 0.72422

0.21638 0.78824

0.25408 0.83125

0.30309 0.85126

0.37382 0.88827

0.42443 0.90108

0.45514 0.90527

0.49753 0.92028

0.52565 0.93672

0.58188 0.94859

0.60999 0.96047

0.67185 0.97235

0.69996 0.99017

0.76181 1.02631

0.78993 1.05551

0.86303 1.09114

0.88552 1.12678

0.92911 1.18135

0.95862 1.26038

0.97719 1.33841

0.98229 1.39042

0.98814 1.44043

0.98955 1.46544

0.99943 1.61048


Annex 2

Table 1. Nitrogen adsorption isotherm for 1 day of impregnation

P/Po Volume

[cc/g] STP

0.02901 0.12004

0.05602 0.23007

0.08202 0.32411

0.11603 0.42013

0.15605 0.52016

0.19706 0.60918

0.24607 0.70821

0.29509 0.77423

0.33705 0.81224

0.3892 0.826

0.44131 0.822

0.4872 0.82311

0.52002 0.83395

0.57625 0.86652

0.60437 0.85837

0.65021 0.87193

0.69434 0.89906

0.74422 0.92828

0.78431 0.94246

0.85741 0.98586

0.87991 1.00214

0.91327 1.08352

0.95159 1.22237

0.98392 1.57182

0.98505 1.58047

0.98955 1.66951

0.99092 1.68751

0.99517 1.73152

0.99879 1.82755


Table 2. Nitrogen adsorption isotherm for 2 days of impregnation

P/Po Volume

[cc/g] STP

0.02401 0.12604

0.05502 0.26908

0.08603 0.40012

0.11804 0.50515

0.14904 0.58017

0.18406 0.66421

0.22507 0.74622

0.26108 0.78524

0.30072 0.80724

0.33133 0.83425

0.37945 0.82525

0.42443 0.82645

0.45255 0.84225

0.50315 0.86357

0.52565 0.86071

0.58751 0.91211

0.61561 0.92353

0.67747 0.95782

0.70558 0.95209

0.76744 0.98064

0.78993 1.0033

0.86865 1.08344

0.89114 1.10628

0.93613 1.15235

0.96471 1.22051

0.98392 1.46744

0.98674 1.63949

0.98955 1.65453

0.99236 1.74452

0.99517 1.75453

0.9966 1.76253

0.99732 1.78253

0.99924 1.92758


Table 3. Nitrogen adsorption isotherm for 3 days of impregnation

P/Po Volume

[cc/g] STP

0.01901 0.09101

0.07101 0.29103

0.11207 0.42001

0.15773 0.53202

0.19305 0.61503

0.22756 0.68601

0.27112 0.78504

0.30063 0.82301

0.35685 0.88002

0.42993 0.89001

0.45241 0.88502

0.50862 0.88502

0.53111 0.89001

0.59341 0.89301

0.62152 0.89302

0.66101 0.90001

0.71099 0.91102

0.7733 0.93611

0.79531 0.95212

0.86839 0.99868

0.89088 1.02335

0.94006 1.08364

0.96395 1.24634

0.98152 1.45907

0.98644 1.55447

0.98925 1.60612

0.99066 1.64309

0.99487 1.79435

0.99682 1.87312

0.99851 1.99301

0.99909 2.09201


Annex 3

Figure 1. Wavelength with maximum absorption for the OII dye

Figure 2. Calibration curve of OII at 486nm using UV-Vis spectrophotometry


Annex 4

Table 1. Factors evaluated in the dye degradation of OII using iron supported on fique catalyst 34

Factor

Level

Low Medium High

pH 2.5 3 3.5

[OII]o (M) 2𝑥10−5 1.1𝑥10−4 2𝑥10−4

[H2O2]o (M) 1𝑥10−4 5.05𝑥10−3 1𝑥10−2

Fe wt.% 10.9 13.2 14.9

Table 2. Experiments values of Box - Behnken experimental design, degradation percentage and kap obtained for each experimental conditions 35

Run pH COIIo (M) H2O2 (M) Fe wt.% %Deg

1 0 -1 1 0 5.91

2 0 0 0 0 6.83

3 -1 0 0 1 81.94

4 1 0 0 -1 19.67

5 1 0 0 1 1.22

6 0 1 -1 0 1.28

7 0 1 1 0 0.56

8 -1 0 0 -1 93.23

9 0 -1 -1 0 53.30

10 1 1 0 0 0.23

11 -1 -1 0 0 94.50

12 -1 1 0 0 62.96

13 0 0 0 0 27.98

14 1 -1 0 0 5.43

15 0 0 1 -1 60.19

16 0 0 -1 1 4.31

17 0 0 1 1 3.49

18 0 0 -1 -1 40.31

19 0 -1 0 1 49.05

20 1 0 1 0 4.23

21 0 1 0 1 0.30

22 0 0 0 0 20.08

23 -1 0 -1 0 86.72

24 1 0 -1 0 20.27

25 -1 0 1 0 95.61

26 0 1 0 -1 2.24

27 0 -1 -1 -1 7.28


Figure 1. Data Experiments values of Box - Behnken experimental design, degradation percentage 51

Figure 2. Data Experiments values of Box - Behnken experimental design, degradation

percentage 52


Annex 5

Figure 1. Experimental maximum degradation value of OII degradation


Annex 6

Figure 1. Calibration curve of Fe using FAAS

Table 1. Data obtained for Fe by FASS

Run Abs [Fe] ppm Run Abs [Fe] ppm

1 0.005 0.355 15 0.009 0.740

2 0.006 0.451 16 0.005 0.355

3 0.012 1.028 17 0.005 0.355

4 0.002 0.067 18 0.007 0.548

5 0.006 0.451 19 0.013 1.124

6 0.005 0.355 20 0.005 0.355

7 0.004 0.259 21 0.006 0.451

8 0.029 2.661 22 0.009 0.740

9 0.006 0.451 23 0.024 2.181

10 0.005 0.355 24 0.005 0.355

11 0.022 1.988 25 0.029 2.661

12 0.026 2.373 26 0.005 0.355

13 0.006 0.451 27 0.004 0.259

14 0.006 0.451 Average 0.00985 0.822


Annex 7

Table 1. Factors assessed in mercury removal using a adsorbent from Fique and iron

nanoparticles36

Factor

Level

Low Medium High

pH 4 7 10

[Hg]o (ppm) 1 10 14

Fe wt.% 10.9 13.2 14.9

Table 2. Experimental levels used in the design of experiments Box - Behnken and values obtained for the Langmuir isotherm model and Langergren model of adsorption 37.

Run pH [Hg]0 mg/L

Fe wt.%

Removal (%)

1 0 1 -1 71.73

2 -1 0 -1 92.43

3 0 -1 1 76.02

4 -1 0 1 71.76

5 1 1 0 67.29

6 0 0 0 75.78

7 1 0 1 51.44

8 0 -1 -1 86.32

9 1 -1 0 93.14

10 0 1 1 74.44

11 -1 1 0 71.73

12 0 0 0 71.46

13 1 0 -1 55.41

14 0 0 0 71.58

15 -1 -1 0 39.09


Figure 1. Data Experiments values of Box - Behnken experimental design, removal percentage 53

Figure 2. Data Experiments values of Box - Behnken experimental design, removal percentage 54

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