Hydrothermal Synthesis of CuO Nanoparticles- Study on Effects of Operational Conditions on Yield, Purity, And Size of the Nanoparticles

Published: February 16, 2011

r 2011 American Chemical Society 3540 dx.doi.org/10.1021/ie1017089 | Ind. Eng. Chem. Res. 2011, 50, 35403554

ARTICLE

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Hydrothermal Synthesis of CuO Nanoparticles: Study on Effects ofOperational Conditions on Yield, Purity, and Size of the NanoparticlesM. Outokesh, M. Hosseinpour, S. J. Ahmadi,, T. Mousavand,*, S. Sadjadi, and W. Soltanian

School of Energy Engineering, Sharif University of Technology, Azadi Ave., P.O. Box 113658639, Tehran, IranDepartment of Mechanical Engineering, McGill University, 817 Sherbrooke Street, West Montreal, QC H3A 2K6, Canada

ABSTRACT:Hydrothermal synthesis of CuO nanoparticles under near-critical and supercritical conditions was investigated fromtwo dierent standpoints in the current study. The rst standpoint was optimization of yield, purity, and size of thenanoparticles that were optimized at T = 500 C, time = 2 h, [Cu(NO3)2] = 0.1 mol dm-3, and pH 3. This was achieved byundertaking an orthogonal experiment design methodology and performing dierent instrumental analyses, such as X-raydiractometry, inductively coupled plasma spectrometry, and transmission electron microscopy, along with treatment of the databy analysis of variance (ANOVA). The second goal of the study was elucidation of the mechanisms of eects of operationalconditions (e.g., temperature) on the above-mentioned target parameters, through application of the appropriate mechanisms offormation of nanoparticles. Nanoparticles are suggested to form initially in the liquid phase as Cu(OH)2, which are later transformedto Cu2(OH)3NO3, through which CuO product is obtained. Decomposition of nitric acid also plays role in this mechanism.Fabricated nanoparticles are eective catalysts for the synthesis of benzoheterocycle compounds in the pharmaceutical industries.

1. INTRODUCTION

Aggregations of atoms or molecules that have at least one oftheir dimensions in the nano size scale (i.e., between 1 nm and100 nm) indicate properties that are fundamentally dierentfrom the properties of the individual atoms or bulk matter. Ingeneral, it is the preparation method of these nanomaterials(particles, bers, or coatings) that determines their principalcharacteristics, such as size, morphology, and surface, which, inturn, are of high importance in the subsequent applications.1,2

As for the special case of inorganic nanoparticles, so far,numerousmethods have been developed, including (among others)solid-state reactions, sol-gel method, coprecipitation, and hy-drothermal techniques. The rst three methods, although usedwidely, suer from some major shortcomings. Solid-state reac-tions are generally associated with poor composition and mor-phology control. Sol-gel methods allow excellent control ofcomposition and morphology, but its process is costly. Addi-tional calcination and milling steps, which are required in thecoprecipitation method, make it less desirable than the single-step synthesis processes.3

Among dierent methods of preparation of metal oxide nano-particles, supercritical water (SCW) synthesis is unique, because,in this method, the size, morphology, and crystal structure of thenanoparticles are adjustable. SCW oers a relatively simple routethat is inherently scalable, and, because no organic solvents areused, environmentally more benign than the other synthesispathways. The most important advantages of SCW over theconventional hydrothermal method are these: faster kinetics,smaller particle size, and tuning ability of the process that is aresult of the drastic change of physical properties of water in thevicinity of its critical point. So far, the SCW method has beensuccessfully used for the synthesis of many signicant inorganicnanoparticles (see Table 1).

One of the most important metal oxides, from the standpointof catalytic usage, is copper(II) oxide (CuO).CuO is an oxidation-reduction catalyst whose application in organic chemistry datesback to the 19th century. In its nano form, CuO has found abroader range of application in high-critical-temperature (high-Tc) superconductors,

5 gas sensors,6 catalysts for the water-gasshift reaction,7 steam reforming,8 and CO oxidation of auto-mobile exhaust gases.9

Recently, our research group has succeeded in the synthesis oftetrahydrobenzofurans and benzoheterocycle compounds usinga CuO nanocatalyst.10,11 These organic compounds are impor-tant intermediates in the preparation of a wide range of syntheticderivatives with diverse biological and pharmaceutical applica-tions.12-15 For instance, 1,4-benzothiazin-3(4H)-ones are anti-hypertensive drugs, calcium antagonists, and highly potent inhibi-tors of low-density lipoprotein (LDL) oxidation.16

To date, several techniques have been used for the fabricationof CuO nanoparticles. These methods include the metal-organic chemical vapor deposition (MOCVD) template method,17

the wet-chemistry route,18 sonochemical preparation,19 alkoxide-based preparation,20 and solid-state reaction in the presence of asurfactant.21 Nevertheless, a supercritical hydrothermal method hasnever been used for this purpose. If conducted under an optimalcondition, SCWproduces a nanometric product with a high reac-tion yield. However, what exactly does the term optimal meanin this context? To answer this question, we must go through moredetails in the next paragraph.

Received: August 12, 2010Accepted: January 5, 2011Revised: December 1, 2010

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3541 dx.doi.org/10.1021/ie1017089 |Ind. Eng. Chem. Res. 2011, 50, 35403554

Industrial & Engineering Chemistry Research ARTICLE

There are three target parametersyield of the reaction,size of the nanoparticles, and purity of the productsthatmust be optimized in the SCWprocess, as the functions of at leastfour controlling factors, namely, temperature, concentrationof copper nitrate solution, residence time, and eventuallypH. Fortunately, to solve such a dicult multivariable problem,adequate mathematical tools are now available. We made use ofthe Taguchi orthogonal experiment design method, which hasproven its capacity in solving many similar problems.22-25 Inaddition, to make the results of the Taguchi methodmore robust,we fortied it with a strong statistical tool, namely, analysis ofvariance (ANOVA). Finally, some complementary experimentswere carried out to verify the outcomes of the Taguchi-ANOVAanalysis.

The current study has three new features. It is the rst attemptat using SCW for the synthesis of CuO as one themost signicantnanometal oxides. But, more importantly, it takes a new approachfor optimization (i.e, Taguchi-ANOVA analysis) that has beenrarely used in supercritical water technology. Besides optimiza-tion, the current study also aimed at revealing the mechanisms ofthe eects of the controlling factors (e.g., temperature) on theabove-mentioned target parameters. This goal has been achievedthrough investigation of the mechanisms of formation of theCuO nanoparticles in SCW. The suggested mechanisms are pri-marily based on the works of the previous researchers; however,because of the particular feature of the CuO synthesis, the authorshad to take some new standpoints and suggest a series of newreactions that have not been proposed so far. Also, this work isprobably the rst attempt in applying elevated temperatures inthe range of 500 C for the SCW synthesis of nanoparticles.

2. EXPERIMENTAL METHODS

2.1. Synthesis of Nanoparticles. Copper(II) nitrate trihy-drate (Merck AG, Fur synthesis) was used as the raw material forthe synthesis of CuO nanoparticles. Hydrothermal synthesis wascarried out in a stainless steel batch reactor (type 316 L), espe-cially designed to endure a working pressure and temperature of610 atm and 550 C, respectively. The capacity of the reactor was200 cm3; however, to maintain an adequate safety margin, it wasalways loaded to only one-third of its volume.In the synthesis procedure, concentration of Cu(NO3)2 solu-

tion varied from 0.1 mol dm-3 to 0.5 mol dm-3; the temperatureranged from 350 C to 500 C, and the residence time was 1-3 h. The initial pH of the solution was adjusted in the range of3-3.75 by precise addition of NaOH or HNO3 solutions.After removing from furnace, the reaction vessel was quenched

by cold water and produced nanoparticles were separated fromthe solution using a high-speed centrifuge. Afterward, super-natant was sent for copper analysis by inductively coupled plasma(ICP, Varian 150AX turbo) to result in the yield of reaction; andthe obtained nanoparticles were three-fold washed/centrifugedwith distilled water and dried under ambient conditions.2.2. Characterization. The synthesized nanoparticles were

characterized by transmission electron microscopy (TEM) (LEOModel 912AB), X-ray diffractometry (XRD) (Philips Model PW1800), thermogravimetric analysis (TGA) (Model SATA 1500,Scientific Rheometric), and measurement of the specific surfacearea via nitrogen adsorption testing (i.e., BET, NovaModel 2000e).

3. RESULTS AND DISCUSSION

3.1. Optimization of the Synthesis Process. Optimizationof the synthesis process was the prime goal of the current study,and therefore it is discussed first in this section. The outcomes ofthis section are specific operational conditions in which the threetarget parameters of the study (i.e., purity, yield, and size of thenanoparticles) attain their optimum values. The section starts bydescribing the procedure of designing the experimental array,which is followed by analysis of the responses of the system usingTaguchi-ANOVA analysis. Complementary experiments thenwill be discussed that, together with the foregoing statisticalmethods, specify the optimum reaction conditions.3.1.1. Setting of the Experiment DesignMatrix. The extensive

studies of the previous researchers had revealed4,26,27 that, undersupercritical conditions, the controlling factors whose variations

Table 1. Compounds Produced in Nanoparticles by Hydro-thermal Synthesis in Supercritical Water (SCW)4

Particle Dimension

product range mean size authors

AlOOH 80-1000 Adschiri et al.,Hakuta et al.

R-Fe2O3 50 Adschiri et al.Fe3O4 50 Adschiri et al.

Co3O4 100 Adschiri et al.

NiO 200 Adschiri et al.

ZrO2(cubic) 10 Adschiri et al.

TiO2 10-1000 20 Adschiri et al.TiO2(anatase) 20 Adschiri et al.

CeO2 20-300 18 Hakuta et al.BaO 3 6Fe2O3 50-1000 100 Hakuta et al.Al5(YTb)3O12 20-600 Hakuta et al.LiCoO2 40-400 Hakuta et al.ZrO 10-1000 Adschiri et al.AlO(OH) 20-200 Adschiri et al.Ce1-xZrxO2 3-5, 4-7 Cabanas et al.CeO2 20-200 Adschiri et al.Fe3O4 Fe 40-92 Cabanas et al.CoFe2O4 39-72 Cabanas et al.NiFe2O4 28-43 Cabanas et al.NixCo1-xFe2O4 23-42 Cabanas et al.ZnFe2O4 47-105 Cabanas et al.AlOOH 13-16 Li et al.R-Fe2O3 30-60 30-40 Cote et al.

25-170Co3O4 30-60 30-40

20-30 Cote et al.CoFe2O4 20 Cote et al.

ZnO 120-320 Viswanathan et al.39-251

YAG:Tb 14-152 Hakuta et al.ZrO2 3-5 Galkin et al.TiO2 7-9 Galkin et al.1% Pd/ZrO2 3-5 Galkin et al.1% Pd/TiO2 7-9 Galkin et al.R-Fe2O3, Fe3O4 14 -25 Takami et al.AlOOH 45-500 Mousavand et al.La2CuO4 70-120 Galkin el al.

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significantly influence the characteristic of the nanoparticles are:temperature, residence time, initial Cu(NO3)2 concentra-tion, and, eventually, its pH. Ranges of variations of thesefactors in the current study were restricted by certain physico-chemical limitations. For instance, application of excessively lowtemperatures (i.e., < 300 C) led to a rather low reaction yield.On the other hand, temperatures that were too high (Tg 500 C)gave rise to an excessive steam pressure, the handling of whichdemanded special safety precautions. For pH, limitations were ofanother type. Using a pH value of >4 led to an immediate pre-cipitation of Cu2 ions under ambient conditions and priorcharging of the solution into the reactor. Conversely, a pH valueof



CuO was found to be a qualitative mean for evaluation of itspurity (see Table 3): the blacker the color of the sample, thegreater its purity level.To estimate the size of the nanoparticles, two dierent

methods were exploited. In the rst (or direct) method, TEMimages of the CuO nanoparticles were examined. The secondmethod was based on the well-known Scherrer formula:28

d kFWHM cos max

3

where k denotes the shape factor, is the X-ray wavelength,FWHM depicts the line broadening at half of the maximumintensity, and designates the Bragg angle. In the above formula,

d is the mean size of the crystalline domains, which may be equalto the size of the grains. In analysis of the XRD data, we used pro-duct (FWHM cos max) as our target parameter or, in other words,as a measure of the size of the nanoparticles (see Figure 1).According to Figure (1), in some cases, trend of dependency of

target parameters such as Y on the controlling factors (e.g., time)was monotonically ascending or descending. In other instances,this correlation was not direct, which revealed the presence ofcertain interactions between the eects of controlling factors. Todetermine the extent of this factor coupling, the Interactiontool box of Qualitec-4 software was used. The results showedextensive interaction between temperature and residence timeand also concentration and pH in the case of Y as the targetparameter (see Table 4). Similar statements can be made aboutinteractions in the cases of Irel and the size factor.The mechanisms of interactions of some of the controlling

factors of Table 4 are given in the next sections. However, gen-erally, interpretation of these data is rather formidable, and it is

Table 3. Operational Conditions and Responses of the Systema

sample temperature (C) time (h) concentration (mol dm-3) pH Irel Y (%) (fwhm) cos max color

A1 350 1 0.1 3 0.11 11.48 0.198 black

A2 350 2 0.3 3.5 1.71 58.87 0.149 gray

A3 350 3 0.5 3.75 11.72 92.53 0.179 olive green

A4 400 1 0.3 3.75 4.86 33.99 0.194 greenish blue

A5 400 2 0.5 3 0.5 44.67 0.186 black

A6 400 3 0.1 3.5 0.49 78.57 0.198 black

A7 450 1 0.5 3.5 2.11 30.42 0.209 jade green

A8 450 2 0.1 3.75 0.25 48.22 0.226 black

A9 450 3 0.3 3 0.73 51.56 0.189 black

A10 400 3 0.5 3.57 0.96 96.5

A11 400 3 0.5 3 68.3

A12 450 2 0.5 3.75 59.1

A13 400 3 0.1 3 0.08 0.236

A14 450 2 0.1 3 0.024 0.286

A15 450 3 0.1 3



better to examine the signicance of the eect of each control-ling factor on the total response of the target parameters throughanalysis of variance (ANOVA).The results of ANOVA calculations are illustrated in Figure 3.

When these results are seen in a combined framework with theresponses of the system in Figure 1 and Table 3, the followingoutcomes can be deduced: Higher temperature (450 C or more) is preferred, in termsof reducing the size of the nanoparticles and lowering theimpurity level of the product, although its inuence on yieldpercentage is slightly negative.

Longer residence time is advantageous for enhancing theyield percentage and, to a lesser extent, removing the Cu2-(OH)3NO3 impurity, although it has a detrimental impacton the size of the nanoparticles.

Concentration and pH both take their optimum valueswhen they are minimized (i.e., pH 3 and [Cu2] 0.1mol dm-3, respectively). This is mainly due to their adversesevere eects on the purity of the product.

3.1.3. Complementary Experiments and Optimum Opera-tional Conditions. To verify the aforementioned outcomes aboutoptimal reaction conditions, a set of complementary experimentswas carried out. Samples A10-A21 in Table 3 represent the re-sults of these experiments. Note that a higher temperature (500 C)was also examined in the complementary experiments.To make the appraisal of these results more convenient, an

auxiliary table (Table 5) was devised. A comparing couple hasbeen inserted in each cell of Table 5. When a couple is selectedfrom this table, the corresponding data can be found in Table 3.One very signicant result that is deduced from Tables 3 and 5

is an improvement in the values of all target parameters at atemperature of 500 C. In this case, higher temperature couldcompensate for the negative eects of the lower pH, and

shorter residence time. By considering this result, and thethree bulleted outcomes of the last section, the optimum opera-tional conditions were determined to be the following: tempera-ture = 500 C, residence time = 2 h, concentration = 0.1 moldm-3, and pH = 3.3.2. Mechanisms of the Effect of Controlling Factors

(Operational Conditions) on the Target Parameters. In anattempt to determine the mechanisms of the effects of control-ling factors (e.g., temperature) on the target parameters, thefirst step was discovering the mechanism of formation of thenanoparticles. For this purpose, first, different formation me-chanisms reported by the previous researchers were examined.Afterward, based on the results of the current study, amongthose mechanisms, the two most appropriate reaction sets wereselected. These selected sets will be presented at the end ofsection 3.2.1. Then, in sections 3.2.2-3.2.4. the suggestedmechanisms will be applied on different observed phenomena,to examine the effects of different controlling factors on everytarget parameter.3.2.1. FormationMechanism. The comprehensive study of the

previous researchers (see Table 1) revealed that, under supercriticalconditions, the following three-step mechanism is involved in theformation of oxide nanoparticles from corresponding transition-metal salts:(1) The ion product of water (Kw) considerably increases,

giving rise to higher concentrations of [OH-] ions andmore rapid hydrolysis of the metal cations as a result (seereactions 4 and 5).

(2) The dielectric constant of water declines and, accordingly,its solvent power for dissolving ionic materials. Reducingthe solvent power of water elevates the tendency of thehydroxide molecules (in reaction 5) for immediate pre-cipitation, which, in turn, leads to the creation of a larger

Figure 3. Signicance of the contribution of each controlling factors in the total response of the system calculated by ANOVA analysis: (a) Irel, (b) Y,and (c) FWHM cos max.

Table 5. Comparing Couples for Elaborating on the Eects of Experimental Conditions on Irel, Yield (Y), and FWHM cos max forSeeing the Conditions and Responses of Each Couple Shown in Parenthesesa

temperature (C) time (h) concentration (mol dm-3) initial pH

Irel (A13-A15) (A14-A15) (A13-A9) (A13-A6)(A14-A16) (A17-A18) (A16-A19) (A14-A8)

(A16-A18)yield, Y (%) (A3-A10) (A5-A11) (A8-A12) (A10-A11)FWHM cos max (A13-A15) (A14-A15) (A13-A9) (A6-A13)

(A14-A16) (A17-A18) (A16-A19) (A8-A14)(A18-A20) (A8-A21) (A16-A18)

aRefer to Table 2 for an explanation of terms.

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number of the precipitate nuclei and, thus, the formationof the nanosized particles.

(3) Because of the high-temperature conditions, unstabletransition-metal hydroxides are converted to their corre-sponding oxides (see reaction 6).

Water dissociation : H2O f HOH- 4

Hydrolysis : Cu22OH-fCuOH2 5

Dehydration : CuOH2fCuOH2O 6As was mentioned in section 3.1.2, the results of the XRD

analyses indicated that, besides copper hydroxynitrate (Cu2-(OH)3NO3), no other impurity existed in the CuO samples(see Figure 4). Therefore, either some of the initially formedCu(OH)2 or CuO must be converted to Cu2(OH)3NO3 viareactions 7-9, or Cu2(OH)3NO3 should be directly producedfrom Cu(NO3)2 via the reaction reported by Lee et al.

29

(reaction 10).

2CuOH2HNO3 aqfCu2OH3NO3H2O 7

2CuOH2HNO3 gfCu2OH3NO3H2Og 8

HNO3 gH2Og2CuOfCu2OH3NO3 9

2CuNO32 aq3OH-aqfCu2OH3NO3NO3-aq10

All of the above reactions except reaction 10 require liquid orgaseous nitric acid. This acid is either free nitric acid that existsin the reactor from the beginning, or it is coproduced with

Cu(OH)2, as a result of the hydrolysis reactions described byreactions 4 and 5.

NO3-OHfHNO3 11

This reaction principally occurs in the vicinity of the criticalpoint, where water loses its large dielectric constant.The nal product of the hydrothermal synthesis is copper(II)

oxide; therefore, both Cu(OH)2 and Cu2(OH)3NO3 musteventually decompose to CuO through reaction 6 or via thefollowing reaction:

Cu2OH3NO3THNO3 gH2Og2CuO 12Nitric acid that is produced via reactions 11 and 12 remains in theuid phase, along with free nitric acid that exists from thebeginning. At elevated temperatures, these acids, which are prin-cipally in the form of a mixture of H2O, O2, and NOx gases, mayfurther decompose to nitrogen.

HNO3fH2ONO2O2 12 N2 13

When the reactor is quenched, the undecomposed nitrous gasesare partially dissolved in water to form a dilute HNO3 solution.The formed acid then can dissolve a fraction of CuO nanopar-ticles, hence reducing the yield of the CuO synthesis.By combining all of the above-mentioned facts, and the dis-

cussed reactions (reactions 4-12), the two following formationmechanisms can be proposed: The rst mechanism assumes that, after the formation ofcopper hydroxide (Cu(OH)2) via reactions 4 and 5, a frac-tion of it is converted to CuO via reaction 6, but the mainpart of the Cu(OH)2 and a part of the produced CuO aretransformed to Cu2(OH)3NO3 through solid-gas reac-tions (reactions 8 and 9). Since these reactions occurbetween the solid and uid phases, they proceed only whenthe entire water content of the reactor is evaporated (i.e., atT > TC), or, in other words, after the initial 40-60 min ofthe heating period have elapsed.

The second mechanism suggests a somewhat dierent path-way, in which Cu2(OH)3NO3 is produced in the hot liquidphase from Cu(OH)2 (reaction 7), or from Cu(NO3)2(reaction 10). At the same time, some Cu(OH)2 is directlyconverted to CuO, according to the Adschirris dehydrationreaction (reaction 6). Accepting this mechanism impliesthat Cu2(OH)3NO3 is formed within the rst 40-60min ofthe heating period, when liquid still exists.

These mechanisms hereinafter are referred as the bulletedmechanisms. Figure 5 shows an illustration of them.Note that the bulleted mechanisms are a combination-

modication of the works of Adschirri and Lee, which were devisedto address the disappearance of the Cu(OH)2 peak in the XRDpatterns of our samples. The rationale behind the suggestion ofthesemechanisms is this: Either the formation of Cu2(OH)3NO3 inthe liquid phase is slow, which in that case Cu2(OH)3NO3 will belargely produced by the solid-gas reactions (the rst mechan-ism), or it is rapid and can be completed in a short period, whichmeans that it would occur before the liquid phase is totallyevaporated (the second mechanism).There is evidence that supports the second bulleted mechan-

ism: even after one hour of heating, some amount of the Cu2-(OH)3NO3 was detected in CuO samples (see Table 3). Since,

Figure 4. Typical XRD patterns of the produced CuO product contain-ing impurties.



during most of the course of this period, the temperature is belowthe critical point, the secondmechanismmust be involved in the for-mation of this impurity.Nonetheless, in the next subsections, wewillencounter somephenomena that further support therstmechanism.Note that the two bulleted mechanisms are not competing

mechanisms, i.e., they can occur in parallel in the same reactor,and along with others.

Here, it is worthwhile to point out that both bulleted mechan-isms include reaction 13, which is highly important in the inter-pretation of the variation of yield Y in section 3.2.3.3.2.2. Purity of the Product. Figures 1 and 3 indicate that the

impurity content of the CuO product is highly dependent on thepH of Cu(NO3)2 solution. This phenomenon can be attributedto the further progress of reactions 5 and 10 at higher pHs. Note

Figure 5. Schematic illustration of the bulleted mechanism, exhibiting major reactions.

Table 6. Elaboration of the Eect of Temperature on Impurity Content (Irel)

sample concentration (mol dm-3) time (h) temperature (C) relative mass of product color initial pH Irel nal pH

A3 0.5 3 350 1 greenish blue 3.75 11.7 3.08

A10 0.5 3 400 0.64 gray 3.75 0.96 2.46

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that both of the bulleted mechanisms are based on these twoprincipal reactions.Figure 1, andTables 3 and 5, indicate that the impurity content

of CuO is a descending function of temperature. This behaviorwas anticipated, because Cu2(OH)3NO3 is an unstable com-pound that appreciably decomposes at high temperatures (seereaction 12).48 To further verify this argument, an additionalexperiment was performed in which two identical volumes ofCu(NO3)2 solution were heated up to 350 and 400 C, and theirresults are summarized in Table 6. According to Table 6, byincreasing the temperature, the amount of the produced powderdecreased and, at the same time, the nal pH was lowered. Par-allel with these phenomena, Irel was reduced by a factor of >11.When these ndings are considered together, it turns out thatone must accept that, at higher temperatures, the heavier Cu2-(OH)3NO3 decomposes to the lighter CuO, and at the sametime, the pH of the solution decreases, as a result of reaction 12occurring.The eect of residence time on the impurity contentmay not

be readily observed in Figure 1, since, because of the strong inter-action between residence time and temperature (see Table 4),the eect of the former on Irel depends on the magnitude of thelatter. The previous discussions suggests that (i) if the tempera-ture is adequately high, a prolonged heating period leads todecomposition of the Cu2(OH)3NO3 impurity, and (ii) at lowertemperatures (e.g., 350 C), wherein Cu2(OH)3NO3 is stable,the impurity content of the product increases as the heatingperiod elapses through the rst bulleted mechanism. For both ofthese speculations, there is some supporting evidence. The rstspeculation is supported by Figure 6, which indicates the XRDpatterns of two similar samples synthesized at 500 C, but atdierent time intervals. Obviously, the impurity peak disap-peared during the longer period. Evidence for the secondspeculation is found by comparing samples A1-A3 of Table 3.While, according to the published literature,29-32 Cu2(OH)3-

NO3 in dried form decomposes within a few minutes at 300 C,the data inTable 3 indicate that, in the closed space of a supercritical

reactor, this material is stable, even after three hours. This phenom-enon probably results from the reversible nature of reaction 12,which, by virtue of highwater vapor pressure, keeps some amount ofthe Cu2(OH)3NO3 at equilibrium.

Concentration has an adverse eect on the purity (seeFigure 1). This eect can be interpreted by considering any ofthe bulletedmechanisms. In either case, by increasing the [Cu2]concentration, the extent of Cu2(OH)3NO3 production is increased.However, for the Cu2(OH)3NO3-consuming reaction (i.e., reac-tion 12), the concentration of the Cu(NO3)2 solution is im-material. As a result, the net rate of production of Cu2(OH)3-NO3that is, subtraction of its production and consumptionrateswould favor the production of a larger amount of this ma-terial at higher Cu(NO3)2 concentration.3.2.3. Yield of Reaction. Figures 1 and 3 indicate that, besides

temperature, the other controlling factors have a positive effecton the yield of reaction. Elaborating of the pH effect is quitestraightforward, because the higher the pH, the greater the rate ofCu2 precipitation by reactions 5 or 10 will be, and the larger theyield will be, as a consequence.The response of yield (Y) to temperature in Figure 1 is slightly

negative. This unexpected behavior could result from increasingthe partial pressure of water at higher temperature, and the greaterprogress of reaction 12 to the right-hand side under these con-ditions. The resulting CuO and Cu(OH)2 are more readilysoluble in dilute nitric acid that is produced via reaction 12 andcondensed in the reactor after its quenching. Note that Cu2-(OH)3NO3 is insoluble in water, and a larger amount of thismaterial corresponds to a greater yield of synthesis.Table 3 shows that, when the residence time increases from 1 h

to 2 h and then 3 h, the yield increases by a factor of 2-9. Appar-ently, the chemical equilibration time in the synthesis systemoften exceeds 2 h, because, after this period, the yield still changes.But what special reaction requires such a long time to attain its equi-librium?As stated earlier, the reactor temperature after40-60min

Figure 6. XRD spectra of samples A17 and A18 heated at 500 C for 1and 2 h, respectively.

Table 7. List of Metal Oxide Nanoparticles That WereSynthesized by Our Research Group Using the SCW Method

product precursor

instrumental

analysis

average

size (nm)a

ZnO nitrate XRD, TEM 19

NiO nitrate XRD, TEM 76

Cr2O3 nitrate XRD, TEM 35

BaO Ba(OH)2 nitrate XRD, TEM, TGA 33SrO nitrate XRD, TEM 79

Y2O3 nitrate XRD, TEM 17

PdO Pd nitrate XRD, TEM-TGA 18La2O3 LaOOH nitrate XRD, TEM, TGA 27Fe2O3 nitrate XRD, TEM 14

Co3O4, CoO nitrate XRD, TEM-TGA 39

CeO2 Ce(OH)3 nitrate XRD, TEM, TGA 17CuO-Al2O3 nitrate XRD, TEM-XRF 25ZrO2 nitrate XRD, TEM 47

MnO2-ZrO2 nitrate XRD, TEM-XRF, IR 52SiO2 chloride XRD, TEM 32

Fe2O3-Al2O3 nitrate XRD, TEM, XRF 48Ag AgO Ag2O nitrate XRD, TEM, TGA 12MnO2 nitrate XRD, TEM 57

aCalculated using CLEMEX software.



exceeds the critical point, so that after this period, only solid-gasreactions or gas can occur. Among the previously describedbulleted mechanisms, the rst onewhere Cu2(OH)3NO3 isproduced by prolonged solid-gas reactions described by reac-tions 8 and 9provides a better explanation for this phenom-enon. In addition, production via prolonged solid-gas reactionsdescribed by reactions 8 and 9 provides a better explanation forthis phenomenon. In addition, by elapsing time, gaseous nitricacid gradually but irreversibly decomposes to N2, H2O, and O2,or, in other words, a set of neutral gases that are unable to dissolvenanoparticles on the time of condensation.Here, an important question may arise as: During the heat-up

time (t < 60 min), is not it possible for temperature to locallyexceed its equilibrium value (Te), while the average temperaturehas not yet attained the Te temperature? In other words, isthere not any possibility at t < 60 min for the formation of hotspots on the inner surface of the reactors, where copper nitratesolution can locally decompose to the nal nanoparticles? In therst row of Table 3, there is evidence that supports the emer-gence of such hot spots; for a sample that was heated up to350 C for1 h, 11% of the solution reacted and decomposed tothe nal solid product, implying that the formation of thenanoparticle probably occurs before 45 min via the aforemen-tioned hot-spot mechanism.In the absence of any online sensor in the reactor, the above

question cannot be fully addressed; however, there are severalreasons that refute the possible occurrence of such phenomenon.(1) As mentioned previously, no visible eect of formation of

nanoparticles was observed before 45 min. On the otherhand, the aforementioned sample, which was heated for 1h (at 350 C), contained an appreciable amount of solid;but that solid product was quite impure. This means that,after 1 h, the formation of nanoparticles was not com-pleted andwas in the early stage of its process (also see thethird reason below).

(2) As discussed in the Appendix, the mass of water was 1/157of the total mass of the reactor, and only 6% of injectedenergy into the reactor was consumed for heating andphase transformation of the water. In addition, heat waschiey transferred in the radial direction, where there was,in addition, a cylindrical symmetry (see Figure A1 in theAppendix). With such a bulky reactor, and high symme-try, it is physically unlikely to have large hot spots (orzones) in the reactor wall. In fact, what is more probable isto have cold spots (or regions) in the corners of reactor oron its bottom. While the large hot zone cannot formduring the heating, there is still a possibility for the for-mation of ne or micronized spots on the reactor surface,which also can act as the host for bubble formation andphase transformation.

(3) As Figure 3 shows, the most inuential factor on the yieldof formation of nanoparticles is time and not temperature.The mechanism of increasing yield with time was dis-cussed in the previous paragraphs; nevertheless, here, it isworthwhile to mention that, even if some nanoparticlesform before 45min, on the time of quenching of the reactor,they would readily be dissolved in the nitric acid solutionthat was formed via hydrolysis reaction (reaction 11). Inother words, to have a large amount of pure CuO nano-particles, it is necessary to keep the system at high tem-perature for a suciently long time, until (i) the formednitric acid decomposes almost completely or (ii) aging of

nanoparticle transforms them from initial Cu(OH)2 toCu2(OH)3NO3 and, through which, to the nal or most-stable CuO product.

The above points can be summarized as follows: The forma-tion of nanoparticles is a time-consuming process andmay not becompleted in the short periods (e.g.,



contactwith eachother and fuse together, to forma three-dimensionalstructure comprised of cemented particles (see Figure 8).

4. CONCLUSION

Taguchi experiment design method oers a simple buteective technique for optimization of dierent chemical pro-cesses. Upon applying Taguchi method in the current study, thefollowing results were obtained:(1) A signicant parameter whose proper adjustment could, to a

large extent, alleviate the adverse eects of the other param-eters is temperature. The optimum temperature was deter-mined to be the maximum temperature, or 500 C.

(2) Since, in our experiments, attaining the thermal equilib-rium lasted longer than 40 min, heating courses shorterthan this period resulted in low production yield. On theother hand, a residence time of >2 h, because of the over-growth of the nanoparticles, was often detrimental. Over-all, when temperature was adequately high (over 450 C)to guarantee complete decomposition of Cu2(OH)3NO3to CuO, a heating period of 2 h was adequate and wasdetermined to be the best.

(3) While the reaction yield increased with the concentrationand pH, size and purity were remarkably deteriorated.Therefore, the optimum [Cu2] concentration and pHwere the minimums in the range of study, or 0.1 moldm-3 and pH 3, respectively. Lower concentrations andpHs are not recommended, because they severely reducethe yield. The basis of the current work on the study of theformation of nanoparticles was the three-step Adschirrismechanism, shown by reactions 4-6. One very importantpoint that is deduced from his theory is that nanoparticlesare initially formed in the aqueous solution in the form ofCu(OH)2 (or Cu2(OH)3NO3) through reaction sets 4and 5 or 4 and 10, and within the initial 60 min of the

reaction course, when liquid phases exist. The Cu(OH)2(or Cu2(OH)3NO3) nanoparticles then will be convertedto CuO nanoparticles via bulleted mechanisms.

For any of the bulleted mechanisms, there is some experi-mental evidence, but there is more evidence for the rst mech-anism. As a result, it was better to accept that both of thesemechanisms, to some extent, are involved in the formation ofCu2(OH)3NO3, but the rst mechanism stands as the chief one.Despite their slight dierence, both of the bulleted mechanismsemphasize the same fact, that is, the role of Cu2(OH)3NO3 as anintermediate in the formation of CuO. The nal CuO product ispartially formed via decomposition of this material and partiallyformed via dehydration reaction (reaction 6) that was reportedby Adschirri et al.

At very high temperature (T > 450 C), where Cu2(OH)3-NO3 is extremely unstable, the two bulleted mechanisms mergeinto each others and, in that case, only reaction set 4-6 occurs.

One signicant point that has not been emphasized by theprevious researchers is the important role of the decompositionof nitric acid to N2, H2O, etc. The occurrence of this reactionguarantees the stability of formed nanoparticles, because of theremoval of their solvent (HNO3) at the end of the reaction.

At the end, it seems worthwhile to briey discuss the generalityand applicability of the above ndings. The present study exploitedthe batch mode of the hydrothermal synthesis for fabrication ofthe CuO nanoparticles. The main advantage of the batch mode isthe possibility of controlling of oxidation states of the elements andpreparation of a system of mixed oxides in which a polycrystallinestructure of high homogeneity is formed. The mixed oxides phasesare of great importance in the manufacturing of the major indus-trial catalysts, and in the other applications of nanotechnology.

The current article, besides synthesizing of one of the im-portant nanomaterials, has provided the following:(1) The trends of the responses of the target parameters to

variations in the controlling factors, and the weight of the

Figure 7. TEM images of some CuO nanoparticles, showing the eect oftemperature on size ((top left) 350 C(A20) and (top right) 500 C(A18))and TEM images of some CuO nanoparticles, showing the eect of res-idence time on size ((bottom left) 2 h (A8) and (bottom right) 3 h (A21)).

Figure 8. TEM images of CuO nanoparticles, showing the eect of pHon size ((top left) pH 3.0 (A16) and (top right) pH 3.75 (A18)) and theeect of initial concentration on size ((bottom left) 0.1 mol dm-3

[Cu2] (A16) and (bottom right) 0.5 mol dm-3 [Cu2] (A19)).

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inuence of each controlling factor in the total response ofthe system. For instance, the results of this study demon-strated that the eect of temperature on size of the nano-particles is more pronounced than that of pH.Using the knowledge acquired in this study, the authorshave attempted to synthesize some other metal oxides inother batch reactors that had dierent geometries. A briefsummary of this investigation is presented in Table 77. Ineither case, the same trends of variation of the target pa-rameters with controlling factorwere observed, even thoughthe numerical results were, to an extent, dierent.Some of the results of the current batch experiments canbe used for parameter setting of the large-scale contin-uous process. For example, for the rst time, our batchexperiments exploited temperatures as high as 500 C forthe supercritical water (SCW) synthesis, which was anexperience that was proved advantageous. Now, based onthis experience, it is advisible to increase the temperatureof the continuous SCW reactors from its present values(normally



developed for estimation of the h value of a uid enclosed in aclosed enclosure:40

hmin kca kc 10-20 k

The kc/k ratio in the above equation is a function of theGrashof number; for our case of study, this ratio is between 10and 20. The thermal conductivity (k) values for saturated liquidand vapor are tabulated and may be found in some references.41

With regard to estimation of a minimum k value, we consideredthe worst or initial conditions in which one-third of the totalvolume was occupied by liquid and the rest by saturated vapor at25 C . In that case, the coecient h was dened as

hmin 10 1

3kliquid23kvapor

a

10 1

3 0:61

2

3 0:19

0:0275

120

For a more conservative estimation, hmin in the current studywas taken as 100 W/(m2 C). A simultaneous system (describedby eqs A-1 and A-2) was solved by the nite dierence method.The explicit forms of the equations, according to Figure A1b, are

Tttn TtnRt

1 12r

Ttn1

Rt

1-

12r

Ttn-1 A-5

Ttt1 2Rt2

Tt2 1-2Rt2

-2htFCP

Tt1

2htFCP

Ttin A-6

TttN 2FtFCP

TtW4-TtN4

1-2Rt2

TtN

2Rt2

TtN-1

A-7

utt h2aLtmt

Tt1 ut-

h2aLtmt

Ttin

A-8

Heating elements were mounted circumferentially in the innerside of a cylinder, which was quite close to the reactor surface (seeFigure A1). As a result, the view factor is almost equal to the viewfactor of two innite concentric cylinders:

F 11 1-2

2

cb

A-9

The stability conditions for monotonic convergence of ournite dierence equation were

t e1

hFCP

2R2

t e Minmut

h2aLTtin

A-10

Figure A1. (a) Schematic illustration of the high-pressure reactor and the heating furnace. (b) Cross section of the reactor wall, depicting the one-dimensional radial meshes.



Figure A2a shows the results of solving eqs A-5-A-8, using aMathlab computer code that was written for this purpose.According to this gure, the time required to attain the criticaltemperature (t373) is highly dependent on the temperature of theheating surface (i.e., TW). When the furnace temperature variesfrom 500 C to 750 C, t373 decreases by a factor of 3, from 3600 sto 1160 s.

The eect of variation of heat-transfer coecient (h) on t373 ispresented in Figure A2b. Compared to the eect ofTW, this eectis less pronounced. Indeed, a 10-fold increase in h could onlyprolong the t373 period from 1500 s to 1800 s. This behavior wasnot unexpected, because, as previously mentioned, the heating ofthe water takes only a small portion of the total injected energy.In addition, the convection rate of heat transfer to the watercannot exceed the rate of absorption of radiant energy by theexternal surface of reactor:

hTa, t-TineF TW 4-T4b, t A-11

The discussed model in the above text could reveal trends ofvariation of the response of system (i.e., Tin) with changes in themain physical parameters, such asTW and h. It also demonstratedthe pivotal role of the massive reactor body in the heat-transferprocess. In addition, it showed that even in the worst case (i.e.,TW= 500 C), the time required to attain the critical temperaturedoes not exceed 3500 s.

In a real heating system (Figure A1), the temperature of theouter surface of the reactor is monitored by a control system.Such system changes the heating power of the furnace, or, inother words, the temperature of the radiant surface (TW),according to the type and constants of the control system (i.e.,constants of proportional, derivative, and integral parts). As aresult, the term TW

4 in eq A-1 becomes variable, and, in addition,another equation is added to the system (eqs A-1 and A-2) todescribe the dynamics of the variation of TW by a control system.

The described model could be further modied by replacingthe one-dimensional equations given in eq A-1 with the corre-sponding two-dimensional set, including an additional axial term.Such modications, although necessary, are beyond the scope ofthe current article. Now, a new project for a comprehensivemodeling of the heat transfer as well as thermodynamic of thesynthesis reactor is planned, and under the procedure describedby the authors.

AUTHOR INFORMATION

Corresponding Author*E-mail: [email protected].

Present AddressJaber Ebne Hayyan Research Laboratory, NSTRI, Tehran, Iran.

ACKNOWLEDGMENT

The authors gratefully acknowledge the Department of En-ergy Engineering of Sharif University of Technology, for thenancial support of this project. They also would like to expressestheir gratitude appreciation toMr. SayyedMohsenMirahmadi ofSharif Energy Research Institute, and Prof. Ali Noori, Dr. MohsenHasanvand and Dr. Alireza Khanchi from Sharif University ofTechnology for their helpful discussions on the mechanisms ofreactions, and heat transfer in the batch reactors.

NOMENCLATURE AND NUMERICAL VALUES OF THEPHYSICAL PARAMETERS

Parametersa = inner radius of the reactor; a = 0.0275 mb = outer radius of the reactor; b = 0.05 mc = inner radius of the furnace; c = 0.06 mCP = heat capacity of stainless steel (SS316): CP = 560 J/(kg K)F = view factor for radiation-absorption from (and by) gray

surfaces, dimensionlessh = convective heat-transfer coecient, W/(m2 K)hMin = minimum convective heat-transfer coecient; hMin = 100

W/(m2 K)hMax = maximum convective heat-transfer coecient; hMax=

1000 W/(m2 K)k = thermal conductivity, W/(m K)kc = corrected thermal conductivity, W/(m K)kliquid = thermal conductivity of liquid water at 25 C; kliquid

0.61 W/(m K)kS-S = thermal conductivity of stainless steel (316) at 125 C;

kS-S 18.3 W/(m K)kvapor = thermal conductivity of saturated water steam at 25 C;

kvapor 0.19 W/(m K)L = height of reactor; L = 0.088 mmt = total mass of water; mt = 0.066 kg

Figure A2. (a) Variation of the response of system temperature (Tin), relative to changes in the furnace temperature (TW); in all cases, h = 250 W/(m2 K). (b) Eect of heat-transfer coecient (h) on the response of the system at constant temperature (TW = 650 C).

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r = radial coordinate, mPH2O = vapor pressure of water at dierent temperatures, PaPair = partial pressure of air in reactor; under the initial condi-

tions, Pair = 86700 PaPt = total pressure, Pat = time, sT = temperature of stainless steel, KTin = temperature of water, K (C)TW = temperature of radiating surface, Ku = specic internal energy of water, J/kgU = total internal energy of water, Jv = specic volume, m3/kgvf = specic volume of liquid water, m

3/kgvg = specic volume of water vapor, m

3/kgV = total volume of reactor; V = 2 10-4 m3

Greek Symbolsr = thermal diusivity of stainless steel; R = kS-S/(FCP) = 4.6

10-6 m2/s = size of radial mesh: = 1.125 10-5 mt = time increment, s = emissivity of surface, dimensionless1 = emissivity of oxidized stainless steel; 1 0.52 = emissivity of alumina; 2 = 0.7F = density of stainless steel; F = 7800 kg/m3

= Stefan-Boltzmann constant; = 5.67 10-8 W/(m2 K4)

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Hydrothermal Synthesis of CuO Nanoparticles- Study on Effects of Operational Conditions on Yield, Purity, And Size of the Nanoparticles