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An investigation on non-ferrous metals particles separability from electronic scraps using Hyperspectral Imaging and Micro-XRF Analysis

Riccardo Gasbarrone*, Silvia Serranti, Giuseppe BonifaziDepartment of Chemical Engineering Materials & Environment,

Sapienza University of Rome, Via Eudossiana, 18, 00184 Rome, Italy

*riccardo.gasbarrone@uniroma1.it

ICNIRS 2017 - 18th International Conference on Near Infrared Spectroscopy11th - 15th June 2017 – Copenhagen, Denmark

Challenge:

• In these last years, the volume of waste from electrical and electronic equipment (WEEE) Is steady increasing,

• A significant amount of valuable materials that can be profitably recovered is contained in WEEE (i.e. metals, precious metals, non-ferrous

metals, high-quality plastics and other materials).

Objectives:

• In this study, the attention was focused on the development, the set-up and the implementation of non-ferrous metal concentration strategies

at the end of a Magnetic Density Separation (MDS) process.

• Hyperspectral imaging (HSI) alongside with micro-XRF analysis are two of the main emerging innovative technologies in raw materials industry

that can enable an in-depth characterization of WEEE products.

HYPERSPECTRAL AND XRF

SYSTEMS

CLASSIFICATION MODELS

Acquisition, management and processing of spectra (SWIR: 1000-2500 nm) for classification

model building.

SWIR ANALYSIS

HSI classification models were obtained in order to evaluate the possibility to optically perform an almost similar recognition

carried out by XRF analysis.

SPECTRAL DATA

ANALYSIS

Spectral data have been analysed using thePLS_Toolbox 8.1 (Eigenvector ResearchInc.), in Matlab™ environment.Chemometric techniques were applied inorder to explore the data (PrincipalComponent Analysis - PCA) and to build aclassification model (Partial Least Square-Discriminant Analysis – PLS-DA) able todiscriminate the different material fractionsSpecim SISUChema XL™ Spectral

range: 1000 -2500 nm

ANALYZED SAMPLES

MDS byproduct consisting of milled WEEEfrom small and medium appliances.Provenience:WEEE treatment plant of Weeehold company(Rotterdam, The Netherlands), which utilisesan innovative separation technology, the so-called MDS (magnetic density separator).Size range:- 10 mmDensity range:1300 – 2200 kg/m3

µXRF analysis were performed to quantitatively access the presence of non- ferrous metals and other elements in the

fractions.

µXRF ANALYSIS

Semi-quantitative elemental analysis.

ELEMENTAL MAPS AND REPORT

PROCEDURE

Calculation on identification accuracy.

Bruker M4 Tornado

XRF

ANALYSIS

Elental maps and semi-quantitative elementalreport were obtained usingBruker M4 Tornado nativeprogram.

Total spectrum of a ROI

MODEL RESULTS

Training dataset

PCBs

Glass

White plastics

Wires

Black plastics

Wood

Predition map

ELEMENTAL MAPS

Elemental maps of all found elements

CONCLUSION

• Near infrared wavelength range does not allow the full identificationof metallic materials spectra: XRF analysis should be performed.

• Micro-XRF analysis may be extremely precise and accurate when ametal identification over material has to be done.

• The developed classification model allows the identification of thetypical material of the printed circuit boards involving metals: such asepoxy resin in the layer below the copper and solder mask on the top.