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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
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.
