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Electronic waste analysis using laser-induced breakdown spectroscopy (LIBS) and X-ray fluorescence (XRF): Critical evaluation of data fusion for the determination of Al, Cu and Fe

dc.contributor.authorFerreira, Dennis S.
dc.contributor.authorPereira, Fabiola M.V. [UNESP]
dc.contributor.authorOlivieri, Alejandro C.
dc.contributor.authorPereira-Filho, Edenir R.
dc.contributor.institutionUniversidade Federal de São Carlos (UFSCar)
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionUniversidad Nacional de Rosario
dc.contributor.institutionInstituto de Química Rosario (CONICET-UNR)
dc.date.accessioned2025-04-29T19:35:12Z
dc.date.issued2024-05-15
dc.description.abstractBackground: Electronic waste (e-waste) proliferation and its implications underscore the imperative for advanced analytical methods to mitigate its environmental impact. It is estimated that e-waste production stands at a staggering 20–50 million tons yearly, of which merely 20–25% undergo formal recycling. The e-waste samples evaluated contain computers, laptops, smartphones, and tablets. Results: Forty-one samples were processed, involving the disassembly and separation of components. Subsequently, two analytical techniques, laser-induced breakdown spectroscopy (LIBS) and energy dispersive X-ray fluorescence (ED-XRF), were applied to quantify aluminum (Al), copper (Cu), and iron (Fe) in the e-waste samples. The samples were then analyzed after acid mineralization with 50% v v−1 aqua regia in a digester block and finally by ICP OES. A solid residue composed of Si and Ti was observed after the digestion of the samples. Multivariate calibration strategies such as partial least-squares regression (PLS), principal component regression (PCR), maximum likelihood principal component regression (MLPCR), and error covariance penalized regression (ECPR) were used for calibration. Finally, the figures of merit were calculated to verify the most suitable models. The results revealed robust models with notable sensitivity, varying from 8.98 to 35.04 Signal (a.u.)(% w w−1) −1, low Limits of Detection (LoD) within the range of 0.001–0.2 % w w−1, and remarkable relative errors ranging from 2% to 33%, particularly for Cu and Fe. Significance: Notably, the models for Al faced inherent challenges, thus highlighting the complexities associated with its quantification in e-waste samples. In conclusion, this research represents an important step toward a more sustainable and efficient future for electronic waste recycling, signifying its relevance to global environmental welfare and resource conservation.en
dc.description.affiliationGroup of Applied Instrumental Analysis (GAIA) Department of Chemistry Federal University of São Carlos (UFSCar), P.O. Box 676
dc.description.affiliationGroup of Alternative Analytical Approaches (GAAA) Bioenergy Research Institute (IPBEN) Institute of Chemistry São Paulo State University (UNESP), São Paulo
dc.description.affiliationDepartamento de Química Analítica Facultad de Ciencias Bioquímicas y Farmacéuticas Universidad Nacional de Rosario, Suipacha 531
dc.description.affiliationInstituto de Química Rosario (CONICET-UNR), 27 de Febrero 210 Bis
dc.description.affiliationUnespGroup of Alternative Analytical Approaches (GAAA) Bioenergy Research Institute (IPBEN) Institute of Chemistry São Paulo State University (UNESP), São Paulo
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipConsejo Nacional de Investigaciones Científicas y Técnicas
dc.description.sponsorshipUniversidad Nacional de Rosario
dc.description.sponsorshipAgencia Nacional de Promoción Científica y Tecnológica
dc.description.sponsorshipIdCNPq: 140867/2021–0
dc.description.sponsorshipIdCNPq: 302085/2022–0
dc.description.sponsorshipIdCNPq: 302719/2020–2
dc.description.sponsorshipIdCNPq: 307328/2019–8
dc.description.sponsorshipIdAgencia Nacional de Promoción Científica y Tecnológica: PICT 2020–00179
dc.identifierhttp://dx.doi.org/10.1016/j.aca.2024.342522
dc.identifier.citationAnalytica Chimica Acta, v. 1303.
dc.identifier.doi10.1016/j.aca.2024.342522
dc.identifier.issn1873-4324
dc.identifier.issn0003-2670
dc.identifier.scopus2-s2.0-85188961195
dc.identifier.urihttps://hdl.handle.net/11449/304530
dc.language.isoeng
dc.relation.ispartofAnalytica Chimica Acta
dc.sourceScopus
dc.subjectData fusion
dc.subjectE-waste
dc.subjectFigure of merit
dc.subjectLIBS
dc.subjectMultivariate calibration
dc.titleElectronic waste analysis using laser-induced breakdown spectroscopy (LIBS) and X-ray fluorescence (XRF): Critical evaluation of data fusion for the determination of Al, Cu and Feen
dc.typeArtigopt
dspace.entity.typePublication
relation.isOrgUnitOfPublicationbc74a1ce-4c4c-4dad-8378-83962d76c4fd
relation.isOrgUnitOfPublication.latestForDiscoverybc74a1ce-4c4c-4dad-8378-83962d76c4fd
unesp.author.orcid0000-0003-1554-8901 0000-0003-1554-8901 0000-0003-1554-8901[1]
unesp.author.orcid0000-0003-4276-0369 0000-0003-4276-0369[3]
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Química, Araraquarapt
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Pesquisa em Bioenergia, Rio Claropt

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