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.author | Ferreira, Dennis S. | |
| dc.contributor.author | Pereira, Fabiola M.V. [UNESP] | |
| dc.contributor.author | Olivieri, Alejandro C. | |
| dc.contributor.author | Pereira-Filho, Edenir R. | |
| dc.contributor.institution | Universidade Federal de São Carlos (UFSCar) | |
| dc.contributor.institution | Universidade Estadual Paulista (UNESP) | |
| dc.contributor.institution | Universidad Nacional de Rosario | |
| dc.contributor.institution | Instituto de Química Rosario (CONICET-UNR) | |
| dc.date.accessioned | 2025-04-29T19:35:12Z | |
| dc.date.issued | 2024-05-15 | |
| dc.description.abstract | Background: 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.affiliation | Group of Applied Instrumental Analysis (GAIA) Department of Chemistry Federal University of São Carlos (UFSCar), P.O. Box 676 | |
| dc.description.affiliation | Group of Alternative Analytical Approaches (GAAA) Bioenergy Research Institute (IPBEN) Institute of Chemistry São Paulo State University (UNESP), São Paulo | |
| dc.description.affiliation | Departamento de Química Analítica Facultad de Ciencias Bioquímicas y Farmacéuticas Universidad Nacional de Rosario, Suipacha 531 | |
| dc.description.affiliation | Instituto de Química Rosario (CONICET-UNR), 27 de Febrero 210 Bis | |
| dc.description.affiliationUnesp | Group of Alternative Analytical Approaches (GAAA) Bioenergy Research Institute (IPBEN) Institute of Chemistry São Paulo State University (UNESP), São Paulo | |
| dc.description.sponsorship | Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) | |
| dc.description.sponsorship | Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) | |
| dc.description.sponsorship | Consejo Nacional de Investigaciones Científicas y Técnicas | |
| dc.description.sponsorship | Universidad Nacional de Rosario | |
| dc.description.sponsorship | Agencia Nacional de Promoción Científica y Tecnológica | |
| dc.description.sponsorshipId | CNPq: 140867/2021–0 | |
| dc.description.sponsorshipId | CNPq: 302085/2022–0 | |
| dc.description.sponsorshipId | CNPq: 302719/2020–2 | |
| dc.description.sponsorshipId | CNPq: 307328/2019–8 | |
| dc.description.sponsorshipId | Agencia Nacional de Promoción Científica y Tecnológica: PICT 2020–00179 | |
| dc.identifier | http://dx.doi.org/10.1016/j.aca.2024.342522 | |
| dc.identifier.citation | Analytica Chimica Acta, v. 1303. | |
| dc.identifier.doi | 10.1016/j.aca.2024.342522 | |
| dc.identifier.issn | 1873-4324 | |
| dc.identifier.issn | 0003-2670 | |
| dc.identifier.scopus | 2-s2.0-85188961195 | |
| dc.identifier.uri | https://hdl.handle.net/11449/304530 | |
| dc.language.iso | eng | |
| dc.relation.ispartof | Analytica Chimica Acta | |
| dc.source | Scopus | |
| dc.subject | Data fusion | |
| dc.subject | E-waste | |
| dc.subject | Figure of merit | |
| dc.subject | LIBS | |
| dc.subject | Multivariate calibration | |
| dc.title | 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 | en |
| dc.type | Artigo | pt |
| dspace.entity.type | Publication | |
| relation.isOrgUnitOfPublication | bc74a1ce-4c4c-4dad-8378-83962d76c4fd | |
| relation.isOrgUnitOfPublication.latestForDiscovery | bc74a1ce-4c4c-4dad-8378-83962d76c4fd | |
| unesp.author.orcid | 0000-0003-1554-8901 0000-0003-1554-8901 0000-0003-1554-8901[1] | |
| unesp.author.orcid | 0000-0003-4276-0369 0000-0003-4276-0369[3] | |
| unesp.campus | Universidade Estadual Paulista (UNESP), Instituto de Química, Araraquara | pt |
| unesp.campus | Universidade Estadual Paulista (UNESP), Instituto de Pesquisa em Bioenergia, Rio Claro | pt |

