Proposição de modelos de classificação e de calibração para polímeros presentes em resíduos eletrônicos empregando laser-induced breakdown spectroscopy (LIBS) e ferramentas quimiométricas
Resumo
This thesis proposes the development of analytical
methods for the analysis of polymers from waste electrical electronic equipment (WEEE)
by laser-Induced breakdown spectroscopy (LIBS). The results presented in the chapters
2 and 3 of this thesis were developed in collaboration with a recycling company of WEEE
called REVERSA. In the first method proposed LIBS was used for the identification and
classification of six polymers and a total of 477 samples were analyzed. Classification
models using k-nearest neighbors (KNN) and soft independent modeling of class
analogy (SIMCA) were used to classify the polymers. The proposed models presented
satisfactory results for the validation samples, with accuracy of 98% for KNN and 92%
for SIMCA. In addition, other validation parameters such as sensitivity, false alarm rate
and specificity showed adequate. In the second method, the LIBS was employed to
determination of the constituents polycarbonate (PC) and acrylonitrile-butadiene-styrene
(ABS) in PC/ABS blends. For this were built multivariate calibration models using partial
least squares (PLS). The PLS models obtained for the PC and ABS presented good
analytical parameters as: i) standard error calibration (SEC) of 3.4 (w/w%); (ii) standard
error of cross-validation (SECV) of 5.6 (w/w%); iii) linear correlation coefficient of 0.996;
iv) number of latent variables equal to 2; v) explained variance of 70%. For the validation
of the PLS models PC/ABS blends with unknown concentrations of PC and ABS were
analyzed, and the information provided by LIBS was in agreement with the reference
technique. A third method was developed in collaboration with a plastics recycling
company of car batteries. These plastics were contaminated with Pb and the objective
was to evaluate different calibration strategies in LIBS for the quantitative determination
of this analyte. Multivariate calibration strategies and a new univariate strategy were
proposed. The new univariate calibration strategy was called a two-point calibration
transfer and the results presented were satisfactory. The chemometrics tools including
experimental desing, supervised methods for classification, unsupervised methods and
multivariate calibration were employed during the development of the methods proposed
in this thesis.
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