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Polímeros

Print version ISSN 0104-1428On-line version ISSN 1678-5169

Abstract

SILVA, Daniel José da  and  WIEBECK, Hélio. Predicting LDPE/HDPE blend composition by CARS-PLS regression and confocal Raman spectroscopy. Polímeros [online]. 2019, vol.29, n.1, e2019010.  Epub Mar 18, 2019. ISSN 0104-1428.  http://dx.doi.org/10.1590/0104-1428.00218.

Industries and the scientific community currently focus on creating new ways to recycle and to reuse polymer waste that leads to serious socio-environmental risks. However, the quality of recycled polyethylenes depends strongly on their purity degree, but the distinction between Low Density Polyethylene (LDPE) and High Density Polyethylene (HDPE) by a fast and consistently good methodology is still an unsolved issue for the current recycling processes. In this study, confocal Raman spectroscopy and Competitive Adaptive Reweighted Sampling - Partial Least Squares (CARS-PLS) linear regression have been successfully applied to quantify the concentration of LDPE/HDPE blends. The effects of several regression parameters (pretreatment method, Monte Carlo sampling runs, k-fold and maximal number of latent variables for cross-validation) on the CARS-PLS model training and prediction performance were analyzed. The CARS-PLS-based models show root-mean-squared prediction error of 4.06 - 8.87 wt% of LDPE for the whole composition range of HDPE/LDPE blend.

Keywords : CARS-PLS regression; polymer blends; polyethylene; confocal Raman spectroscopy.

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