Predicting LDPE/HDPE blend composition by CARS-PLS regression and confocal Raman spectroscopy

AUTOR(ES)

Silva, Daniel José da

FONTE

Polímeros

DATA DE PUBLICAÇÃO

18/03/2019

RESUMO

Abstract 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.

Documentos Relacionados

• Fast differentiation of bacteria causing pharyngitis by low resolution Raman spectroscopy and PLS-discriminant analysis
• Confocal Raman spectroscopy: determination of natural moisturizing factor profile related to skin hydration
• Nanostructured transdermal hormone replacement therapy for relieving menopausal symptoms: a confocal Raman spectroscopy study
• Rapid Identification of Candida Species by Confocal Raman Microspectroscopy
• Diagnosing breast cancer by using Raman spectroscopy