Predicting LDPE/HDPE blend composition by CARS-PLS regression and confocal Raman spectroscopy
| Autor: | Daniel José da Silva, Hélio Wiebeck |
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| Jazyk: | English<br />Portuguese |
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | Polímeros, Vol 29, Iss 1 (2019) |
| Druh dokumentu: | article |
| ISSN: | 1678-5169 0104-1428 |
| DOI: | 10.1590/0104-1428.00218 |
| Popis: | 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. |
| Databáze: | Directory of Open Access Journals |
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