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Miniaturized Near-Infrared (MicroNIR) Spectrometer in Plastic Waste Sorting

Valorisation of the urban plastic waste in high-quality recyclates is an imperative challenge in the new paradigm of the circular economy. In this scenario, a key role in the improvement of the recycling process is exerted by the optimization of waste sorting. In spite of the enormous developments a...

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Autores principales: Rani, Monika, Marchesi, Claudio, Federici, Stefania, Rovelli, Gianluca, Alessandri, Ivano, Vassalini, Irene, Ducoli, Serena, Borgese, Laura, Zacco, Annalisa, Bilo, Fabjola, Bontempi, Elza, Depero, Laura E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6747759/
https://www.ncbi.nlm.nih.gov/pubmed/31461858
http://dx.doi.org/10.3390/ma12172740
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author Rani, Monika
Marchesi, Claudio
Federici, Stefania
Rovelli, Gianluca
Alessandri, Ivano
Vassalini, Irene
Ducoli, Serena
Borgese, Laura
Zacco, Annalisa
Bilo, Fabjola
Bontempi, Elza
Depero, Laura E.
author_facet Rani, Monika
Marchesi, Claudio
Federici, Stefania
Rovelli, Gianluca
Alessandri, Ivano
Vassalini, Irene
Ducoli, Serena
Borgese, Laura
Zacco, Annalisa
Bilo, Fabjola
Bontempi, Elza
Depero, Laura E.
author_sort Rani, Monika
collection PubMed
description Valorisation of the urban plastic waste in high-quality recyclates is an imperative challenge in the new paradigm of the circular economy. In this scenario, a key role in the improvement of the recycling process is exerted by the optimization of waste sorting. In spite of the enormous developments achieved in the field of automated sorting systems, the quest for the reduction of cross-contamination of incompatible polymers as well as a rapid and punctual sorting of the unmatched polymers has not been sufficiently developed. In this paper, we demonstrate that a miniaturized handheld near-infrared (NIR) spectrometer can be used to successfully fingerprint and classify different plastic polymers. The investigated urban plastic waste comprised polyethylene (PE), polypropylene (PP), poly(vinyl chloride) (PVC), poly(ethylene terephthalate) (PET), and poly(styrene) (PS), collected directly in a recycling plastic waste plant, without any kind of sample washing or treatment. The application of unsupervised and supervised chemometric tools such as principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) on the NIR dataset resulted in a complete classification of the polymer classes. In addition, several kinds of PET (clear, blue, coloured, opaque, and boxes) were correctly classified as PET class, and PE samples with different branching degrees were properly separated.
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spelling pubmed-67477592019-09-27 Miniaturized Near-Infrared (MicroNIR) Spectrometer in Plastic Waste Sorting Rani, Monika Marchesi, Claudio Federici, Stefania Rovelli, Gianluca Alessandri, Ivano Vassalini, Irene Ducoli, Serena Borgese, Laura Zacco, Annalisa Bilo, Fabjola Bontempi, Elza Depero, Laura E. Materials (Basel) Article Valorisation of the urban plastic waste in high-quality recyclates is an imperative challenge in the new paradigm of the circular economy. In this scenario, a key role in the improvement of the recycling process is exerted by the optimization of waste sorting. In spite of the enormous developments achieved in the field of automated sorting systems, the quest for the reduction of cross-contamination of incompatible polymers as well as a rapid and punctual sorting of the unmatched polymers has not been sufficiently developed. In this paper, we demonstrate that a miniaturized handheld near-infrared (NIR) spectrometer can be used to successfully fingerprint and classify different plastic polymers. The investigated urban plastic waste comprised polyethylene (PE), polypropylene (PP), poly(vinyl chloride) (PVC), poly(ethylene terephthalate) (PET), and poly(styrene) (PS), collected directly in a recycling plastic waste plant, without any kind of sample washing or treatment. The application of unsupervised and supervised chemometric tools such as principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) on the NIR dataset resulted in a complete classification of the polymer classes. In addition, several kinds of PET (clear, blue, coloured, opaque, and boxes) were correctly classified as PET class, and PE samples with different branching degrees were properly separated. MDPI 2019-08-27 /pmc/articles/PMC6747759/ /pubmed/31461858 http://dx.doi.org/10.3390/ma12172740 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Rani, Monika
Marchesi, Claudio
Federici, Stefania
Rovelli, Gianluca
Alessandri, Ivano
Vassalini, Irene
Ducoli, Serena
Borgese, Laura
Zacco, Annalisa
Bilo, Fabjola
Bontempi, Elza
Depero, Laura E.
Miniaturized Near-Infrared (MicroNIR) Spectrometer in Plastic Waste Sorting
title Miniaturized Near-Infrared (MicroNIR) Spectrometer in Plastic Waste Sorting
title_full Miniaturized Near-Infrared (MicroNIR) Spectrometer in Plastic Waste Sorting
title_fullStr Miniaturized Near-Infrared (MicroNIR) Spectrometer in Plastic Waste Sorting
title_full_unstemmed Miniaturized Near-Infrared (MicroNIR) Spectrometer in Plastic Waste Sorting
title_short Miniaturized Near-Infrared (MicroNIR) Spectrometer in Plastic Waste Sorting
title_sort miniaturized near-infrared (micronir) spectrometer in plastic waste sorting
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6747759/
https://www.ncbi.nlm.nih.gov/pubmed/31461858
http://dx.doi.org/10.3390/ma12172740
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