MIR spectral characterization of plastic to enable discrimination in an industrial recycling context: II. Specific case of polyolefins.

Identification MIR Polymer recycling Polyolefins Sorting WEEE

Journal

Waste management (New York, N.Y.)
ISSN: 1879-2456
Titre abrégé: Waste Manag
Pays: United States
ID NLM: 9884362

Informations de publication

Date de publication:
Oct 2019
Historique:
received: 30 04 2019
revised: 15 07 2019
accepted: 09 08 2019
pubmed: 27 8 2019
medline: 13 9 2019
entrez: 27 8 2019
Statut: ppublish

Résumé

Sorting at industrial scale is required to perform mechanical recycling of plastics in order to obtain properties that could be competitive with virgin polymers. As a matter of fact, the most part of the various types of plastic waste are not miscible and even compatible. Mid-Infrared (MIR) HyperSpectral Imagery (HSI) is viewed as one of the solutions to the problem of black plastic sorting. Many Waste of Electrical and Electronic Equipment (WEEE) plastics are black. Nowadays, these materials are difficult to sort at an industrial scale because the main used pigment to produce this color, carbon black, masks the Near-Infrared (NIR) spectra of polymers, the currently most used technology for acute sorting in industrial conditions. In this study, laboratory Fourier-Transform Infrared (FTIR) in Attenuated Total Reflection mode (ATR) has been used as a theoretical toolbox based on physical chemistry to help building an automated HSI discrimination despite its limited conditions, especially shorter wavelengths ranges. Weaker resolution and very short acquisition times are other HSI limitations. Helping fast and exhaustive laboratory characterizations of polymeric waste stocks is the other goal of this study. This study focusses on polyolefins as they represent the second biggest fraction of WEEE plastics (WEEP) after styrenics and since little quantities mixed to styrenics during mechanical recycling can lead to important decrease in mechanical properties. Twelve references were thus evaluated and compared between each other and with real waste samples to highlight spectral elements, which can enable differentiation. Charts compiling the signals of discussed polymers were built aiming to the same objective.

Identifiants

pubmed: 31450178
pii: S0956-053X(19)30524-0
doi: 10.1016/j.wasman.2019.08.010
pii:
doi:

Substances chimiques

Plastics 0
Polyenes 0
Polymers 0
PL 732 83136-87-2

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

160-172

Informations de copyright

Copyright © 2019 Elsevier Ltd. All rights reserved.

Auteurs

Charles Signoret (C)

C2MA, IMT Mines Ales, Univ Montpellier, 7 Avenue Jules Renard 30100 Ales, France.

Anne-Sophie Caro-Bretelle (AS)

C2MA, IMT Mines Ales, Univ Montpellier, 7 Avenue Jules Renard 30100 Ales, France.

José-Marie Lopez-Cuesta (JM)

C2MA, IMT Mines Ales, Univ Montpellier, 7 Avenue Jules Renard 30100 Ales, France.

Patrick Ienny (P)

C2MA, IMT Mines Ales, Univ Montpellier, 7 Avenue Jules Renard 30100 Ales, France.

Didier Perrin (D)

C2MA, IMT Mines Ales, Univ Montpellier, 7 Avenue Jules Renard 30100 Ales, France. Electronic address: didier.perrin@mines-ales.fr.

Articles similaires

Semiconductors Photosynthesis Polymers Carbon Dioxide Bacteria
Animals Huntington Disease Mitochondria Neurons Mice
Rivers India Environmental Monitoring Microplastics Water Pollutants, Chemical
Nanoparticles Needles Polylactic Acid-Polyglycolic Acid Copolymer Polyethylene Glycols Curcumin

Classifications MeSH