Accurate Characterization of Mixed Plastic Waste Using Machine Learning and Fast Infrared Spectroscopy-Reference-Cited by-同舟云学术

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Accurate Characterization of Mixed Plastic Waste Using Machine Learning and Fast Infrared Spectroscopy

Published:2021-10-12 Issue:42 Volume:9 Page:14143-14151
ISSN:2168-0485
Container-title:ACS Sustainable Chemistry & Engineering
language:en
Short-container-title:ACS Sustainable Chem. Eng.

Author:

Zinchik Stas¹,Jiang Shengli²^ORCID,Friis Søren³,Long Fei¹^ORCID,Høgstedt Lasse³,Zavala Victor M.²,Bar-Ziv Ezra¹^ORCID

Affiliation:

1. Department of Mechanical Engineering, Michigan Technological University, Houghton, Michigan 49931, United States

2. Department of Chemical and Biological Engineering, University of Wisconsin—Madison, Madison, Wisconsin 53706, United States

3. NLIR ApS, Hirsemarken 1, Farum 3520, Denmark

Funder

National Science Foundation

Publisher

American Chemical Society (ACS)

Subject

Renewable Energy, Sustainability and the Environment,General Chemical Engineering,Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acssuschemeng.1c04281

Reference43 articles.

1. Plastic wastes to construction products: Status, limitations and future perspective

2. A review on automated sorting of source-separated municipal solid waste for recycling

3. Recyling of plastic wastes via pyrolysis

4. Polymer blends and composites from renewable resources

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