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URN to cite this document: urn:nbn:de:bvb:703-epub-9033-8
Title data
Albuquerque, Rodrigo Q. ; Stephan, Florian ; Pongratz, Annalena ; Brütting, Christian ; Krause, Katharina ; Ruckdäschel, Holger:
Recycling of Thermoplastics with Machine Learning : A Review.
In: Advanced Functional Materials.
Vol. 36
(2026)
Issue 3
.
- e09447.
ISSN 1616-3028
DOI der Verlagsversion: https://doi.org/10.1002/adfm.202509447
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Project information
| Project title: |
Project's official title Project's id Maschinelles Lernen zur zielgerichteten Prozessführung beim Recycling von Polyestern mittels reaktiver Extrusion 518732456 Open Access Publizieren No information |
|---|---|
| Project financing: |
Deutsche Forschungsgemeinschaft |
Abstract
This critical review examines the transformative role of machine learning (ML) in revolutionizing thermoplastic recycling across mechanical, chemical, and biological pathways. As global plastic waste challenges intensify, sophisticated ML approaches are emerging as powerful tools to overcome traditional recycling limitations. Recent technological breakthroughs are systematically analyzed that leverage ML to optimize sorting precision, process efficiency, and quality assurance in recycled thermoplastics. The review presents a detailed analysis of feature engineering strategies that have proven most effective across diverse recycling applications. By identifying current implementation barriers and unexplored opportunities, a forward-looking research agenda is established for ML integration that can accelerate progress toward a truly circular thermoplastic economy. This interdisciplinary perspective bridges materials science, computer science, and sustainability to provide actionable insights for researchers and industry practitioners.
Further data
| Item Type: | Article in a journal |
|---|---|
| Keywords: | biological recycling; chemical recycling; machine learning; mechanical recycling; thermoplastics |
| DDC Subjects: | 600 Technology, medicine, applied sciences > 620 Engineering |
| Institutions of the University: | Faculties > Faculty of Engineering Science > Chair Polymer Materials > Chair Polymer Materials - Univ.-Prof. Dr.-Ing. Holger Ruckdäschel Profile Fields > Advanced Fields > Advanced Materials Faculties Faculties > Faculty of Engineering Science Faculties > Faculty of Engineering Science > Chair Polymer Materials Profile Fields Profile Fields > Advanced Fields |
| Language: | English |
| Originates at UBT: | Yes |
| URN: | urn:nbn:de:bvb:703-epub-9033-8 |
| Date Deposited: | 27 Mar 2026 12:28 |
| Last Modified: | 27 Mar 2026 12:28 |
| URI: | https://epub.uni-bayreuth.de/id/eprint/9033 |
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