Recycling of Engineering Polymers: Process and Physico-Chemical Changes

A special issue of Polymers (ISSN 2073-4360). This special issue belongs to the section "Polymer Processing and Engineering".

Deadline for manuscript submissions: 31 May 2025 | Viewed by 1779

Special Issue Editors


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Guest Editor
Polymer Processing Division, Institute of Materials Technology, Faculty of Mechanical Engineering, Poznan University of Technology, Piotrowo 3, 61-138 Poznan, Poland
Interests: polymer composites and nanocomposites; polymer blends; polyoxymethylene composites; plastics engineering; mechanics of plastics cracking; mechanical-thermal properties of recyclates; product ecology; design for recycling; environmental management; structure development in polymer processing; polymer processing; ageing of polymers; polymer recycling; biodegradation; material characterization

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Guest Editor
Department of Industrial Products and Packaging Quality, Institute of Quality Science, Poznań University of Economics and Business, Poznan, Poland
Interests: packaging materials; plastic; quality; safety; recycling; eco-design; design for recycling; biodegradation; innovation; greenwashing; microplastics

Special Issue Information

Dear Colleagues,

We are dedicating you to this new Special Issue dedicated to the issues of Recycling Engineering Polymers, where you can post the results of scientific research and share with others new technological solutions aimed at recovering from secondary waste polymeric materials and raw materials with defined characteristics and structure according to the principles of the circular economy.

The modern world shows a huge demand for new recycled polymeric materials in the form of recyclates and their mixtures, the properties and structure of which can be compared with virgin materials. The aim of this Special Issue is to bring together research or review papers into a single-issue collection of the current state of the art in the field of mechanical/chemical/organic recycling of polymeric waste, the correlation between processing parameters and the resulting structure and properties of re-granulated or other raw materials obtained by chemical and/or organic recycling.

We very much hope that this absorbing topic, driven by the needs of industry and the conservation of non-renewable resources, will prompt you to submit your manuscript to this Special Issue.

This Special Issue focuses on the following topics:

  • Mechanical recycling of polymers: process/physical-chemical changes in re-granulated/closing the loop.
  • Effect of polymer recycling on resulting morphology and/or properties.
  • Mechanical, rheological, and thermal properties of polymers induced by reprocessing conditions and their relationship with the structure.
  • Organic recycling/chemical recycling and properties polymers by processing.

Prof. Dr. Dorota Czarnecka-Komorowska
Dr. Karolina Wiszumirska
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Polymers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • engineering polymer wastes
  • closing the loop/circular economy
  • mechanical recycling
  • chemical recycling
  • organic recycling
  • property–structure relationships

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Published Papers (1 paper)

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Research

17 pages, 2542 KiB  
Article
Machine Learning in the Analysis of the Mechanical Shredding Process of Polymer Recyclates
by Izabela Rojek, Marek Macko and Dariusz Mikołajewski
Polymers 2024, 16(13), 1852; https://doi.org/10.3390/polym16131852 - 28 Jun 2024
Viewed by 1177
Abstract
Artificial intelligence methods and techniques creatively support the processes of developing and improving methods for selecting shredders for the processing of polymer materials. This allows to optimize the fulfillment of selection criteria, which may include not only indicators related to shredding efficiency and [...] Read more.
Artificial intelligence methods and techniques creatively support the processes of developing and improving methods for selecting shredders for the processing of polymer materials. This allows to optimize the fulfillment of selection criteria, which may include not only indicators related to shredding efficiency and recyclate quality but also energy consumption. The aim of this paper is to select methods of analysis based on artificial intelligence (AI) with independent rule extraction, i.e., data-based methods (machine learning—ML). This study took into account real data sets (feature matrix 1982 rows × 40 columns) describing the shredding process, including energy consumption used to optimize the parameters for the energy efficiency of the shredder. Each of the 1982 records in a .csv file (feature vector) has 40 numbers divided by commas. The data were divided into a learning set (70% of the data), a testing set (20% of the data), and a validation set (10% of the data). Cross-validation showed that the best model was LbfgsLogisticRegressionOva (0.9333). This promotes the development of the basis for an intelligent shredding methodology with a high level of innovation in the processing and recycling of polymer materials within the Industry 4.0 paradigm. Full article
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