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Compositional Analysis and Mechanical Recycling of Polymer Fractions Recovered via the Industrial Sorting of Post-Consumer Plastic Waste: A Case Study toward the Implementation of Artificial Intelligence Databases
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This study characterizes the types and quantities of polymers found in end-of-life vehicles and evaluates how well those plastics can be recovered and reprocessed through mechanical recycling. Findings highlight the complexity of automotive plastic streams and the challenges of achieving high-quality recyclate from mixed polymer sources.
Nowadays, society is oriented toward reducing the production of plastics, which have a significant impact on the environment. In this context, the recycling of existing plastic objects is currently a fundamental step in the mitigation of pollution. Very recently, the outstanding development of artificial intelligence (AI) has concerned and continues to involve a large part of the industrial and informatics sectors. The opportunity to implement big data in the frame of recycling processes is oriented toward the improvement and the optimization of the reproduction of plastic objects, possibly with enhanced properties and durability. Here, a deep cataloguing, characterization and recycling of plastic wastes provided by an industrial sorting plant was performed. The potential improvement of the mechanical properties of the recycled polymers was assessed by the addition of coupling agents. On these bases, a classification system based on the collected results of the recycled materials' properties was developed, with the aim of laying the groundwork for the improvement of AI databases and helpfully supporting industrial recycling processes.
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