ArticlePolymers2024
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.
Article in Polymers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Valorization of Expanded Polystyrene by Embedding of High GFRP Loading Through Cold-Mixing Solvent-Assisted Process.Polymers · 2026Article
- Microplastic Formation and Surface Crack Patterns: A Method for Waste Plastic Identification.Molecules (Basel, Switzerland) · 2025Review
- Application of Computational Studies Using Density Functional Theory (DFT) to Evaluate the Catalytic Degradation of Polystyrene.Polymers · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.