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Record W4414515467 · doi:10.3390/recycling10050180

Recycling Disassembled Automotive Plastic Components for New Vehicle Components: Enabling the Automotive Circular Economy

2025· article· en· W4414515467 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueRecycling · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsnot available
FundersOak Ridge National LaboratoryUT-BattelleU.S. Department of EnergyMcGill UniversityBattelleAmerican Chemistry Council
KeywordsAutomotive industryPolypropyleneHeat deflection temperaturePlastics industryThermoplasticPolyamideMolding (decorative)Deflection (physics)

Abstract

fetched live from OpenAlex

As the automotive industry increasingly relies on plastic components to meet fuel efficiency and emissions targets, the challenge of managing end-of-life vehicle (ELV) plastics continues to grow. Currently, more than 80% of ELV plastics in the U.S. are landfilled due to limited economic incentives and technical barriers to recycling. This study examines a mechanical recycling pathway for thermoplastic components disassembled from ELVs and assesses their usability for reintegration into new vehicle parts. Four representative materials were chosen based on material labels embedded in recovered parts and aligned with their virgin industrial equivalents: polypropylene (PP), 10% talc-filled PP (PP-T10), 20% talc-filled PP (PP-T20), and a 20% glass-/mineral-filled polyamide (PA6 + GF7 + MF13). The materials underwent shredding, drying, and injection molding before being characterized by particle size analysis, density measurement, thermal analysis (TGA, DSC), mechanical testing, and heat deflection temperature (HDT) evaluation. The results in this work indicated that minor differences in crystallinity were observed and small differences between model materials and ELV materials could have contributed to these changes. Mechanical testing revealed that neat polypropylene suffered a 15–20% reduction in stiffness and tensile strength, but talc-filled polypropylene and glass/mineral-filled nylon retained >90% of their modulus, strength, and heat deflection temperature values relative to virgin controls. Differences between virgin and ELV materials could have been attributed to use life degradation, contamination during use life, or even chemical/processing differences in model materials and ELV materials. However, these findings suggest that mechanically recycled, disassembled ELV plastics can retain sufficient structural performance to support circularity efforts in the automotive sector.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.267
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it