Post-consumer recycling of PA66-GF Composites from Electrical Waste: Performance Retention through Accelerated Aging Models
Bibliographic record
Abstract
The recycling of post-consumer glass fiber-reinforced polyamide 6,6 (PA66-GF) composites from electrical equipment poses significant challenges due to material degradation after prolonged use and high-temperature exposure. This study investigates the recyclability and performance retention of PA66-GF composites simulating end-of-life (EoL) waste from low-voltage circuit breaker components. A simplified accelerated thermal aging model, based on an Arrhenius-type equation, was developed to examine the relationship between aging time, temperature, and the material's mechanical properties. This model was then used to age virgin PA66-GF specimens to a state representative of post-consumer waste after a 20-year service life in low-voltage circuit breakers. Comparative analyses were conducted on virgin, aged, and recycled PA66-GF samples to assess mechanical, thermal, electrical, and structural changes through various characterization methods, including tensile and flexural tests, Charpy impact tests, Comparative Tracking Index (CTI), glow wire tests, vertical flame burning tests, and SEM-EDX measurements. Testing revealed measurable declines in mechanical properties in aged samples, accompanied by changes in crystallinity and oxidation levels. Recycled aged samples, when incorporated back into new formulations at varying proportions, demonstrated that up to a specific threshold, recyclate could be reintroduced with minimal impact on key material properties. These results suggest an optimal percentage of aged/recycled content in new PA66-GF formulations that balances performance and sustainability goals, providing a practical approach for recycling EoL plastic components from electrical waste. This study underscores the feasibility of incorporating post-consumer recycled composites into circular material flows and offers a framework for recycling similar high-performance polyamide composites in industrial applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".