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Record W4377138792 · doi:10.1002/pol.20230154

Recycling of polyamides: Processes and conditions

2023· article· en· W4377138792 on OpenAlexaff
Valerian Hirschberg, Denis Rodrigue

Bibliographic record

VenueJournal of Polymer Science · 2023
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPolyamideAutomotive industryProcess engineeringRange (aeronautics)SustainabilityPolymerMaterials scienceComputer scienceBiochemical engineeringComposite materialEngineering

Abstract

fetched live from OpenAlex

Abstract Polyamides (PA) are a family of engineering thermoplastics used in a wide range of applications including automotive, building, construction, separation processes, textiles, and so forth. This is related to their good properties (mechanical and thermal) which can also be modified by additives, other polymers (blends and multilayers) and fillers (composites). But these complex systems (several components) make the final materials more difficult to recycle. In this review, basic statistics on the production rate of polyamides are presented and the different recycling methods are reported to compare their advantages and limitations with respect to economics and technical analyses. The discussion includes biological, chemical, mechanical, physical, and thermal treatments to reintroduce, as much as possible, the parts after their end‐of‐service. Finally, a general conclusion on the current state of PA recycling is presented with several openings for future developments to satisfy the concept of circular economy and general sustainability.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.033
GPT teacher head0.282
Teacher spread0.249 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations115
Published2023
Admission routes1
Has abstractyes

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