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Record W4377138792 · doi:10.1002/pol.20230154

Recycling of polyamides: Processes and conditions

2023· article· en· W4377138792 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.319

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.033
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