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Record W4297249032 · doi:10.1002/cssc.202201613

Solid‐State Enzymatic Hydrolysis of Mixed PET/Cotton Textiles**

2022· article· en· W4297249032 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemSusChem · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesHORIZON EUROPE Marie Sklodowska-Curie ActionsNatural Sciences and Engineering Research Council of Canada
KeywordsHydrolysisEnzymatic hydrolysisChemistrySolid-stateEnzymePolymer scienceChemical engineeringMaterials scienceOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Waste polyester textiles are not recycled due to separation challenges and partial structural degradation during use and recycling. Chemical recycling of polyethylene terephthalate (PET) textiles through depolymerization can provide a feedstock of recycled monomers to make "as-new" polymers. While enzymatic PET recycling is a more selective and more sustainable approach, methods in development, however, have thus far been limited to clean, high-quality PET feedstocks, and require an energy-intensive melt-amorphization step ahead of enzymatic treatment. Here, high-crystallinity PET in mixed PET/cotton textiles could be directly and selectively depolymerized to terephthalic acid (TPA) by using a commercial cutinase from Humicola insolens under moist-solid reaction conditions, affording up to 30±2 % yield of TPA. The process was readily combined with cotton depolymerization through simultaneous or sequential application of the cellulase enzymes CTec2®, providing up to 83±4 % yield of glucose without any negative influence on the TPA yield.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.085
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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 head0.006
GPT teacher head0.207
Teacher spread0.201 · 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