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Record W4416295528 · doi:10.3390/polym17223042

Enzymatic Degradation of PLA: Preferential Degradation of the Amorphous Fraction

2025· article· en· W4416295528 on OpenAlexafffund
Sarita Shrestha, Michael R. Snowdon, David B. Levin

Bibliographic record

VenuePolymers · 2025
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsNational Research Council CanadaUniversity of Manitoba
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsPolylactic acidDegradation (telecommunications)Amorphous solidDifferential scanning calorimetryMonomerPolymerLactic acidBiodegradationHydrolysis

Abstract

fetched live from OpenAlex

Polylactic acid (PLA), a widely used biobased biopolymer, is highly resistant to biodegradation under ambient conditions, contributing to persistent plastic pollution and posing potential environmental and health risks. This study investigates the enzymatic degradation of PLA by Proteinase K, a proteolytic hydrolase enzyme with the ability to degrade PLA, and explores the underlying mechanisms for degradation. Both amorphous and semi-crystalline PLA were treated with Proteinase K (2 mg/mL) at 37 °C over varying time periods. PLA degradation was evaluated using multiple techniques, including weight loss measurement, pH reduction, quantification of lactic acid monomer release by High-Performance Liquid Chromatography (HPLC), surface morphology analysis through Scanning Electron Microscopy (SEM), changes in thermal properties by Differential Scanning Calorimetry (DSC), and structural changes by X-Ray Diffraction (XRD). The data revealed that the degradation of amorphous regions of the PLA polymer was faster and more extensive than the crystalline regions of the polymer. Repeated enzymatic treatments significantly enhanced the degradation rate. Furthermore, Proteinase K showed a clear preference for degrading amorphous regions of the PLA, as evidenced by higher weight loss, sharper pH decline, higher lactic acid production, and more pronounced surface disruptions, such as visible gaps between degraded oligomer structures.

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 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 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 score0.037
Threshold uncertainty score0.488

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)0.0000.000

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 head0.020
GPT teacher head0.233
Teacher spread0.213 · 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 teacher head, 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

Citations3
Published2025
Admission routes2
Has abstractyes

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