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Record W3163606005 · doi:10.1139/er-2020-0117

New insights into the biodegradation of polylactic acid: from degradation to upcycling

2021· article· en· W3163606005 on OpenAlexvenueno aff
Bin Xu, Yinping Chen, Jie He, Shixiang Cao, Jiawei Liu, Rui Xue, Fengxue Xin, Xiujuan Qian, Jie Zhou, Weiliang Dong, Min Jiang

Bibliographic record

VenueEnvironmental Reviews · 2021
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsnot available
FundersHorizon 2020 Framework ProgrammeNational Natural Science Foundation of ChinaEuropean Commission
KeywordsBiodegradationPolylactic acidBiopolymerDegradation (telecommunications)Plastic wasteMicrobial biodegradationMineralization (soil science)Waste managementEnvironmentally friendlyChemistryEnvironmental scienceBiochemical engineeringMicroorganismOrganic chemistryPolymerBacteriaEngineeringBiologyEcology

Abstract

fetched live from OpenAlex

Owing to its biosynthetic and biodegradable properties, polylactic acid (PLA) is considered to be a most promising biopolymer that could play a crucial role as a potentially environmentally friendly material for a sustainable bioeconomy. However, its long-life cycle indicates that it cannot be easily degraded in nature. Therefore, understanding the biodegradation mechanism of PLA is important for reducing the impacts of waste plastic and waste disposal. With the recent development of molecular biology techniques, some studies have confirmed that specific groups of microorganisms can facilitate the biodegradation of PLA. Here, recent advances in the biodegradation of PLA (i.e., microbial and enzymatic degradation) and key factors affecting the degradation efficiency were reviewed. In addition, compared with complete degradation through mineralization, upcycling is also proposed as a more recyclable strategy for disposing of waste plastics.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.322
Threshold uncertainty score1.000

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)0.0010.001

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 head0.028
GPT teacher head0.239
Teacher spread0.211 · 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; both teacher heads agree on what is shown here.

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

Citations35
Published2021
Admission routes1
Has abstractyes

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