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Record W2268340554 · doi:10.1021/acs.iecr.5b03473

Thermoforming of Polylactic Acid Foam Sheets: Crystallization Behaviors and Thermal Stability

2015· article· en· W2268340554 on OpenAlexafffund
Richard Eungkee Lee, Yanting Guo, Harinder Tamber, Mirek Planeta, Siu N. Leung

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2015
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsThermoformingPolylactic acidMaterials scienceCrystallizationComposite materialExtrusionThermal stabilityPolystyreneGlass transitionChemical engineeringPolymer

Abstract

fetched live from OpenAlex

Biobased polylactic acid (PLA) foam packaging has been commercialized as an alternative to conventional polystyrene (PS) foam. However, PLA’s low glass transition temperature results in its inherently poor heat resistance and in turn limits the application to cold-fill packaging. In this study, low-density PLA foam sheet was extruded using an industry-scale tandem extrusion line and subsequently laminated with a PLA film casted from a high heat deflection temperature (HDT) PLA resin with a very low d -lactide monomer content (i.e., ∼0.4 mol %). Experimental results reveal that the crystallization behaviors of PLA foam sheets were sensitive to both thermoforming temperature and process-induced strain. Furthermore, this work has demonstrated that heat-resistant biodegradable PLA foam sheets could be realized by laminating them with solid films made of high-HDT PLA to serve as environmentally sustainable alternatives to PS foams in hot-fill packaging applications.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.000
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

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 head0.161
GPT teacher head0.309
Teacher spread0.148 · 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

Citations50
Published2015
Admission routes2
Has abstractyes

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