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Elasticity and thermal transport of commodity plastics

2019· article· en· W2979820828 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

VenuePhysical Review Materials · 2019
Typearticle
Languageen
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsUniversity of British Columbia
FundersAlexander von Humboldt-Stiftung
KeywordsPolymerElasticity (physics)van der Waals forceThermalThermal conductivityStiffnessThermal expansion

Abstract

fetched live from OpenAlex

Applications of commodity polymers are often hindered by their low thermal conductivity. In these systems, going from the standard polymers dictated by weak van der Waals interactions to biocompatible hydrogen-bonded smart polymers, the thermal transport coefficient $\ensuremath{\kappa}$ varies between 0.1 and 0.$4{\mathrm{Wm}}^{\ensuremath{-}1}\phantom{\rule{0.16em}{0ex}}{\mathrm{K}}^{\ensuremath{-}1}$. Combining all-atom molecular dynamics simulations with some experiments, we study thermal transport and its link to the elastic response of (standard and smart) commodity plastics. We find that there exists a maximum attainable stiffness (or sound-wave velocity), thus providing an upper bound of $\ensuremath{\kappa}$ for these solid polymers. The specific chemical structure and the glass transition temperature play no role in controlling $\ensuremath{\kappa}$, especially when the microscopic interactions are hydrogen-bonding based. Our results are consistent with the minimum thermal conductivity model and existing experiments. The effect of polymer stretching on $\ensuremath{\kappa}$ is also discussed.

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 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 score0.007
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0060.001

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 head0.015
GPT teacher head0.257
Teacher spread0.242 · 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