MétaCan
Menu
Back to cohort
Record W4403538398 · doi:10.1002/marc.202400517

Thermal Conductivity of Polymers: A Simple Matter Where Complexity Matters

2024· review· en· W4403538398 on OpenAlexaff
Debashish Mukherji

Bibliographic record

VenueMacromolecular Rapid Communications · 2024
Typereview
Languageen
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsUniversity of British Columbia
FundersMax-Planck-Institut für Polymerforschung
KeywordsContext (archaeology)Thermal conductivityAmorphous solidPolymerMaterials scienceWork (physics)Range (aeronautics)Engineering physicsThermoelectric materialsThermoelectric effectNanotechnologyThermodynamicsPhysicsComposite materialChemistryGeology

Abstract

fetched live from OpenAlex

Thermal conductivity coefficient κ measures the ability of a material to conduct a heat current. In particular, κ is an important property that often dictates the usefulness of a material over a wide range of environmental conditions. For example, while a low κ is desirable for the thermoelectric applications, a large κ is needed when a material is used under the high temperature conditions. These materials range from common crystals to commodity amorphous polymers. The latter is of particular importance because of their use in designing light weight high performance functional materials. In this context, however, one of the major limitations of the amorphous polymers is their low κ, reaching a maximum value of ≈0.4 W/Km that is 2-3 orders of magnitude smaller than the standard crystals. Moreover, when energy is predominantly transferred through the bonded connections, κ ⩾ 100 W/Km. Recently, extensive efforts have been devoted to attain a tunability in κ via macromolecular engineering. In this work, an overview of the recent results on the κ behavior in polymers and polymeric solids is presented. In particular, computational and theoretical results are discussed within the context of complimentary experiments. Future directions are also highlighted.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0040.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.007

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 head0.101
GPT teacher head0.344
Teacher spread0.243 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations13
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueMacromolecular Rapid CommunicationsSame topicThermal properties of materialsFrench-language works237,207