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Record W4405173969 · doi:10.48550/arxiv.2412.05062

Heat transport in crystalline organic semiconductors: coexistence of phonon propagation and tunneling

2024· preprint· en· W4405173969 on OpenAlexfundno aff
Lukas Legenstein, Lukas Reicht, Sandro Wieser, Michele Simoncelli, Egbert Zojer

Bibliographic record

VenuearXiv (Cornell University) · 2024
Typepreprint
Languageen
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilQueen's UniversityTU Graz, Internationale Beziehungen und MobilitätsprogrammeUlster UniversityAustrian Science FundQueen's University Belfast
KeywordsQuantum tunnellingPhononCondensed matter physicsOrganic semiconductorSemiconductorMaterials sciencePhysicsOptoelectronics

Abstract

fetched live from OpenAlex

Understanding heat transport in organic semiconductors is of fundamental and practical relevance. Therefore, we study the lattice thermal conductivities of a series of (oligo)acenes, where an increasing number of rings per molecule leads to a systematic increase of the crystals' complexity. Temperature-dependent thermal conductivity experiments in these systems disagree with predictions based on the traditional Peierls-Boltzmann framework, which describes heat transport in terms of particle-like phonon propagation. We demonstrate that accounting for additional phonon-tunneling conduction mechanisms through the Wigner Transport Equation resolves this disagreement and quantitatively rationalizes experiments. The pronounced increase of tunneling transport with temperature explains several unusual experimental observations, such as a weak temperature dependence in naphthalene's conductivity and an essentially temperature-invariant conductivity in pentacene. While the anisotropic conductivities within the acene planes are essentially material-independent, the tunneling contributions (and hence the total conductivities) significantly increase with molecular length in the molecular backbone direction, which for pentacene results in a surprising minimum of the thermal conductivity at 300K.

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 categoriesMeta-epidemiology (narrow)
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 score0.019
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.059
GPT teacher head0.186
Teacher spread0.127 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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