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Record W2902649523 · doi:10.1149/ma2018-02/32/1096

Thermal Transport across a Semiconductor/Semiconductor Interface: A First-Principles-Based Approach

2018· article· en· W2902649523 on OpenAlexaff
Jesse Maassen, Vahid Askarpour

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPhononSemiconductorCondensed matter physicsPhonon scatteringBoltzmann equationScatteringHeterojunctionMaterials scienceThermal conductivityBallistic conductionPhysicsOptoelectronicsOpticsThermodynamicsQuantum mechanics

Abstract

fetched live from OpenAlex

Controlling heat flow across material heterojunctions is important for thermoelectrics and thermal management of electronic devices. A clear physical understanding of what transport mechanism dominates near an interface can help benefit technology. We present a theoretical investigation of phonon transport across a semiconductor/semiconductor interface, specifically Si/Ge, and demonstrate how inelastic scattering and non-equilibrium effects play a key role. We treat phonon transport with the McKelvey-Shockley flux method, which is efficient, captures ballistic and non-equilibrium effects, inelastic scattering, and has shown excellent agreement with the more computationally-demanding Boltzmann equation. The Si and Ge phonon dispersions and 3-phonon scattering rates, serving as input for the transport modeling, are calculated from first-principles. The results show that, while the maximum phonon frequency in Si is nearly double that of Ge, significant heat currents are carried by the high-frequency Si phonons above the Ge cutoff. When approaching the interface, inelastic scattering redistributes energy to the phonon frequencies that can transfer elastically across the Si/Ge junction. We explain how this collective reorganization of phonons is driven by non-equilibrium effects near the interface. We also include a model for the contact resistance of an ideal interface, that depends on both phonon dispersions, which provides a lower limit for a given material combination. These results help provide clear physical insights into what controls phonon transport at semiconductor/semiconductor interfaces.

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)0.002
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.046
GPT teacher head0.277
Teacher spread0.231 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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