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Record W3011203309 · doi:10.1088/1361-648x/ab7f07

Accessing general relations for temperature coefficients of Raman shifts in 2D materials

2020· article· en· W3011203309 on OpenAlexaff
Nianbei Li, Junjie Liu

Bibliographic record

VenueJournal of Physics Condensed Matter · 2020
Typearticle
Languageen
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsUniversity of Toronto
FundersHuaqiao UniversityScience and Technology Commission of Shanghai MunicipalityNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsAnharmonicityPhononRaman spectroscopyCondensed matter physicsThermal expansionMaterials scienceTemperature coefficientThermal conductivityThermalThermodynamicsPhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

The temperature coefficient of Raman shifts, which regulates the linear-in-temperature dependence of Raman shifts, plays a vital role in the experimental determinations of thermal conductivities in two-dimensional (2D) materials. Originating from anharmonic phonon effects, however, its connection to the underlying phonon structure remains poorly understood. Here, we explore the possibility of a simple albeit general relation that relates temperature coefficients to frequencies of the associated phonon modes in 2D materials. Remarkably, by resorting to a renormalized phonon picture, we explicitly show that the ratio between the temperature coefficient of Raman shifts and the associated phonon frequency is almost a constant that is varied only among materials. Our general relation fits well to experimental results for typical 2D materials and may have implications for addressing the impact of anharmonic phonon effects on thermal conductivities in 2D materials.

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 categoriesInsufficient payload (model declined to judge)
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 score0.003
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.028
GPT teacher head0.266
Teacher spread0.238 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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