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Record W4414636295 · doi:10.1088/1361-648x/ae0dd6

On the question of second sound in germanium: a theoretical viewpoint

2025· article· en· W4414636295 on OpenAlexaff
Samuel Huberman, Chuang Zhang, Jamal Abou Haibeh

Bibliographic record

VenueJournal of Physics Condensed Matter · 2025
Typearticle
Languageen
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsMcGill University
FundersChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsEigenvalues and eigenvectorsScatteringObservableBoltzmann equationWork (physics)Boltzmann constantPhononOperator (biology)Sound (geography)

Abstract

fetched live from OpenAlex

eabg4677) wherein the observation of second sound in germanium is claimed. Through the lens of the phonon Boltzmann transport equation, we seek theoretical evidence of second sound. We begin with direct solutions to the linearized phonon Boltzmann transport equation (LBTE) for a frequency modulated heat source which do not reveal the presence of second sound. We then review the requirements imposed on the collision operator (or equivalently, the full scattering matrix) of the LBTE for the observation of driftless second sound as established by Hardy. By performing an eigendecomposition of the full scattering matrix, we show that the requirement that the smallest nonzero eigenvalue must be associated with an odd eigenvector is not satisfied. Finally, numerical solutions to the BTE under the relaxation time approximation in the 1D frequency-domain thermoreflectance experimental geometry demonstrate that phase lag alone is not a suitable experimental observable for inferring second sound. We conclude by suggesting alternative explanations that may explain the experimental data and discussing the need for a second sound 'smoking gun'.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.009
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.263
Teacher spread0.252 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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