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Record W4404572336 · doi:10.1103/physrevb.110.184517

Computationally efficient method for calculating electron-phonon coupling for high-throughput superconductivity screening

2024· article· en· W4404572336 on OpenAlexaff
Oliver A. Dicks, Kateryna Foyevtsova, Ilya Elfimov, Rohit P. Prasankumar, G. A. Sawatzky

Bibliographic record

VenuePhysical review. B./Physical review. B · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSuperconductivity in MgB2 and Alloys
Canadian institutionsUniversity of British Columbia
FundersEngineering and Physical Sciences Research Council
KeywordsSuperconductivityCoupling (piping)ThroughputElectronPhononPhysicsCondensed matter physicsHigh-throughput screeningComputer scienceMaterials scienceQuantum mechanicsChemistryTelecommunications

Abstract

fetched live from OpenAlex

Using a computationally inexpensive frozen phonon approach we have developed a technique which can be used to screen large unit cell materials and systems for enhanced superconducting critical temperatures. The method requires only density functional theory calculated electronic band structures of phonon modes corresponding to atomic displacements for various materials. We have applied this method to well-known conventional superconductors including ${\mathrm{MgB}}_{2}$, ${\mathrm{H}}_{3}\mathrm{S}$ and other hydrides as examples.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.800
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.032
GPT teacher head0.425
Teacher spread0.392 · 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 designTheoretical or conceptual
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

Citations2
Published2024
Admission routes1
Has abstractyes

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