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Record W2738587265 · doi:10.1063/1.4985548

Electronic transition in solid Nb at high pressure and temperature

2017· article· en· W2738587265 on OpenAlexafffund
Innocent C. Ezenwa, Richard A. Secco

Bibliographic record

VenueJournal of Applied Physics · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectrical resistivity and conductivityIsothermal processExtrapolationCondensed matter physicsThermal conductivityThermodynamicsMaterials scienceTransition temperatureChemistrySuperconductivityPhysics

Abstract

fetched live from OpenAlex

The electrical resistivity of high purity solid Nb has been measured at fixed pressures up to 5 GPa in a large volume press and temperatures up to ∼1900 K. The expected resistivity decrease with pressure and increase with temperature were found. A transition was observed in the temperature dependence of resistivity at high temperature. The transition is discussed in terms of the effects of pressure and temperature on the electronic band structure of Nb causing a resistivity behavior characteristic of a change from the “minus group” to the “plus group.” Extrapolation of the pressure dependence of the transition temperature suggests that Nb would show plus group behavior at room T at an estimated pressure of ∼27 ± 7 GPa. The electronic thermal conductivity was calculated using the Wiedemann-Franz law and was in very good agreement with 1 atm data. We show that the temperature dependence of the calculated electronic thermal conductivity increases with a steep slope from room temperature up to the electronic transition temperature for all fixed pressures. Above the transition temperature, the T-dependence of electronic thermal conductivity remained constant at 2 GPa and exhibited an increasingly negative slope at higher pressures. The isothermal pressure-dependence of electronic thermal conductivity is positive.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score0.326

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 science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.199
Teacher spread0.195 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations16
Published2017
Admission routes2
Has abstractyes

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