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Record W3049421389 · doi:10.1103/physrevb.102.165125

Superconductivity in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mrow><mml:mi>La</mml:mi></mml:mrow><mml:mn>2</mml:mn></mml:msub><mml:msub><mml:mrow><mml:mi>Ni</mml:mi></mml:mrow><mml:mn>2</mml:mn></mml:msub><mml:mi>In</mml:mi></mml:math>

2020· article· lv· W3049421389 on OpenAlexafffund
Jannis Maiwald, I. I. Mazin, A. Gurevich, M. C. Aronson

Bibliographic record

VenuePhysical review. B./Physical review. B · 2020
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicRare-earth and actinide compounds
Canadian institutionsUniversity of British Columbia
FundersCanada First Research Excellence FundNational Science Foundation
KeywordsSuperconductivityCondensed matter physicsElectrical resistivity and conductivityMagnetismFerromagnetismSpecific heatMaterials sciencePhysicsCrystallographyChemistryQuantum mechanics

Abstract

fetched live from OpenAlex

We report here the properties of single crystals of ${\mathrm{La}}_{2}{\mathrm{Ni}}_{2}\mathrm{In}$. Electrical resistivity and specific heat measurements concur with the results of density functional theory calculations, finding that ${\mathrm{La}}_{2}{\mathrm{Ni}}_{2}\mathrm{In}$ is a weakly correlated metal, where the Ni magnetism is almost completely quenched, leaving only a weak Stoner enhancement of the density of states. Superconductivity is observed at temperatures below 0.9 K. A detailed analysis of the field and temperature dependencies of the resistivity, magnetic susceptibility, and specific heat at the lowest temperatures reveals that ${\mathrm{La}}_{2}{\mathrm{Ni}}_{2}\mathrm{In}$ is a dirty type-II superconductor with likely $s$-wave gap symmetry. Nanoclusters of ferromagnetic inclusions significantly affect the subgap states resulting in a nonexponential temperature dependence of the specific heat $C(T)$ at $T\ensuremath{\ll}{T}_{c}$.

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.924
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0020.004
Meta-epidemiology (broad)0.0010.006
Bibliometrics0.0010.004
Science and technology studies0.0020.003
Scholarly communication0.0020.004
Open science0.0050.004
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.5940.008

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 head0.024
GPT teacher head0.281
Teacher spread0.257 · 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

Citations10
Published2020
Admission routes2
Has abstractyes

Explore more

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