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>
Bibliographic record
Abstract
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 $T\ensuremath{\ll}{T}_{c}$.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.091 | 0.025 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".