Superconducting phase diagram in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Bi</mml:mi><mml:mi>x</mml:mi></mml:msub><mml:msub><mml:mi>Ni</mml:mi><mml:mrow><mml:mn>1</mml:mn><mml:mo>–</mml:mo><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math> thin films: The effects of Bi stoichiometry on superconductivity
Bibliographic record
Abstract
The Bi-Ni binary system has been of interest due to possible unconventional superconductivity aroused therein, such as time-reversal symmetry breaking in Bi/Ni bilayers or the coexistence of superconductivity and ferromagnetism in ${\mathrm{Bi}}_{3}\mathrm{Ni}$ crystals. While Ni acts as a ferromagnetic element in such systems, the role of the strong spin-orbit coupling element Bi in superconductivity has remained unexplored. In this work, we systematically studied the effects of Bi stoichiometry on the superconductivity of ${\mathrm{Bi}}_{x}{\mathrm{Ni}}_{1--x}$ thin films ($x\ensuremath{\approx}0.5--0.9$) fabricated via a composition-spread approach. The superconducting phase map of ${\mathrm{Bi}}_{x}{\mathrm{Ni}}_{1--x}$ thin films exhibited a superconducting composition region attributable to the intermetallic ${\mathrm{Bi}}_{3}\mathrm{Ni}$ phase with different amounts of excess Bi, revealed by synchrotron x-ray diffraction analysis. Interestingly, the mixed-phase region with ${\mathrm{Bi}}_{3}\mathrm{Ni}$ and Bi showed unusual increases in the superconducting transition temperature and residual resistance ratio as more Bi impurities were included, with the maximum ${T}_{\mathrm{c}}$ ($=4.2\phantom{\rule{0.28em}{0ex}}\mathrm{K}$) observed at $x\ensuremath{\approx}0.79$. A correlation analysis of structural, electrical, and magneto-transport characteristics across the composition variation revealed that the unusual superconducting ``dome'' is due to two competing roles of Bi: impurity scattering and carrier doping. We found that the carrier doping effect is dominant in the mild doping regime $(0.74\ensuremath{\le}x\ensuremath{\le}0.79)$, while impurity scattering becomes more pronounced at larger Bi stoichiometry.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.004 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.561 | 0.004 |
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; both teacher heads agree on what is shown here.
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".