Superconductivity in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Li</mml:mi><mml:mn>8</mml:mn></mml:msub><mml:mi>Au</mml:mi></mml:mrow></mml:math> electride
Bibliographic record
Abstract
Located at crystal voids, interstitial anion electrons (IAEs) have diverse topologies, which may be tuned to achieve different properties. Elucidating the role of IAEs in electron-phonon coupling (EPC), and using it to design electride superconductors, leads to the current prediction of superconducting ${\mathrm{Li}}_{8}\mathrm{Au}$ at high pressure. We suggest that the occurence of high-temperature superconductivity in electrides requires high-symmetry structures with hydrogenlike cages, an electron acceptor element to balance charges, and isolated IAEs coupled with medium-frequency vibrations. The uniquely designed ${\mathrm{Li}}_{8}\mathrm{Au}$ electride has a NaCl-type ($B1$) lattice, with atomic Au and cubic ${\mathrm{Li}}_{8}$ cages as bases. Isolated IAEs are formed at the cage centers, with extra charges taken up by Au. These octahedrally coordinated IAEs have a $p$-orbital-like attribute and are strongly coupled with atomic vibrations in the ${\mathrm{Li}}_{8}$ cages. The strong EPC in ${\mathrm{Li}}_{8}\mathrm{Au}$ results in a calculated ${T}_{c}$ of 73.1 K at 250 GPa, which is the highest ${T}_{c}$ reported to date for all the electrides. A slight substitutional Pt doping can enhance the ${T}_{c}$ of ${\mathrm{Li}}_{8}\mathrm{Au}$ to exceed liquid nitrogen temperature.
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 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".