Superconductivity in lithium under high pressure investigated with density functional and Eliashberg theory
Bibliographic record
Abstract
Structural phase transitions and superconducting properties in three phases ($9R$, fcc, and $cI16$) of solid Li are investigated using a pseudopotential plane-wave method based on density functional perturbation theory. In particular, it is shown that phonon softening is responsible for a pressure-induced $\text{fcc}\ensuremath{\rightarrow}cI16$ transition as well as for a significant enhancement of electron-phonon coupling and superconducting transition temperature ${T}_{c}$ preceding this structural transformation. The nature of superconductivity in the fcc and $cI16$ phases is examined by solving the Eliashberg equations with the spectral function ${\ensuremath{\alpha}}^{2}F(\ensuremath{\omega})$ obtained from first-principles calculations and by evaluating the functional derivative $\ensuremath{\delta}{T}_{c}/\ensuremath{\delta}{\ensuremath{\alpha}}^{2}F(\ensuremath{\omega})$. The calculated ${T}_{c}$ reaches a maximum at pressure close to the $\text{fcc}\ensuremath{\rightarrow}cI16$ transition and is significantly reduced in the $cI16$ phase, in agreement with the trend observed experimentally. The variation in ${T}_{c}$ as a function of pressure is explained in terms of the functional derivative and shifts of the spectral weight.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".