Effects of dispersion corrections on the theoretical description of bulk metals
Bibliographic record
Abstract
The addition of a London dispersion correction to standard Kohn-Sham density-functional theory is essential for an accurate description of noncovalent interactions. While several dispersion-corrected density functionals (DC-DFs) have shown excellent performance for hard solids at ambient conditions, their transferability to metallic systems at ambient conditions or under isotropic compression has not been systematically examined. In this study, we assess the ability of selected DC-DFs to describe the equations of state (EOSs) of selected elemental metals and intermetallic compounds up to several gigapascals of pressure. EOS-derived properties, such as the unit-cell volume, the bulk modulus, and its pressure derivative, were then evaluated with and without thermal effects and the results compared with experimental reference data. We also assess the ability of the DC-DFs to predict the phase-transition pressures for a set of intermetallic compounds. The results of this study establish that London dispersion physics, and even dispersion contributions from the core electrons, is important in the description of bulk metals.
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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 | 0.002 |
| 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) | 0.001 | 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".