Van der Waals Interactions in Density-Functional Theory: Rare-Gas Diatomics
Bibliographic record
Abstract
The application of conventional GGA and meta-GGA density functionals to van der Waals interactions is fraught with difficulties. Conventional functionals do not contain the physics of the dispersion interaction. To make matters worse, the exchange part alone can yield anything from severe overbinding to severe over-repulsion depending on the choice of functional. We have assessed a variety of exchange GGAs for their ability to reproduce exact Hartree-Fock repulsion energies in rare-gas systems, and we find that PW86 [ Phys. Rev. B 1986 , 33 , 8800 ] performs remarkably well. The addition of a dynamical correlation GGA and the nonempirical dispersion model of Becke and Johnson [ J. Chem. Phys. 2007 , 127 , 154108 ] to PW86 gives a simple GGA plus dispersion theory yielding excellent rare-gas interaction curves for pairs involving He through Kr, with only two adjustable parameters for damping of the dispersion terms.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".