Quantitative Electron Delocalization in Solids from Maximally Localized Wannier Functions
Bibliographic record
Abstract
Electron delocalization is the quantum-mechanical principle behind chemical concepts such as aromaticity, resonance, and bonding. A common way to measure electron delocalization in the solid state is through the visualization of maximally localized Wannier functions, a method similar to using localized orbitals in molecular quantum chemistry. Although informative, this method can only provide qualitative information and is essentially limited by the arbitrariness in the choice of orbital rotation. Quantitative orbital-independent interatomic delocalization indices can be calculated by integration inside of atomic regions of probability densities obtained from the system's wave function. In particular, Bader's delocalization indices are very informative, but typically expensive to calculate. In this article, we present a fast method to obtain the localization and delocalization indices in a periodic solid under the plane-wave/pseudopotential approximation. The efficiency of the proposed method hinges on the use of grid-based atomic integration techniques and maximally localized Wannier functions. The former enables the rapid calculation of all atomic overlap integrals required in the construction of the delocalization indices. The latter allows discarding the overlaps between maximally localized Wannier functions whose centers are far enough apart. Using the new method, all localization and delocalization indices in solids with dozens of atoms can be calculated in hours on a desktop computer. Illustrative examples are presented and studied: some simple and molecular solids, polymeric nitrogen, intermolecular delocalization in 10 phases of ice, and the self-ionization of ammonia under pressure. This work is an important step toward the quantitative description of chemical bonding in solids under pressure.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".