Communication: Correct charge transfer in CT complexes from the Becke’05 density functional
Bibliographic record
Abstract
It has been known for over twenty years that density functionals of the generalized-gradient approximation (GGA) type and exact-exchange-GGA hybrids with low exact-exchange mixing fraction yield enormous errors in the properties of charge-transfer (CT) complexes. Manifestations of this error have also plagued computations of CT excitation energies. GGAs transfer far too much charge in CT complexes. This error has therefore come to be called “delocalization” error. It remains, to this day, a vexing unsolved problem in density-functional theory (DFT). Here we report that a 100% exact-exchange-based density functional known as Becke’05 or “B05” [A. D. Becke, J. Chem. Phys. 119, 2972 (2003); 122, 064101 (2005)] predicts excellent charge transfers in classic CT complexes involving the electron donors NH3, C2H4, HCN, and C2H2 and electron acceptors F2 and Cl2. Our approach is variational, as in our recent “B05min” dipole moments paper [Dale et al., J. Chem. Phys. 147, 154103 (2017)]. Therefore B05 is not only an accurate DFT for thermochemistry but is promising as a solution to the delocalization problem as well.
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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 | 0.002 | 0.005 |
| 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 | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.048 | 0.009 |
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".