Transferable Atom-Centered Potentials for the Correction of Basis Set Incompleteness Errors in Density-Functional Theory
Bibliographic record
Abstract
Recent progress in the accurate calculation of noncovalent interactions has enabled density-functional theory (DFT) to model systems relevant in biological and supramolecular chemistry. The application of DFT methods using atom-centered Gaussian basis sets to large systems is limited by the number of basis functions required to accurately model thermochemistry and, in particular, weak intermolecular interactions. Basis set incompleteness error (BSIE) arising from the use of incomplete basis sets leads to erroneous intermolecular energies, bond dissociation energies, and structures. In this article, we develop a correction for BSIE in DFT calculations using basis set incompleteness potentials (BSIP). BSIPs are atom-based one-electron potentials (ACPs) with the same functional form as effective core potentials (ECP) that are designed to correct the effects of BSIE in properties that are linear mappings of the energy. We present a systematic way of developing general, error-correcting ACPs and apply this technique to generate BSIPs for eight common elements in organic and biological systems (H, C, N, O, F, P, S, and Cl). Two BSIPs were optimized for use with the scaled MINI (MINIs) and MINIs(d) basis sets and were designed to correct for the impacts of BSIE on noncovalent binding energies and intra/intermolecular geometries. BSIPs developed for use with 6-31G*, pc-1, and 6-31+G** basis sets also correct for the effects of BSIE on bond dissociation energies, which enables the study of chemical reactions in very large systems. BSIPs can be used with any density functional in any electronic structure program that implements ECPs. Our BSIPs add very little to the computational cost provided an efficient ECP implementation is used. Our results support the use of BLYP-D3/MINIs-BSIP as a computationally inexpensive and more accurate alternative to other approaches (e.g., B3LYP/6-31G* and BP86/6-31G*) in protein and supramolecular structural studies.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".