Fast and Accurate Electrostatics in Metal Organic Frameworks with a Robust Charge Equilibration Parameterization for High-Throughput Virtual Screening of Gas Adsorption
Bibliographic record
Abstract
The charge equilibration (QEq) method has been parametrized to reproduce the ab-initio-derived electrostatic potential in a large and diverse training set of 543 metal organic frameworks (MOFs) containing the most popular Zn, Cu, and V structural building units (SBUs), 52 different organic carboxylate- and nitrogen-capped SBUs, and the 17 functional groups. The MOF electrostatic-potential-optimized charge scheme, or MEPO-QEq, was validated by evaluating the CO 2 uptake and heats of adsorption in the 543 member training set and a nonoverlapping 693 member validation set. Compared with the results obtained from ab-initio-derived charges, the MEPO-QEq charges give Pearson (linear) and Spearman (rank-order) correlation coefficients of >0.97 for these two sets. MEPO-QEq enables near-ab-initio quality nonbonded electrostatic interactions to be evaluated using the fast QEq method for fast and accurate virtual high-throughput screening of gas-adsorption properties in MOFs.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".