Efficient calculation of electron paramagnetic resonance g-tensors by multireference configuration interaction sum-over-state expansions, using the atomic mean-field spin–orbit method
Bibliographic record
Abstract
Using the multireference configuration interaction method due to Grimme and Waletzke, combined with the atomic mean-field approximations for the efficient calculation of spin–orbit matrix elements, the g-tensors in second-order perturbation theory have been calculated for the main group radicals CO+, CN, BO, BS, MgF, AlO, O2, HCO, H2O+, NO2, CO2−, NF2, NO22−, O3−, ClO2, and H2CO+, and for the transition metal compounds ZnH, ZnF, and TiF3, using explicit sum-over-state expansions for up to 20 excited states. In most cases, a valence triple-zeta basis set with polarization functions has been employed. It is shown that the addition of diffuse functions to this basis set does not improve the g-tensor results, and in several instances leads to slower convergence of the sum-over-state expansion. The calculated g-tensors are in good agreement with experimental values, and with our previous multireference configuration interaction results available for 9 of the 19 radicals. Our results are shown to be equivalent to, or better than, values obtained by other theoretical methods. Examples of radicals for which g-tensor calculations presented problems in the past are AlO and TiF3. For AlO, we obtain Δg⊥=−1530 ppm (parts per million), compared with an experimental value of −1900 ppm in Ne matrix. Using the SVP (valence double-zeta plus polarization) basis set, Δg⊥ of TiF3 is calculated to be −115.3 ppt (parts per thousand), compared with experimental values of −111.9 and −123.7 ppt.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".