Calculation of the EPR g-Tensors of High-Spin Radicals with Density Functional Theory
Bibliographic record
Abstract
The second-order DFT approach of Schreckenbach and Ziegler to the computation of EPR g tensors of doublet radicals ( J. Phys. Chem. A 1997, 101, 3388), has been generalized to arbitrary spatially nondegenerate electronic states. The new technique is applied to a large number (47) of diatomic main-group radicals, in n Σ ( n > 2) ground states. Calculated principal components, of the EPR g tensors, are in a good agreement with experiment for main group radicals, with the average errors approaching the accuracy available in experimental matrix isolation studies (VWN average absolute error: 3.8 ppt). The agreement with experiment deteriorates for the mixed, main group−transition metal radicals (VWN error: 8.1 ppt) but the major trends in Δ g ⊥ values are still reproduced. The approach largely breaks down for radicals containing chemical bonds between two transition metal atoms (VWN error: 30 ppt). In all cases, the calculated g tensors are insensitive to the choice of the approximate exchange-correlation functional, with the simple VWN LDA, and gradient-corrected BP86 and RPBE functionals, giving essentially identical results. As an example of the possible future applications of the technique, we examine the g -tensor of the first 3 B u excited state of the trans- cation. Our calculations for this systems agree well with the experimental results, both for the magnitudes, and for the orientations of the principal components.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".