NMR Shielding Calculations across the Periodic Table: Diamagnetic Uranium Compounds. 1. Methods and Issues
Bibliographic record
Abstract
In this and a subsequent article, the range of application for relativistic density functional theory (DFT) is extended to the calculation of nuclear magnetic resonance (NMR) shieldings and chemical shifts in diamagnetic actinide compounds. In the given first paper, various issues are explored that are related to this goal. It is shown that both the relativistic DFT-ZORA (zeroth-order regular approximation, as developed for NMR properties by Wolff, S. K.; Ziegler, T.; van Lenthe, E.; Baerends, E. J. J. Chem. Phys. 1999, 110, 7689) and the older quasi-relativistic (QR) DFT methods are applicable to these compounds. Another popular relativistic method, the use of relativistic effective core potentials (ECP) for the calculation of ligand NMR parameters, is tested as well. It is demonstrated that the ECP approach is beyond its limits for the very heavy actinide compounds. Comparing the ZORA and Pauli approaches, it is found that Pauli is more accurate for the 1 H NMR in UF 6 - n (OCH 3 ) n compounds whereas ZORA is more accurate in other cases. This is in contrast to earlier studies that always showed ZORA to be superior. The neglect of spin−orbit effects, leading to scalar relativistic approximations, is possible in some cases. In other cases, however, spin−orbit cannot be neglected. For instance in UF 5 (OCH 3 ), a large spin−orbit chemical shift of about 7 ppm has been found for the 1 H nuclei but only small effects for the other ligand nuclei. The large influences of the reference geometry, the reference compound, and the exchange correlation (XC) functional are demonstrated and discussed. The 19 F chemical shift tensor in UF 6 is well reproduced by the ZORA and QR methods. However, for the 19 F chemical shifts in UF 6 - n Cl n compounds, only some experimental trends could be reproduced by the calculations. Possible explanations are discussed for these shortcomings, including the choice of model XC functional.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".