Structural and Crystallographic Information from<sup>61</sup>Ni Solid-State NMR Spectroscopy: Diamagnetic Nickel Compounds
Bibliographic record
Abstract
Despite the significance of nickel compounds, NMR spectroscopy of the active nickel isotope 61 Ni remains a largely unexplored field. While nickel(0) compounds have been studied by 61 Ni NMR in solution, solid-state experiments have been limited to Knight shift studies of nickel metal and nickel intermetallics. In conjunction with an NMR study of their ligands and 61 Ni relativistic computations, the first 61 Ni solid-state NMR (SSNMR) spectra of diamagnetic compounds are reported here. Specifically, bis(1,5-cyclooctadiene)nickel(0) [Ni(cod) 2 ], tetrakis(triphenylphosphite)nickel(0) [Ni[P(OPh) 3 ] 4 ], and tetrakis(triphenylphosphine)nickel(0) [Ni(PPh 3 ) 4 ] were studied. 61 Ni SSNMR spectra of Ni(cod) 2 were used to determine its isotropic chemical shift (δ iso = 965 ± 10 ppm), span (Ω = 1700 ± 50 ppm), skew (κ = −0.15 ± 0.05), quadrupolar coupling constant ( C Q = 2.0 ± 0.3 MHz), quadrupolar asymmetry parameter (η = 0.5 ± 0.2), and the relative orientation of the chemical shift and electric field gradient tensors. A solution study of Ni(cod) 2 in C 6 D 6 yielded a narrow 61 Ni signal, and the temperature dependence of δ iso ( 61 Ni) was assessed (δ iso being 936.5 ppm at 295 K). The solution is proposed as a secondary chemical shift reference for 61 Ni NMR in lieu of the extremely toxic Ni(CO) 4 primary reference. For Ni[P(OPh) 3 ] 4, 61 Ni SSNMR was used to infer the presence of two distinct crystallographic sites and establish ranges for δ iso in the solid state, as well as an upper bound for C Q (3.5 MHz for both sites). For Ni(PPh 3 ) 4, line shape fitting provided a δ iso value of 515 ± 10 ppm, Ω of 50 ± 50 ppm, κ of 0.5 ± 0.5, C Q of 0.05 ± 0.01 MHz, and η of 0.0 ± 0.2. The study of Ni(PPh 3 ) 4, in particular, demonstrates the utility of 61 Ni SSNMR given the lack of a previously reported crystal structure and transient nature of Ni(PPh 3 ) 4 in solution.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.170 | 0.044 |
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".