Crystal structure refinements of borate dimorphs inderite and kurnakovite using 11B and 25Mg nuclear magnetic resonance and DFT calculations
Bibliographic record
Abstract
Borate minerals composed of [Bφ 3 ] triangles and/or [Bφ 4 ] tetrahedra (φ = O or OH) commonly exhibit complex polymerizations to form diverse polyanion groups. High-resolution solid-state magic angle spinning (MAS) 11 B and 25 Mg NMR spectroscopy at moderate to ultrahigh magnetic fields (9.4, 14.1, and 21.1 T) allows for very accurate NMR parameters to be obtained for the borate dimorphs, inderite, and kurnakovite, [MgB 3 O 3 (OH) 5 ·5H 2 O]. Improved agreement between experimental results and ab initio density functional theory (DFT) calculations using Full Potential Linear Augmented Plane Wave (FP LAPW) with WIEN2k validates the geometry optimization procedures for these minerals and permits refinements of the hydrogen positions relative to previous X-ray diffraction crystal structures. In particular, the optimized structures lead to significant improvements in the positions of the H atoms, suggesting that H atoms have significant effects on the 11 B and 25 Mg NMR parameters in inderite and kurnakovite. This study shows that combined high-resolution NMR spectroscopy and ab initio theoretical modeling provides an alternative method for the refinement of crystal structures, especially H positions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".