A Solid-State NMR Method for Solution of Zeolite Crystal Structures
Bibliographic record
Abstract
Since zeolites are notoriously difficult to prepare as large single crystals, structure determination usually relies on powder X-ray diffraction (XRD). However, structure solution (i.e., deriving an initial structural model) directly from powder XRD data is often very difficult due to the diffraction phase problem and the high degree of overlap between the individual reflections, particularly for materials with the structural complexity of most zeolites. Here, we report a method for structure determination of zeolite crystal structures that combines powder XRD and nuclear magnetic resonance (NMR) spectroscopy in which the crucial step of structure solution is achieved using solid-state (29)Si double-quantum dipolar recoupling NMR, which probes the distance-dependent dipolar interactions between naturally abundant (29)Si nuclei in the zeolite framework. For two purely siliceous zeolite blind test samples, we demonstrate that the NMR data can be combined with the unit cell parameters and space group to solve structural models that refine successfully against the powder XRD data.
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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 | 0.001 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".