<sup>35</sup>Cl NMR of Metal‐Organic Frameworks: What Can We Learn?
Bibliographic record
Abstract
Abstract Metal‐organic frameworks (MOFs) are a diverse class of hybrid organic‐inorganic materials with a wide range of applications. Chlorine often plays a crucial role in MOF structures; the local environment about Cl significantly affects material properties and applications. It is shown that direct characterization of Cl local environments within MOFs using 35 Cl wideline solid‐state NMR (SSNMR) provides unique insights into the local electronic and chemical structure, including the Cl bonding mode. 35 Cl SSNMR provides clear information regarding hydrogen bonding within MOFs and also yields direct evidence of phase transitions. There is a strong correlation linking 35 Cl quadrupolar interaction parameters to local bond lengths and angles. It is also shown that 35 Cl SSNMR of MOFs can be effective when paramagnetic centers are directly bound to Cl, greatly expanding the applicability of this approach. Density functional theory calculations of quadrupolar interaction parameters are in good agreement with experimental values, particularly when dispersion corrections are used for geometry optimization. This work highlights the broad potential of 35 Cl SSNMR for investigating MOFs and invites further applications in the field.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 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 teacher head, 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".