Higher Magnetic Fields, Finer MOF Structural Information: <sup>17</sup>O Solid-State NMR at 35.2 T
Bibliographic record
Abstract
The spectroscopic study of oxygen, a vital element in materials, physical, and life sciences, is of tremendous fundamental and practical importance. 17O solid-state NMR (SSNMR) spectroscopy has evolved into an ideal site-specific characterization tool, furnishing valuable information on the local geometric and bonding environments about chemically distinct and, in some favorable cases, crystallographically inequivalent oxygen sites. However, 17O is a challenging nucleus to study via SSNMR, as it suffers from low sensitivity and resolution, owing to the quadrupolar interaction and low 17O natural abundance. Herein, we report a significant advance in 17O SSNMR spectroscopy. 17O isotopic enrichment and the use of an ultrahigh 35.2 T magnetic field have unlocked the identification of many inequivalent carboxylate oxygen sites in the as-made and activated phases of the metal–organic framework (MOF) α-Mg3(HCOO)6. The subtle 17O spectral differences between the as-made and activated phases yield detailed information about host–guest interactions, including insight into nonconventional O···H–C hydrogen bonding. Such weak interactions often play key roles in the applications of MOFs, such as gas adsorption and biomedicine, and are usually difficult to study via other characterization routes. The power of performing 17O SSNMR experiments at an ultrahigh magnetic field of 35.2 T for MOF characterization is further demonstrated by examining activation of the MIL-53(Al) MOF. The sensitivity and resolution enhanced at 35.2 T allows partially and fully activated MIL-53(Al) to be unambiguously distinguished and also permits several oxygen environments in the partially activated phase to be tentatively identified. This demonstration of the very high resolution of 17O SSNMR recorded at the highest magnetic field accessible to chemists to date illustrates how a broad variety of scientists can now study oxygen-containing materials and obtain previously inaccessible fine structural information.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".