Characterization of Metal–Organic Frameworks: Unlocking the Potential of Solid-State NMR
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Bibliographic record
Abstract
Conspectus An exciting advance in materials science is the discovery of hybrid organic–inorganic solids known as metal–organic frameworks (MOFs). Although they have numerous important applications, the local structures, specific molecular-level features, and guest behaviors underpinning desirable properties and applications are often unknown. Solid-state nuclear magnetic resonance (SSNMR) is a powerful tool for MOF characterization as it provides information complementary to that from X-ray diffraction (XRD). We describe our novel pursuits in the three primary applications of SSNMR for MOF characterization: interrogating the metal center, targeting linker molecules, and probing guests. MOFs have relatively low densities, and the incorporated metals are often quadrupolar nuclei, making SSNMR detection difficult. Recently, we examined the local structures of metal centers (i.e., 25 Mg, 47/49 Ti, 63/65 Cu, 67 Zn, 69/71 Ga, 91 Zr, 115 In, 135/137 Ba, 139 La, 27 Al) in representative MOFs by SSNMR at a high magnetic field of 21.1 T, addressing several important issues: (1) resolving chemically and crystallographically nonequivalent metal sites; (2) exploring the origin of disorder around metals; (3) refining local metal geometry; (4) probing the effects of activation and adsorption on the metal local environment; and (5) monitoring in situ phase changes in MOFs. Organic linkers can be characterized by 1 H, 13 C, and 17 O SSNMR. Although the framework structure can be determined by X-ray diffraction, hydrogen atoms cannot be accurately located, and thus the local structure about hydrogen is poorly characterized. Our work demonstrates that magic-angle spinning (MAS) experiments at very high magnetic field along with ultrafast spinning rates and isotope dilution enables one to obtain ultrahigh resolution 1 H MAS spectra of MOFs, yielding structural information truly complementary to that obtained from single-crystal XRD. Oxygen is a key constituent of many important MOFs but 17 O SSNMR work on MOFs is scarce due to the low natural abundance of 17 O. 17 O enriched MOFs can now be prepared in an efficient and economically feasible manner using solvothermal approaches involving labeled H 2 17 O water; the resulting 17 O SSNMR spectra provide distinct spectral signatures of various key oxygen species in representative MOFs. MOFs are suitable for the capture of the greenhouse gas CO 2 and the storage of energy carrier gases such as H 2 and CH 4 . A better understanding of gas adsorption obtained using 13 C, 2 H, and 17 O SSNMR will enable researchers to improve performance and realize practical applications for MOFs as gas adsorbents and carriers. The combination of SSNMR with XRD allows us to determine the number of adsorption sites in the framework, identify the location of binding sites, gain physical insight into the nature and strength of host–guest interactions, and understand guest dynamics.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it