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Record W3046573713 · doi:10.1021/jacs.0c02810

Higher Magnetic Fields, Finer MOF Structural Information: <sup>17</sup>O Solid-State NMR at 35.2 T

2020· article· en· W3046573713 on OpenAlexafffund
Vinícius Martins, Jun Xu, Xiao-Ling Wang, Kuizhi Chen, Ivan Hung, Zhehong Gan, Christel Gervais, Christian Bonhomme, Shijia Jiang, Anmin Zheng, Bryan E. G. Lucier, Yining Huang

Bibliographic record

VenueJournal of the American Chemical Society · 2020
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsWestern University
FundersDivision of Materials ResearchState of FloridaNational Institute of General Medical SciencesNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsChemistrySolid-state nuclear magnetic resonanceSolid-stateNuclear magnetic resonanceNuclear magnetic resonance spectroscopyPhysical chemistryCrystallographyStereochemistryPhysics

Abstract

fetched live from OpenAlex

The spectroscopic study of oxygen, a vital element in materials, physical, and life sciences, is of tremendous fundamental and practical importance. 17 O 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, 17 O is a challenging nucleus to study via SSNMR, as it suffers from low sensitivity and resolution, owing to the quadrupolar interaction and low 17 O natural abundance. Herein, we report a significant advance in 17 O SSNMR spectroscopy. 17 O 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-Mg 3 (HCOO) 6 . The subtle 17 O 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 17 O 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 17 O 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.002

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.

Opus teacher head0.009
GPT teacher head0.258
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations70
Published2020
Admission routes2
Has abstractyes

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