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Record W2771803549 · doi:10.1002/cmr.a.21410

Complete multinuclear solid‐state <scp>NMR</scp> of metal‐organic frameworks: The case of α‐Mg‐formate

2016· article· en· W2771803549 on OpenAlex
Bryan E. G. Lucier, Yue Zhang, Yining Huang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueConcepts in Magnetic Resonance Part A · 2016
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsWestern University
Fundersnot available
KeywordsMicroporous materialSolid-state nuclear magnetic resonanceFormateMetal-organic frameworkMagic angle spinningChemistryHydrogen storageSolid-stateAdsorptionNuclear magnetic resonance spectroscopyHydrogenCrystallographyCatalysisPhysical chemistryOrganic chemistryNuclear magnetic resonancePhysics

Abstract

fetched live from OpenAlex

Abstract Metal‐organic frameworks ( MOF s) are exciting porous materials with a growing number of applications ranging from catalysis to gas storage. Establishing logical connections between the local MOF structure and its properties is not often straightforward, however, solid‐state NMR is a sensitive probe of local structure and can be used to shed light on processes such as guest adsorption and gas motion within MOF s. As illustrated using our recent works on the microporous α‐Mg‐formate (Mg 3 (HCOO) 6 ) MOF , complete multinuclear solid‐state NMR characterization of MOF s is now possible, and can provide unique insight that is not readily available through other methods. A wide variety of solid‐state NMR techniques have been employed, including direct‐excitation, cross‐polarization, fast magic‐angle spinning, and two‐dimensional experiments. New variable‐temperature 2 H solid‐state NMR data of deuterated hydrogen gas within α‐Mg‐formate and the resulting detailed dynamic information is also presented, analyzed, and discussed.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.733

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.015
GPT teacher head0.292
Teacher spread0.277 · 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