MétaCan
Menu
Back to cohort
Record W3196600366 · doi:10.1021/acs.jpclett.1c02465

Two- and Three-Dimensional <sup>13</sup>C–<sup>17</sup>O Heteronuclear Correlation NMR Spectroscopy for Studying Organic and Biological Solids

2021· article· en· W3196600366 on OpenAlexafffund
Ivan Hung, Zhehong Gan, Gang Wu

Bibliographic record

VenueThe Journal of Physical Chemistry Letters · 2021
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsQueen's University
FundersDivision of Materials ResearchNatural Sciences and Engineering Research Council of CanadaFlorida Department of State
KeywordsHeteronuclear moleculeChemistryCarbon-13 NMRSolid-state nuclear magnetic resonanceHomonuclear moleculeMagic angle spinningCarbon-13Nuclear magnetic resonance spectroscopyNuclear magnetic resonanceAnalytical Chemistry (journal)PhysicsMoleculeStereochemistryNuclear physics

Abstract

fetched live from OpenAlex

We report two- and three-dimensional (2D and 3D) 13C–17O heteronuclear correlation solid-state NMR experiments under magic-angle spinning (MAS) conditions. These experiments utilize the D-RINEPT (Dipolar-mediated Refocused Insensitive Nuclei Enhanced by Polarization Transfer) scheme with symmetry-based SR412 recoupling blocks for coherence transfer between 13C and 17O nuclei. First, a 2D 17O → 13C correlation experiment was performed for the [1-13C,17O]-Gly/Gly·HCl cocrystal and [U-13C, 1-17O]-α/β-d-glucose samples. Second, a 2D 17O → 13C MQ-D-RINEPT correlation experiment where the indirect dimension incorporates the multiple-quantum MAS (MQMAS) scheme was tested for obtaining isotropic 17O resolution with [U-13C, 1-17O]-α/β-d-glucose. Third, a new 3D 17O → 13C → 13C correlation experiment was demonstrated where 17O → 13C and 13C → 13C correlations are achieved by D-RINEPT and DARR (Dipolar Assisted Rotational Resonance) sequences, respectively (thus termed as a 3D D-RINEPT/DARR OCC experiment). This new 3D 17O NMR experiment is implemented with the aim for site-resolved solid-state 17O NMR studies.

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 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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score0.690

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.267
Teacher spread0.251 · 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 teacher head, 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

Citations12
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Physical Chemistry LettersSame topicAdvanced NMR Techniques and ApplicationsFrench-language works237,207