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Record W2104126868 · doi:10.1002/anie.201409888

Solid‐State <sup>17</sup>O NMR Spectroscopy of Paramagnetic Coordination Compounds

2015· article· en· W2104126868 on OpenAlexafffund
Xianqi Kong, Victor V. Terskikh, Rahul L. Khade, Yang Liu, Amber Rorick, Yong Zhang, Peng He, Yining Huang, Gang Wu

Bibliographic record

VenueAngewandte Chemie International Edition · 2015
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsWestern UniversityUniversity of OttawaQueen's University
FundersNational Institute of General Medical SciencesNational Institutes of HealthBruker BioSpinUniversity of OttawaOntario Innovation Trust
KeywordsParamagnetismChemistryHyperfine structureDensity functional theoryNuclear magnetic resonance spectroscopySolid-state nuclear magnetic resonanceNMR spectra databaseSpectroscopyCarbon-13 NMR satelliteCrystallographySpectral lineMetalPhysical chemistryNuclear magnetic resonanceFluorine-19 NMRComputational chemistryAtomic physicsStereochemistryPhysicsCondensed matter physics

Abstract

fetched live from OpenAlex

High-quality solid-state (17)O (I=5/2) NMR spectra can be successfully obtained for paramagnetic coordination compounds in which oxygen atoms are directly bonded to the paramagnetic metal centers. For complexes containing V(III) (S=1), Cu(II) (S=1/2), and Mn(III) (S=2) metal centers, the (17)O isotropic paramagnetic shifts were found to span a range of more than 10,000 ppm. In several cases, high-resolution (17)O NMR spectra were recorded under very fast magic-angle spinning (MAS) conditions at 21.1 T. Quantum-chemical computations using density functional theory (DFT) qualitatively reproduced the experimental (17)O hyperfine shift tensors.

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: none
Teacher disagreement score0.604
Threshold uncertainty score0.744

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 integrity0.0000.000
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 head0.020
GPT teacher head0.313
Teacher spread0.293 · 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

Citations55
Published2015
Admission routes2
Has abstractyes

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