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Record W2070699102 · doi:10.1039/c3sc52809j

A<sup>115</sup>In solid-state NMR study of low oxidation-state indium complexes

2013· article· en· W2070699102 on OpenAlexaff
Hiyam Hamaed, Karen E. Johnston, B.F.T. Cooper, Victor V. Terskikh, Eric Ye, Charles L. B. Macdonald, Donna C. Arnold, Robert W. Schurko

Bibliographic record

VenueChemical Science · 2013
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsUniversity of OttawaSteacie Institute for Molecular SciencesNational Research Council CanadaUniversity of Windsor
Fundersnot available
KeywordsIndiumNMR spectra databaseChemistryNuclear magnetic resonance spectroscopyElectric field gradientSolid-state nuclear magnetic resonanceSpectral lineValence (chemistry)SpectroscopyCrystallographyAnalytical Chemistry (journal)Materials scienceNuclear magnetic resonanceElectric fieldPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

115In solid-state NMR (SSNMR) spectroscopy is applied to characterise a variety of low oxidation-state indium(I) compounds. 115In static wideline SSNMR spectra of several In(I) complexes were acquired with moderate and ultra-high field NMR spectrometers (9.4 and 21.1 T, respectively). 115In MAS NMR spectra were obtained with moderate and ultra-fast (>60 kHz) spinning speeds at 21.1 T. In certain cases, variable-temperature (VT) 115In SSNMR experiments were performed to study dynamic behaviour and phase transitions. The indium electric field gradient (EFG) and chemical shift (CS) tensor parameters were determined from the experimental spectra. With the aid of first principles calculations, the tensor parameters and orientations are correlated to the structure and symmetry of the local indium environments. In addition, calculations aid in proposing structural models for samples where single crystal X-ray structures could not be obtained. The rapidity with which high quality 115In SSNMR spectra can be acquired at 21.1 T and the sensitivity of the 115In NMR parameters to the indium environment suggest that 115In SSNMR is a powerful probe of the local chemical environments of indium sites. This work demonstrates that 115In NMR can be applied to a wide range of important materials for the purpose of increasing our understanding of structures and dynamics at the molecular/atomic level, especially for the characterisation of disordered, microcrystalline and/or multi-valence solids for which crystal structures are unavailable.

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 score0.007
Threshold uncertainty score0.494

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.296
Teacher spread0.282 · 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

Citations25
Published2013
Admission routes1
Has abstractyes

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