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Record W2121203175 · doi:10.1039/c3dt50528f

Study of an S = 1 NiII pincer electrocatalyst precursor for aqueous hydrogen production based on paramagnetic 1H NMR

2013· article· en· W2121203175 on OpenAlexaff
Oana R. Luca, Steven J. Konezny, Eric K. Paulson, Fatemah Habib, Kurt M. Luthy, Muralee Murugesu, Robert H. Crabtree, Víctor S. Batista

Bibliographic record

VenueDalton Transactions · 2013
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsParamagnetismChemistryDiamagnetismElectrocatalystLigand (biochemistry)Aqueous solutionCatalysisProton NMRChemical shiftReactivity (psychology)Pincer movementRelaxation (psychology)Inorganic chemistryPhysical chemistryElectrochemistryStereochemistryOrganic chemistryMagnetic field

Abstract

fetched live from OpenAlex

A tridentate NNN Ni(II) complex, shown to be an electrocatalyst for aqueous H2 production at low overpotentials, is studied by using temperature-dependent paramagnetic (1)H NMR. The NMR T1 relaxation rates, temperature dependence of the chemical shifts, and dc SQUID magnetic susceptibility are correlated to DFT chemical shifts and compared with the properties of a diamagnetic Zn analogue complex. The resulting characterization provides an unambiguous assignment of the six proton environments in the meridionally coordinating tridentate NNN ligand. The demonstrated NMR/DFT methodology should be valuable in the search for appropriate ligands to optimize the reactivity of 3d metal complexes bound to attract increasing attention in catalytic applications.

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 score0.001
Threshold uncertainty score0.003

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 communication0.0000.000
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 head0.011
GPT teacher head0.236
Teacher spread0.224 · 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

Citations14
Published2013
Admission routes1
Has abstractyes

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