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Record W2305765323 · doi:10.1139/cjp-2015-0677

Investigations on the local structure and the EPR parameters for the tetragonal Cu<sup>2+</sup> center in ZnSeF<sub>6</sub>·6H<sub>2</sub>O crystal

2016· article· en· W2305765323 on OpenAlexvenueno aff
Zesong Li

Bibliographic record

VenueCanadian Journal of Physics · 2016
Typearticle
Languageen
FieldChemistry
TopicInorganic Fluorides and Related Compounds
Canadian institutionsnot available
FundersEducation Department of Jiangxi Province
KeywordsElectron paramagnetic resonanceTetragonal crystal systemHyperfine structureOctahedronPhysicsCrystallographyLigand field theoryCrystal (programming language)Zero field splittingCrystal structureCluster (spacecraft)Condensed matter physicsIonMolecular physicsNuclear magnetic resonanceChemistryElectronAtomic physicsSpin polarizationQuantum mechanics

Abstract

fetched live from OpenAlex

The electron paramagnetic resonance (EPR) parameters (g factors g ∥ , g ⊥ and hyperfine structure constants A ∥ , A ⊥ ) and the local structure of the tetragonal Cu 2+ center in trigonal ZnSeF 6 ·6H 2 O crystal are theoretically investigated from the perturbation formulas of these parameters for a 3d 9 ion in tetragonally elongated octahedra. In the calculated formulas, the contributions to the EPR parameters from ligand orbital and spin–orbit coupling are included on the basis of the cluster approach in view of moderate covalency of the studied systems, the required crystal-field parameters are estimated from the superposition model, which enables correlation of the crystal-field parameters and hence the EPR parameters with the tetragonal distortion of the studied [Cu(H 2 O) 6 ] 2+ cluster. According to the calculations, the ligand octahedra around Cu 2+ are suggested to suffer relative elongation τ (≈ 0.085 Å) along the [001] (or C 4 ) axis for the tetragonal Cu 2+ centers in ZnSeF 6 ·6H 2 O crystal, due to the Jahn–Teller effect. The results are 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.

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 score0.162
Threshold uncertainty score0.430

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 science0.0000.000
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 head0.009
GPT teacher head0.181
Teacher spread0.172 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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