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Record W2073010728 · doi:10.1002/qua.24624

A perspective on the relative merits of time‐dependent and time‐independent density functional theory in studies of the electron spectra due to transition metal complexes. An illustration through applications to copper tetrachloride and plastocyanin

2014· article· en· W2073010728 on OpenAlexafffund
Hristina R. Zhekova, Michael Seth, Tom Ziegler

Bibliographic record

VenueInternational Journal of Quantum Chemistry · 2014
Typearticle
Languageen
FieldChemistry
TopicPhotochemistry and Electron Transfer Studies
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaWestern Canada Research Grid
KeywordsTime-dependent density functional theoryDensity functional theoryChemistryExcitationPlastocyaninAdiabatic processHybrid functionalRelaxation (psychology)Spectral lineAtomic physicsMolecular physicsComputational chemistryPhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

Evaluation of the excitation energies in and plastocyanin was carried out with three different density functional theory (DFT) methods: time‐dependent DFT (TDDFT), ΔDFT, and Δself consistent field (SCF)‐DFT. Use was made of two local (local density approximation and BP86), two hybrid (B3LYP and PBE0), and one long‐range corrected (LC‐BP86) functionals to probe the effect of the exact exchange on the excitation energies. Some well‐known deficiencies observed in TDDFT were explained on the basis of lacking orbital relaxation and two‐electron terms not considered in adiabatic TDDFT. Δself consistent field (SCF)‐DFT reproduces well the position of the charge‐transfer excitations and yields results in best agreement with experiment regardless of the system or functional used. We conclude that the orbital relaxation and proper account of higher‐order terms neglected in adiabatic TDDFT are of great importance for the simulation of excitation spectra. © 2014 Wiley Periodicals, Inc.

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)0.001
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 score0.010
Threshold uncertainty score0.545

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.021
GPT teacher head0.281
Teacher spread0.260 · 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

Citations32
Published2014
Admission routes2
Has abstractyes

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