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Record W4417539544 · doi:10.1021/acs.jctc.5c01291

Failure of Hund’s J in Contemporary DFT+U+J: Insights from Spin-Crossover Fe(II) Complexes

2025· article· en· W4417539544 on OpenAlexaff

Bibliographic record

VenueJournal of Chemical Theory and Computation · 2025
Typearticle
Languageen
FieldMaterials Science
TopicMagnetism in coordination complexes
Canadian institutionsTrinity College
FundersEuropean Regional Development FundEngineering and Physical Sciences Research CouncilGrand Équipement National De Calcul IntensifTrinity College Dublin
KeywordsAdiabatic processLinear subspaceDensity functional theorySeries (stratigraphy)Valence (chemistry)Covalent bondHubbard modelInvariant (physics)Molecule

Abstract

fetched live from OpenAlex

The effect of the Hund's J terms in the DFT+U+J family of corrective functionals for (semi)local spin-density functional theory is assessed for a series of four octahedrally coordinated Fe(II) spin-crossover molecules spanning the covalent end of the ligand field spectrum. We report values and analyze trends for the Hubbard U and Hund's J parameters determined via minimum-tracking linear response for all valence atomic subspaces and relevant spin states. These parameters are then systematically applied by using simplified rotationally invariant Hubbard functionals to identify the simplest technique capable of yielding reliable adiabatic energy differences with respect to CASPT2/CC benchmarks. Consistent with previous findings, DFT+U improves the underlying DFT electronic density toward the CASPT2 reference, whereas the inclusion of an unlike-spin Hund's J energy term exerts only a marginal additional effect. Notably, the inclusion of this canonical, positively signed Hund's J term fails to remedy, and in fact, exacerbates the deficiencies of DFT+U in describing adiabatic energy differences in strongly covalent molecular systems. It further reveals intrinsic limitations of the contemporary DFT+U+J framework in simultaneously reproducing the charge distribution and energetics of these systems and hints at directions for its improvement.

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 score0.448
Threshold uncertainty score0.356

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)0.0000.000

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 head0.018
GPT teacher head0.293
Teacher spread0.275 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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