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Record W2064620990 · doi:10.1021/jp3084309

Modeling Noncovalent Radical–Molecule Interactions Using Conventional Density-Functional Theory: Beware Erroneous Charge Transfer

2013· article· en· W2064620990 on OpenAlexafffund
Erin R. Johnson, Michela Salamone, Massimo Bietti, Gino A. DiLabio

Bibliographic record

VenueThe Journal of Physical Chemistry A · 2013
Typearticle
Languageen
FieldChemistry
TopicPhotochemistry and Electron Transfer Studies
Canadian institutionsNational Institute for NanotechnologyUniversity of Alberta
FundersWestern Canada Research Grid
KeywordsDensity functional theoryMoleculeCharge (physics)ChemistryAtomic orbitalChemical physicsComputational chemistryAcceptorMolecular orbitalAtomic physicsPhysicsQuantum mechanicsElectronOrganic chemistry

Abstract

fetched live from OpenAlex

Conventional density-functional theory (DFT) has the potential to overbind radical-molecule complexes because of erroneous charge transfer. We examined this behavior by exploring the ability of various DFT approximations to predict fractional charge transfer and by quantifying the overbinding in a series of complexes. It is demonstrated that too much charge is transferred from molecules to radicals when the radical singly unoccupied molecular orbitals are predicted to be erroneously too low in energy relative to the molecule highest occupied molecular orbitals, leading to excessive Coulombic attraction. In this respect, DFT methods formulated with little or no Hartree-Fock exchange perform most poorly. The present results illustrate that the charge-transfer problem is much broader than may have been previously expected and is not limited to conventional (i.e., molecule-molecule) donor-acceptor complexes.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.249
Teacher spread0.229 · 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 designSimulation or modeling
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

Citations49
Published2013
Admission routes2
Has abstractyes

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