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Record W2604605950 · doi:10.1063/1.4979572

Electron transfer from the perspective of electron transmission: Biased non-adiabatic intermolecular reactions in the single-particle picture

2017· article· en· W2604605950 on OpenAlexafffund
Kirk H. Bevan

Bibliographic record

VenueThe Journal of Chemical Physics · 2017
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIntermolecular forceElectron transferParticle (ecology)Adiabatic processPerspective (graphical)ElectronTransmission (telecommunications)Chemical physicsMolecular physicsAtomic physicsPhysicsMaterials scienceChemistryQuantum mechanicsPhotochemistryComputer scienceMoleculeTelecommunications

Abstract

fetched live from OpenAlex

In this work, we revisit Hopfield's formulation of non-adiabatic electron transfer between uncorrelated redox species within the single-particle picture description of electron transmission commonly applied in solid-state systems. The formulation is applied to a model system, similar to that often found in solid-state electron tunneling studies, consisting of redox species separated by an insulating tunneling barrier. Redox tunneling across such an insulator is predicted to demonstrate a marked asymmetry, ranging from one to three orders of magnitude between forward and reverse bias electron transfer rates, when reactants possess dissimilar reorganization energies. This significant asymmetry is shown to arise from trapezoidal reshaping of the integrated Gamow tunneling barrier and corresponding transmission probability under an applied bias. In general, this work aims to further bridge concepts between the electron transfer and transport communities.

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 score0.010
Threshold uncertainty score0.242

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 integrity0.0000.001
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 head0.225
Teacher spread0.216 · 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

Citations17
Published2017
Admission routes2
Has abstractyes

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