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Record W2909244361 · doi:10.1021/acs.jpcc.8b11815

Entropic Barriers Determine Adiabatic Electron Transfer Equilibrium

2019· article· en· W2909244361 on OpenAlexaff
Eric J. Piechota, Renato N. Sampaio, Ludovic Troian‐Gautier, Andrew B. Maurer, Curtis P. Berlinguette, Gerald J. Meyer

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2019
Typearticle
Languageen
FieldChemistry
TopicPhotochemistry and Electron Transfer Studies
Canadian institutionsUniversity of British Columbia
FundersOffice of ScienceBelgian American Educational Foundation
KeywordsAdiabatic processElectron transferExcited stateChemistryCoupling (piping)Intramolecular forceKinetic energyElectronAtomic physicsThermodynamicsChemical physicsMaterials sciencePhysical chemistryPhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

A thermodynamic analysis of the forward and reverse rate constants for adiabatic and nonadiabatic electron transfer equilibria over an 80 K temperature range is reported. The kinetic data were acquired by a spectroscopic approach that utilized excited state injection into TiO2 by sensitizers with two redox active groups linked through aromatic bridges that allow for intramolecular adiabatic (bridge = phenyl) or nonadiabatic (bridge = xylyl) electron transfer. Two impactful results were garnered from this analysis: (1) entropic barriers controlled the adiabatic electron transfer kinetics, and (2) the free energy barriers were unaffected by the degree of electronic coupling within experimental uncertainty. The second result stands in contrast to the common expectation that enhanced electronic coupling lowers the free energy barrier. This analysis provides new insights into how electronic coupling influences the free energy and barriers for electron transfer reactions.

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 categoriesInsufficient payload (model declined to judge)
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 score0.007
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.216
Teacher spread0.211 · 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.

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

Citations11
Published2019
Admission routes1
Has abstractyes

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