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Record W2008929933 · doi:10.1063/1.3140273

Shared-mode assisted resonant energy transfer in the weak coupling regime

2009· article· en· W2008929933 on OpenAlexafffund
Emmanuelle Hennebicq, David Beljonne, Carles Curutchet, Gregory D. Scholes, R. Silbey

Bibliographic record

VenueThe Journal of Chemical Physics · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsUniversity of Toronto
FundersDivision of ChemistryNatural Sciences and Engineering Research Council of CanadaFonds De La Recherche Scientifique - FNRSNational Science Foundation
KeywordsFörster resonance energy transferExcitationAcceptorCoupling (piping)Work (physics)PhononPhysicsGaussianAtomic physicsResonant inductive couplingChromophoreEnergy transferAbsorption (acoustics)Sign (mathematics)Molecular physicsFluorescenceQuantum mechanicsMaterials scienceOptics

Abstract

fetched live from OpenAlex

Recent work has suggested that correlations in the environments of chromophores can lead to a change in the dynamics of excitation transfer in both the coherent and incoherent limits. An example of this effect that is relevant to many single molecule experiments occurs in the standard Forster model for resonant energy transfer (RET). The standard formula for the FRET rate breaks down when the electronic excitations on weakly interacting donor and acceptor couple to the same vibrational modes. The transfer rate can then no longer be factored into donor emission and acceptor absorption lineshapes, but must be recast in terms of a renormalized phonon reorganization energy accounting for the magnitude and sign of the excitation-vibration couplings. In this paper, we derive theoretically how the FRET rate depends on the shared mode structure and coupling, examine the simplified case of Gaussian lineshapes and then provide a quantitative calculation for a system of current interest.

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 score0.075
Threshold uncertainty score0.325

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 head0.017
GPT teacher head0.270
Teacher spread0.253 · 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

Citations60
Published2009
Admission routes2
Has abstractyes

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