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Record W2772019684 · doi:10.1021/acs.jpclett.8b00008

Polariton-Assisted Singlet Fission in Acene Aggregates

2018· article· en· W2772019684 on OpenAlexafffund
Luis Á. Martínez-Martínez, Matthew Du, Raphael F. Ribeiro, Stéphane Kéna‐Cohen, Joel Yuen-Zhou

Bibliographic record

VenueThe Journal of Physical Chemistry Letters · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStrong Light-Matter Interactions
Canadian institutionsPolytechnique Montréal
FundersDivision of ChemistryUniversity of California, San DiegoNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaConsejo Nacional de Ciencia y TecnologíaCanada Research Chairs
KeywordsPentacenePolaritonSinglet fissionQuantum yieldAceneExcitonPhotonYield (engineering)Singlet stateMaterials scienceRelaxation (psychology)FissionChemical physicsOrganic semiconductorPhotochemistryOptoelectronicsChemistryCondensed matter physicsPhysicsAtomic physicsExcited stateNanotechnologyFluorescenceOpticsQuantum mechanicsMoleculeLayer (electronics)

Abstract

fetched live from OpenAlex

Singlet fission is an important candidate to increase energy conversion efficiency in organic photovoltaics by providing a pathway to increase the quantum yield of excitons per photon absorbed in select materials. We investigate the dependence of exciton quantum yield for acenes in the strong light-matter interaction (polariton) regime, where the materials are embedded in optical microcavities. Starting from an open-quantum-systems approach, we build a kinetic model for time-evolution of species of interest in the presence of singlet quenchers and show that polaritons can decrease or increase exciton quantum yields compared to the cavity-free case. In particular, we find that hexacene, under the conditions of our model, can feature a higher yield than cavity-free pentacene when assisted by polaritonic effects. Similarly, we show that pentacene yield can be increased when assisted by polariton states. Finally, we address how various relaxation processes between bright and dark states in lossy microcavities affect polariton photochemistry. Our results also provide insights on how to choose microcavities to enhance similarly related chemical processes.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.009
GPT teacher head0.259
Teacher spread0.251 · 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 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

Citations161
Published2018
Admission routes2
Has abstractyes

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