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Quasi-Steady-State Measurement of Exciton Diffusion Lengths in Organic Semiconductors

2022· preprint· en· W3196513910 on OpenAlexfundno aff
Drew B. Riley, Oskar J. Sandberg, Wei Li, Paul Meredith, Ardalan Armin

Bibliographic record

VenuePhysical Review Applied · 2022
Typepreprint
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilNatural Sciences and Engineering Research Council of CanadaSwansea UniversityLlywodraeth CymruEuropean Regional Development FundUK Research and Innovation
KeywordsOrganic semiconductorDiffusionExcitonOrganic solar cellMaterials scienceSemiconductorPhotoluminescenceThermal diffusivityFullereneExcitationOptoelectronicsChemical physicsChemistryCondensed matter physicsPhysicsThermodynamicsQuantum mechanicsPolymer

Abstract

fetched live from OpenAlex

Understanding exciton diffusion in organic solar cells is crucial to understanding the recent rise in power-conversion efficiencies afforded by using non-fullerene acceptor molecules (NFAs). This study introduces a technique called pulsed-PLQY for measuring exciton diffusion lengths in organic semiconductors. Compared to existing techniques, pulsed-PLQY is faster, easier, requires less specialized equipment, and is less sensitive to experimental conditions. Using this method, the authors find that modern non-fullerene acceptor semiconductors exhibit longer diffusion lengths than their fullerene forerunners, and that this increase is driven by increases in diffusivity.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.138
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.018
GPT teacher head0.251
Teacher spread0.233 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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