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Record W4313535125 · doi:10.1021/acs.jpclett.2c03425

Uncovering the Mechanism of Thermally Activated Delayed Fluorescence in Coplanar Emitters Using Potential Energy Surface Analysis

2023· article· en· W4313535125 on OpenAlexafffund
Katrina Bergmann, Ryoga Hojo, Zachary M. Hudson

Bibliographic record

VenueThe Journal of Physical Chemistry Letters · 2023
Typearticle
Languageen
FieldEngineering
TopicOrganic Light-Emitting Diodes Research
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsPhotochemistryFluorescenceExcited statePhosphorescenceSinglet stateIntramolecular forceMaterials scienceAcceptorQuantum efficiencyChemical physicsOptoelectronicsChemistryAtomic physicsPhysicsStereochemistryOptics

Abstract

fetched live from OpenAlex

Planarized emitters exhibiting thermally activated delayed fluorescence (TADF) have attracted attention due to their narrow emission spectra, improved photostability, and high quantum yields, but with large singlet–triplet energy gaps (Δ E ST ) and no heavy atoms, the origin of their TADF remains a subject of debate. Here we prepare two isomeric, coplanar donor–acceptor compounds, with HMAT-2PYM performing dual TADF and room-temperature phosphorescence but with HMAT-4PYM exhibiting only prompt fluorescence. Although conventional TADF design principles suggest that neither isomer should exhibit TADF, we reveal differences in the excited state potential energy surfaces that enable spin-flip processes in only one isomer. We also find that hydrogen bonding is absent between the planar units of these emitters, despite earlier claims of intramolecular hydrogen bonding in similar compounds. Overall, this work demonstrates that potential energy surface analysis is a practical strategy for designing coplanar TADF materials that might otherwise be overlooked by conventional TADF design metrics.

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 score0.158
Threshold uncertainty score0.432

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.222
Teacher spread0.215 · 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

Citations21
Published2023
Admission routes2
Has abstractyes

Explore more

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