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Record W2981280399 · doi:10.1039/c9sc04410h

Influence of the heavy-atom effect on singlet fission: a study of platinum-bridged pentacene dimers

2019· article· en· W2981280399 on OpenAlexafffund
Bettina S. Basel, Ryan M. Young, Matthew D. Krzyaniak, Ilias Papadopoulos, Constantin Hetzer, Yueze Gao, Nathan T. La Porte, Brian T. Phelan, Timothy Clark, Rik R. Tykwinski, Michael R. Wasielewski, Dirk M. Guldi

Bibliographic record

VenueChemical Science · 2019
Typearticle
Languageen
FieldChemistry
TopicPhotochemistry and Electron Transfer Studies
Canadian institutionsAlberta Hospital EdmontonUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaBayerisches Staatsministerium für Wissenschaft, Forschung und KunstOffice of ScienceFriedrich-Alexander-Universität Erlangen-NürnbergSolar Technologies go HybridBasic Energy SciencesGraduiertenschule für Molekulare Wissenschaften der Friedrich-Alexander-Universität Erlangen-NürnbergStudienstiftung des Deutschen VolkesU.S. Department of Energy
KeywordsPentaceneSinglet fissionExcited stateSinglet stateChemistryGround stateTriplet statePlatinumAtom (system on chip)ChromophoreSpin statesChemical physicsAtomic physicsPhotochemistryPhysicsPhysical chemistryElectrode

Abstract

fetched live from OpenAlex

) formation in both dimers. Using a combination of experiment and quantum chemical calculations, we are able to observe a transition from the CT-mediated to the direct SF mechanism and identify relevant factors that influence the mechanism that dominates SF in pentacene. Moreover, a combination of time-resolved optical and electron paramagnetic resonance spectroscopic data allows us to develop a kinetic model that describes the effect of enhanced spin-orbit couplings on the correlated triplet pair state.

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 score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.244
Teacher spread0.237 · 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

Citations41
Published2019
Admission routes2
Has abstractyes

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