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Record W2783689410 · doi:10.1002/chem.201705355

Pentacene Dimers as a Critical Tool for the Investigation of Intramolecular Singlet Fission

2018· review· en· W2783689410 on OpenAlexafffund
Constantin Hetzer, Dirk M. Guldi, Rik R. Tykwinski

Bibliographic record

VenueChemistry - A European Journal · 2018
Typereview
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaDeutsche Forschungsgemeinschaft
KeywordsPentaceneSinglet fissionIntramolecular forceChromophoreSinglet stateChemical physicsMaterials sciencePhotochemistryChemistryComputational chemistryNanotechnologyStereochemistryMoleculeTriplet stateOrganic chemistryPhysicsAtomic physics

Abstract

fetched live from OpenAlex

Abstract Singlet fission (SF) involves the spontaneous splitting of a photoexcited singlet state into a pair of triplets, and it holds great promise toward the realization of more efficient solar cells. Although the process of SF has been known since the 1960s, debate regarding the underlying mechanism continues to this day, especially for molecular materials. A number of different chromophores have been synthesized and studied in order to better understand the process of SF. These previous reports have established that pentacene and its derivatives are especially well‐suited for the study of SF, since the energetic requirement E (S 1 )≥2 E (T 1 ) is fulfilled rendering the process exothermic and unidirectional. Dimeric pentacene derivatives, in which individual pentacene chromophores are tethered by a “spacer”, have emerged as the system of choice toward exploring the mechanism of intramolecular singlet fission (iSF). The dimeric structure, and in particular the spacer, allows for controlling and tuning the distance, geometric relationship, and electronic coupling between the two pentacene moieties. This Minireview describes recent advances using pentacene dimers for the investigation of iSF.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.903
Threshold uncertainty score0.809

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.023
GPT teacher head0.268
Teacher spread0.244 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations159
Published2018
Admission routes2
Has abstractyes

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