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Record W2863325918 · doi:10.1002/anie.201801041

Singlet Fission for Photovoltaics with 130 % Injection Efficiency

2018· article· en· W2863325918 on OpenAlexaff
Andreas Kunzmann, Marco Gruber, Rubén Casillas, Johannes Zirzlmeier, Melanie Stanzel, Wolfgang Peukert, Rik R. Tykwinski, Dirk M. Guldi

Bibliographic record

VenueAngewandte Chemie International Edition · 2018
Typearticle
Languageen
FieldEngineering
TopicField-Flow Fractionation Techniques
Canadian institutionsUniversity of Alberta
FundersDeutsche Forschungsgemeinschaft
KeywordsPhotovoltaicsSinglet fissionFissionMaterials scienceOptoelectronicsSinglet statePhysicsPhotovoltaic systemNuclear physicsEngineeringElectrical engineeringNeutron

Abstract

fetched live from OpenAlex

Abstract A novel pentacene dimer ( P2 ) and a structurally analogous monomer ( P1 ) were synthesized for use in n‐type dye‐sensitized solar cells. In P2 , the triplet excited states formed by the rapid, spin‐allowed process singlet fission were expected to enable carrier multiplication in comparison to the slow, spin‐forbidden intersystem crossing seen in P1 . A meta ‐positioning of the two pentacenes and the carboxylate anchor were chosen in P2 to balance the intramolecular dynamics of singlet fission and electron injection. Electron injection from energetically low‐lying triplet excited states of pentacene units necessitated the intrinsic and extrinsic lowering of the Fermi level of the semiconductor. Indium‐zinc oxide in the presence of Li + was found to be the optimum choice for the photoelectrodes. Efficient electron injection from the triplet excited states of P1 and P2 was found, with a carrier multiplication of nearly 130 %.

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)0.0020.001

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 head0.011
GPT teacher head0.244
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 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

Citations65
Published2018
Admission routes1
Has abstractyes

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