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Record W3016480086 · doi:10.1021/acsomega.0c00383

Benzo[<i>b</i>]selenophene/thieno[3,2-<i>b</i>]indole-Based N,S,Se-Heteroacenes for Hole-Transporting Layers

2020· article· en· W3016480086 on OpenAlexaff
Nadezhda S. Demina, Nikolay A. Rasputin, Роман А. Иргашев, A. R. Tameev, Natalia V. Nekrasova, Gennady L. Rusinov, Jean‐Michel Nunzi, Valery N. Charushin

Bibliographic record

VenueACS Omega · 2020
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsQueen's University
FundersRussian Science FoundationMinistry of Education and Science of the Russian Federation
KeywordsIndole testStereochemistryChemistry

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Two series of new N,S,Se-heteroacenes, namely, 6 H -benzo[4′,5′]selenopheno[2′,3′:4,5]thieno[3,2- b ]indoles and 12 H -benzo[4″,5″]selenopheno[2″,3″:4′,5′]thieno[2′,3′4,5]thieno[3,2- b ]indoles, were successfully obtained using an effective strategy based on Fiesselmann thiophene and Fischer indole synthesis. The new molecules exhibit a large optical band gap (2.82 eV < E g opt < 3.23 eV) and their highest occupied molecular orbital (HOMO) energy formed by the plane π-core ranges between −5.2 and −5.6 eV, with the narrower optical band gap and lower HOMO level corresponding to selenated heteroacenes. In thin solid films of the heteroacenes, hole mobility measured using the conventional CELIV technique ranges between 10 –5 and 10 –4 cm 2 ·V –1 ·s –1 . All these make the proposed condensed-ring compounds a promising platform for the development of hole-transporting materials applicable in organic electronics.

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 score0.003
Threshold uncertainty score0.010

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)0.0030.001

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 head0.021
GPT teacher head0.219
Teacher spread0.198 · 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

Citations21
Published2020
Admission routes1
Has abstractyes

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