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Record W2964458121 · doi:10.1021/acs.joc.9b01654

Understanding the Photovoltaic Behavior of A–D–A Molecular Semiconductors through a Permutation of End Groups

2019· article· en· W2964458121 on OpenAlexafffund
Yuxuan Che, Yuliang Zhang, Yali Yang, Chenghao Liu, Ricardo Izquierdo, Steven Xiao, Dmitrii F. Perepichka

Bibliographic record

VenueThe Journal of Organic Chemistry · 2019
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsÉcole de Technologie SupérieureGLS Industries (Canada)Université du Québec à MontréalMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaMitacsFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsSemiconductorChemistryDensity functional theoryPhotovoltaic systemConjugated systemBand gapRhodanineMoleculePermutation (music)Polar effectOptoelectronicsPhotochemistryComputational chemistryMaterials scienceOrganic chemistryPhysicsPolymer

Abstract

fetched live from OpenAlex

The facile synthesis of a series of benzodithiophene (BDT)- and indacenodithiophene (IDT)-based A–D–A oligomers with different end groups is reported, and their properties are studied by optical spectroscopy, electrochemistry, and density functional theory calculations. The permutation of central and terminal units tunes the optoelectronic properties and photovoltaic device characteristics in a predictable way, aiding in the rational design of small molecule semiconducting materials. Among the three rhodanine-derived terminal groups, N -alkylthiazolonethione revealed the strongest electron-withdrawing character, resulting in the lowest band gap, the highest stability, and the best photovoltaic device performance. The crystallographic analysis of two IDT derivatives yielded a highly unusual three-dimensional packing of the conjugated backbone, which is likely responsible for the remarkable photovoltaic performance of such A–D–A semiconductors.

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 score0.000
Threshold uncertainty score0.001

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)0.0000.000

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 head0.016
GPT teacher head0.212
Teacher spread0.196 · 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

Citations20
Published2019
Admission routes2
Has abstractyes

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