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Record W4229044757 · doi:10.1002/marc.202200325

Wide Bandgap Polymer Donor with Acrylate Side Chains for Non‐Fullerene Acceptor‐Based Organic Solar Cells

2022· article· en· W4229044757 on OpenAlexafffund
Yi Yuan, Pankaj Kumar, Jenner H. L. Ngai, Xiguang Gao, Xu Li, Haitao Liu, Jin‐Liang Wang, Yuning Li

Bibliographic record

VenueMacromolecular Rapid Communications · 2022
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOrganic solar cellPolymer solar cellMaterials scienceSide chainThiopheneMethyl acrylateEnergy conversion efficiencyBand gapAcceptorSolar cellHybrid solar cellPolymerDielectricPhotochemistryCopolymerOptoelectronicsOrganic chemistryChemistryComposite material

Abstract

fetched live from OpenAlex

Organic semiconductors inherently have a low dielectric constant and hence high exciton binding energy, which is largely responsible for the rather low power conversion efficiency of organic solar cells as well as the requirements to achieve delicate bulk-heterojunction nanophase separation in the active layer. In this study, methyl acrylate as a weakly electron-withdrawing side chain for the electron rich thiophene to prepare a new building block, methyl thiophene-3-acrylate (TA), with increased polarity is used. A wide bandgap polymer PBDT-TA synthesized using TA and a benzodithiophene (BDT) monomer shows increased dielectric constant and reduced exciton binding energy compared to the analogous polymer PBDT-TC, which is made of BDT and methyl thiophene-3-carboxylate (TC). An organic solar cell device based on PBDT-TA:ITIC also achieves a higher power conversion efficiency of 10.47% than that of the PBDT-TC:ITIC based solar cell (9.68%). This work demonstrates the effectiveness of using acrylate side chains to increase the dielectric constant, reduce the exciton binding energy, and enhance the solar cell efficiency of polymer 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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.273
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.203
Teacher spread0.194 · 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.

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

Citations7
Published2022
Admission routes2
Has abstractyes

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