MétaCan
Menu
Back to cohort
Record W2915809153 · doi:10.1002/tcr.201800182

Applying Heteroatom Substitution in Organic Photovoltaics

2019· review· en· W2915809153 on OpenAlexafffund
Joseph G. Manion, Jenny R. Panchuk, Dwight S. Seferos

Bibliographic record

VenueThe Chemical Record · 2019
Typereview
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaAmerican Chemical Society
KeywordsHeteroatomOrganic solar cellThiopheneMaterials sciencePhotovoltaicsSubstitution (logic)PolymerizationPolymerNanotechnologyAbsorption (acoustics)Polymer solar cellPhotovoltaic systemChemistryOrganic chemistryComputer scienceEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Poly(3-alkylthiophene) (P3AT) has been a central focus of research on organic photovoltaics (OPVs) for well over a decade. Due to their controlled synthesis P3ATs have proven to be a vital model system for developing an understanding of the effects of polymer structure on optoelectronic properties and blend morphology in bulk heterojunction OPVs. Similar to their thiophene counterparts, selenophene and tellurophene can be polymerized in a controlled manner. As single atom substitution results in significant differences in absorption, charge transport and self-assembly these model systems provide a unique opportunity to probe fundamental structure-property relationships. In this account, we provide an overview of our work on copolymers of thiophene and selenophene and examine how the optoelectronic and morphological behavior of these materials can be strategically adjusted through polymer design. We also highlight recent developments on poly(3-alkyltellurophene) and comment on its future in fundamental and applied studies.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
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
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.031
GPT teacher head0.262
Teacher spread0.231 · 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 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

Citations17
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueThe Chemical RecordSame topicOrganic Electronics and PhotovoltaicsFrench-language works237,207