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Record W2323569098 · doi:10.1021/cm501985d

Doping Poly(3-hexylthiophene) Nanowires with Selenophene Increases the Performance of Polymer-Nanowire Solar Cells

2014· article· en· W2323569098 on OpenAlexafffund
Han Yan, Jon Hollinger, Colin R. Bridges, George R. McKeown, Tamara Al-Faouri, Dwight S. Seferos

Bibliographic record

VenueChemistry of Materials · 2014
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationDuPontAlfred P. Sloan Foundation
KeywordsMaterials scienceNanowireDopingPolymerTernary operationNanotechnologySolar cellPolymerizationOptoelectronicsComposite material

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Developing novel materials analogous to poly(3-hexylthiophene) (P3HT) with increased absorption range and good one-dimensional self-assembly properties should increase photovoltaic performance while taking advantage of the well-established structure–property relationships developed for P3HT. Herein, we have fabricated novel polymer nanowires composed of P3HT doped with varying amounts of selenophene. Doping is accomplished by statistical polymerization and results in the incorporation of selenophene into the P3HT crystal lattice. Selenophene doping increases optical absorption far beyond what can be achieved by simply blending two materials. Polymer nanowire solar cells using selenphene-doped P3HT outperform native P3HT nanowire and corresponding ternary blend solar cells, reaching an overall maximum performance of >4% PCE. These are some of the highest values of any polymer nanowire solar cells and show that the selenophene-doping strategy is important for achieving high-performance devices.

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 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 score0.001
Threshold uncertainty score0.553

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.003
GPT teacher head0.162
Teacher spread0.159 · 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.

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

Citations50
Published2014
Admission routes2
Has abstractyes

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