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Record W2082627430 · doi:10.1021/ma302605e

Compositional Influence on the Regioregularity and Device Parameters of a Conjugated Statistical Copolymer

2013· article· en· W2082627430 on OpenAlexaff
Lisa M. Kozycz, Dong Gao, Dwight S. Seferos

Bibliographic record

VenueMacromolecules · 2013
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCopolymerConjugated systemPolymerMonomerMaterials sciencePolymer chemistryAcceptorPhysics

Abstract

fetched live from OpenAlex

We describe a conjugated statistical copolymer, poly(3-hexylthiophene)- stat -(3-thiohexylthiophene) (P3HT- s -P3THT), with 3-hexylthiophene:3-thiohexylthiophene monomer ratios ranging from 50:50 to 99:1. The copolymer is head-to-tail regioregular in both its hexylthiophene–hexylthiophene and hexylthiophene–thiohexylthiophene linkages, which is not observed in poly(3-thioalkylthiophene) homopolymers. The polymer sequence is random, and the 1 H NMR spectra have eight distinct aromatic signals that correspond to the eight possible HT–HT regioisomer triads and differ from the spectra expected for the corresponding block or homopolymer systems. When testing the copolymers in bulk heterojunction devices with a fullerene-derivative (PC 71 BM) acceptor, the copolymers have an 11–18% increase in the open-circuit voltage ( V oc ) relative to the P3HT:PC 71 BM device due to the deeper HOMO level of the 3-thiohexylthiophene unit. This increase is independent of copolymer composition over the 50:50 to 85:15 range and is still observed when there is just one 3-thiohexylthiophene unit in the polymer chain. This shows that statistical copolymers containing as low as 1% of a deep HOMO unit can be used to increase the V oc of the device relative to the parent polymer. All device parameters change in a nonlinear manner as a function of composition, which highlights the distinct properties that can be achieved with conjugated statistical copolymers.

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 score0.036
Threshold uncertainty score0.253

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 head0.007
GPT teacher head0.200
Teacher spread0.193 · 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

Citations34
Published2013
Admission routes1
Has abstractyes

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