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Record W4402976045 · doi:10.1117/12.3028603

Unraveling the differences in disorder between flexible-chain and hairy-rod conjugated polymers

2024· article· en· W4402976045 on OpenAlexaff
Henry J. Kantrow, Spencer M. Yeager, Hongmo Li, Sergei Tretiak, Carlos Silva, Erin L. Ratcliff, Natalie Stingelin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicTextile materials and evaluations
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsConjugated systemPolymerChain (unit)Materials sciencePolymer scienceComposite materialPhysics

Abstract

fetched live from OpenAlex

Conjugated hairy-rod polymers, which have emerged as promising photocathode materials for solar-fuel production, are comprised of stiff, low-entropy backbones and complex side-chain substitutions, which collectively affect assembly compared to flexible-chain materials. Here, we unravel the relationship between structural and electronic disorder in a model hairy-rod polymer, PBTTT. We identify a narrow electronic density-of-states (DOS) distribution with weak spatial variations in PBTTT, while the prototypical flexible-chain polymer, P3HT, features an energetically broad, spatially variable DOS. We assign this observation to the fact that PBTTT is structurally homogeneous due to its liquid-crystalline-like behavior, contrary to the structurally heterogeneous, semi-crystalline P3HT. This view is further supported by 2D electronic spectroscopy, which reveals that PBTTT features dynamic electronic disorder, vs. P3HT, which exhibits primarily static electronic disorder. Collectively, our work provides understanding into the disordered energy landscape in conjugated hairy-rod polymers, towards accelerated materials discovery for renewable energy technologies.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0030.000

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 head0.038
GPT teacher head0.285
Teacher spread0.248 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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