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Record W7133034280

Selenophene- and Thiophene-based π-Conjugated Polymer Gels

2022· dissertation· W7133034280 on OpenAlexaff
Sheng Li

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldMaterials Science
TopicSupramolecular Self-Assembly in Materials
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsConjugated systemPolymerCopolymerSelf-healing hydrogelsCovalent bondDopingAmphiphile
DOInot available

Abstract

fetched live from OpenAlex

In this thesis, I describe my effort in the synthesis of selenophene- and thiophene-based conjugated polymers and the development of organogels and hydrogels from them. In Chapter 1, I provide a general introduction on what are conjugated polymers and their applications. Then, a brief overview of programmable self-assembly of conjugated polymers including covalent programming and solid-state programming is introduced. It provides the background, importance, and recent works on the development of conjugated polymer gels. In Chapter 2, I describe the formation and characterization of selenophene- and thiophene-based conjugated homopolymer organogels. I demonstrate the first reported polyselenophene organogels and the result shows they are promising for the development of stretchable electronics. I have also developed a cycle-doping method to successfully dope the bulk gel films and offer the merit of being able to monitor the change in the film conductivity as the doping cycle increases at the same time. And this method can be applied to dope bulk films in general. In Chapter 3, I further expand the types of conjugated polymer organogels to selenophene- and thiophene-based statistical copolymers. I investigate the influence of molecular weight on the electrical performance of those statistical copolymers. I report the self-assembly behaviour of both the statistical copolymer thin films and their gels at low, medium, and high degrees of polymerization. And the doping mechanism of statistical copolymer gels is also determined. In Chapter 4, I examine the concept of forming hydrogels from full conjugated block copolymers. I demonstrate the synthesis of an amphiphilic block copolymer and the successful development of hydrogel from it. In Chapter 5, I summarize the main conclusions and offer outlooks for my thesis work. Future directions in the development of conjugated polymer organogels and hydrogels are described, and they could offer a better understanding and higher impact in the field of conjugated polymer gels.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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)0.0020.001

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 head0.014
GPT teacher head0.316
Teacher spread0.302 · 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 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
Published2022
Admission routes1
Has abstractyes

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