Thiophene- and selenophene-based conjugated polymeric mixed ionic/electronic conductors
Bibliographic record
Abstract
Mixed ionic/electronic conductors (MIECs) are desirable materials for next-generation electronic devices and energy storage applications. Polymeric MIECs are attractive from the standpoint that their structure can be controlled and anticipated to have mechanically robust properties. Here, we prepare and investigate conjugated copolymers containing thiophene and selenophene repeat units and their homopolymer counterparts. Specifically, thiophene bearing a triethylene glycol (EG3) side chain was polymerized and copolymerized with dodecyl thiophene/selenophene monomers. The synthesis leads to a class of copolymers that contain either S or Se and are blocky in nature. The Li-ion conductivity of ionically doped copolymers, P3DDT-s-P3(EG3)T and P3DDS-s-P3(EG3)T (9.7 × 10−6 and 8.2 × 10−6 S/cm, respectively), was 3–4 fold higher than that of the ionically doped constituent homopolymer, P3(EG3)T (2.2 × 10−6 S/cm), at ambient conditions. The electronic conductivity of the oxidatively doped copolymers was significantly higher than that of the constituent homopolymer P3(EG3)T, and most notably, P3DDS-s-P3(EG3)T reached ∼7 S/cm, which is the same order of magnitude as poly(3-dodecylthiophene) and poly(3-dodecylselenophene), which are the highest oxidatively doped conductors based on control experiments. Our findings provide implications for designing new MIECs based on copolymerization and the incorporation of heavy atom heterocycles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".