Mechanically Robust Poly(ionic liquid) Block Copolymers as Self-Assembling Gating Materials for Single-Walled Carbon-Nanotube-Based Thin-Film Transistors
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The proliferation of high-performance thin-film electronics depends on the development of highly conductive solid-state polymeric materials. We report on the synthesis and properties investigation of well-defined cationic and anionic poly(ionic liquid) AB–C type block copolymers, where the AB block was formed by random copolymerization of highly conductive anionic or cationic monomers with poly(ethylene glycol) methyl ether methacrylate, while the C block was obtained by post-polymerization of 2-phenylethyl methacrylate. The resulting ionic block copolymers were found to self-assemble into a lamellar morphology, exhibiting high ionic conductivity (up to 3.6 × 10 –6 S cm –1 at 25 °C) and sufficient electrochemical stability (up to 3.4 V vs Ag + /Ag at 25 °C) as well as enhanced viscoelastic (mechanical) performance (storage modulus up to 3.8 × 10 5 Pa). The polymers were then tested as separators in two all-solid-state electrochemical devices: parallel plate metal–insulator–metal (MIM) capacitors and thin-film transistors (TFTs). The laboratory-scale truly solid-state MIM capacitors showed the start of electrical double-layer (EDL) formation at ∼10 3 Hz and high areal capacitance (up to 17.2 μF cm –2 ). For solid-state TFTs, low hysteresis was observed at 10 Hz due to the completion of EDL formation and the devices were found to have low threshold voltages of −0.3 and 1.1 V for p-type and n-type operations, respectively.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".