Green Solvent‐Processed Hemi‐Isoindigo Polymers for Stable Temperature Sensors
Bibliographic record
Abstract
Abstract A series of donor‐acceptor polymers, namely PTEB, PMEB, PEEB, and PPEB, are designed and synthesized for temperature sensing. The polymers are composed of hemi‐isoindigo as the acceptor unit, 3,3″‐bis(dodecyloxy)‐2,2″‐bithiophene as the donor unit, and thiophene as the spacer unit. Carbamate solubilizing side chains are used to increase the solubility of the polymers in a green solvent anisole. Furthermore, the carbamate side chains can be thermally removed to form solvent‐resistant polymers PTNB, PMNB, PENB, and PPNB, respectively. The removal of carbamate side chains also helps to elevate the highest occupied molecular orbital energy level of the polymer, thereby promoting p‐doping. PMNB, PENB, and PPNB films are doped with 2,3,5,6‐tetrafluoro‐7,7,8,8‐tetracyanoquinodimethane (F4TCNQ) and used for fabricating temperature sensors on flexible polyethylene terephthalate substrates. The sensors exhibit high temperature coefficient of resistance (TCR) of up to −1.92 (±0.125)% °C−1 at 20–60 °C. This is the highest TCR achieved to date for resistor‐type temperature sensors using a non‐composite single conductive polymer. High sensitivity, green solvent processability, and mechanical flexibility make these temperature sensors promising for use in low‐cost, ubiquitous applications.
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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".