A Highly Stable Diketopyrrolopyrrole (DPP) Polymer for Chemiresistive Sensors
Bibliographic record
Abstract
Abstract A novel donor–acceptor (D‐A) conjugated polymer, poly[bis(2‐ethylhexyl)3‐(3′′,4′‐bis(dodecyloxy)‐[2,2′:5′,2′′‐terthiophen]‐5‐yl)‐1,4‐dioxo‐6‐(thiophen‐2‐yl)pyrrolo[3,4‐c]pyrrole‐2,5(1H,4H)‐dicarboxylate] (PDEB), comprising an electron‐accepting carbamate side‐chain bearing thiophene‐flanked diketopyrrolopyrrole (DPPTh) and an electron‐donating 3,3′‐bis(dodecyloxy)‐2,2′‐bithiophene (C12‐BTO) is synthesized. The carbamate side‐chains in this polymer can be thermally removed at a moderate temperature, forming an insoluble polymer poly[3‐(3″,4′‐bis(dodecyloxy)‐[2,2′:5′,2″‐terthiophen]‐5‐yl)‐6‐(thiophen‐2‐yl)‐2,5‐dihydropyrrolo[3,4‐c]pyrrole‐1,4‐dione] (PDNB) with high solvent resistance. PDNB has a high highest occupied molecular orbital energy level of −4.68 eV and a narrow band gap of 1.05 eV, which makes it dopable by HCl to form a stable conductive polymer PDNB:HCl with moderate conductivity of 0.24 S cm–1. A chemiresistive sensor based on PDNB:HCl can distinguish ten common volatile organic liquids with unique current–time profiles under a low operation voltage of 1 V. Importantly, a single sensor can be used many times and remain functional over a long period of time in air, indicating its extraordinary operational and environmental stability. The results demonstrate that PDNB is a promising material for reusable chemiresistive sensors.
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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 | 0.001 |
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.
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".