(Invited) Conducting Polymer Transistors Making Use of Activated Carbon Gate Electrodes
Bibliographic record
Abstract
The characteristics of the gate electrode have significant effects on the behaviour of organic electrochemical transistors (OECTs), which are intensively investigated for applications in the booming field of organic bioelectronics. In this work, high specific surface area activated carbon (AC) was used as gate electrode material in OECTs based on the conducting polymer poly(3,4-ethylenedioxythiophene) (PEDOT) doped with poly(styrene sulfonate) (PSS).1 We found that the high specific capacitance of the AC gate electrodes leads to high drain-source current modulation in OECTs. Cyclic voltammetry studies, where PEDOT:PSS is used as the working electrode (WE) and AC is used as the reference electrode (RE) and counter electrode (CE), show that high double-layer capacitance and absence of Faradaic processes permit the development of stable OECTs where the channel potential is uniquely determined by the applied gate bias. The intrinsic quasi-reference characteristics of AC electrodes make unnecessary the presence of an additional reference electrode to monitor the OECT channel potential. The ease of process of AC electrodes for in plane, flexible device architectures constitutes a step forward in the search of new electrode materials for OECTs to be used in iontronics, printed electronics, bio analytical sensing, and other organic bioelectronic devices.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".