Direct Printed Flexible Organic Thin-Film Transistors With Cross-Linked PVA-Carrageenan Gate Dielectric
Bibliographic record
Abstract
There is an urgent need to develop and implement green materials in electronic systems to minimize the negative environmental impact of traditional electronic materials. In this letter, low-temperature cross-linked polyvinyl alcohol (PVA)-carrageenan (CAR) layer is presented as a green electronic gate dielectric for high-performance organic thin-film transistors (OTFT). A metal-free, flexible OTFT, direct printed on polyaniline films using poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) gel-based gate–source–drain layers, PVA-CAR gate dielectric, and 6,13-bis(triisopropylsilylethynyl)pentacene semiconductor, is tested and characterized compared with a more conventional organic gate dielectric polymethylmethacrylate. PVA-CAR metal–dielectric–metal capacitors showed excellent dielectric properties with an average absolute dielectric constant value of 22.36 and an absolute capacitance density value of 168 nF/cm2at 40 Hz under room temperature conditions. The PVA-CAR OTFT consistently demonstrated a low gate leakage current of 0.2–52.8 nA, a low device override voltage of VDS around -4V, andon/offcurrent ratio of 105–106. The direct printed PVA-CAR OTFT has excellent transistor characteristics for low-temperature processed organic transistors and show promise for application in sensors and green flexible electronics.
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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".