High Performance Organic Electronic Devices Based on a Green Hybrid Dielectric
Bibliographic record
Abstract
Abstract As the cost of electronics decreases, the demand for short‐term and single‐use applications, such as smart packaging, increases. Consequently, there is significant need for electronically active biodegradable materials to reduce the environmental impact of disposable electronic devices. A bilayer dielectric is developed based on environmentally friendly, low‐cost solution‐processable polymers, fabricated by thermally crosslinking a toluene diisocyanate‐terminated polycaprolactone (TPCL) layer with the hydroxyl groups of a poly(vinyl alcohol)/cellulose nanocrystal (CNC) blended dielectric (PVAC). Metal–insulator–metal (MIM) capacitors are fabricated and characterized under ambient and humid conditions. The incorporation of a TPCL layer in the bilayer dielectric results in a large reduction in moisture sensitivity when compared to neat PVAC without significantly altering the dielectric constant. When utilized as a dielectric in organic thin‐film transistors (OTFTs), the transistors prepared with the PVAC/TPCL dielectric have greater on/off ratios and hole mobilities, with reduced hysteresis compared to devices fabricated with PVAC. Furthermore, the fabricated OTFTs function at operating voltages six times lower when compared against a traditional silicon dioxide (SiO2) dielectric. The facile processing, combined with superior device performance, makes this green bilayer dielectric a promising candidate material for biodegradable disposable electronic 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".