Influence of Polymer Gate Dielectric on Organic Field‐Effect Transistors: Interdependence of Molecular Weight, Solvent Polarity, and Surface Energy—A Case Study with PMMA and Pentacene
Bibliographic record
Abstract
Abstract The semiconductor/dielectric interface controls the performance of organic field‐effect transistors (OFETs). Herein, the influence of both the molecular weight and the polarity of the solvent of a poly(methyl methacrylate) (PMMA)‐based gate dielectric on the performance of pentacene OFETs is systematically investigated, by studying surface energy, surface roughness, morphology, leakage current, and capacitance of the dielectric. Various existing views on the role of the surface energy are considered while deriving a correlation. Larger pentacene grains are observed when the film is grown on high molecular weight‐PMMA films cast from high dipole moment‐solvent. The electrical properties of the corresponding OFETs show great improvement compared to those of OFETs fabricated with low molecular weight‐PMMA film as the gate dielectric, irrespective of the solvent. The authors attribute this enhanced performance to the increased surface energy of the polymeric dielectric which turns out to be a strong function of its molecular weight and the dipole moment of the solvent. Bias‐stress measurements on the OFETs confirm this correlation.
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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) | 0.000 | 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".