Simulation of a Low-Voltage Organic Transistor Compatible With Printing Methods
Bibliographic record
Abstract
The use of printing methods to deposit organic semiconductors promises to enable low-cost electronics. However, printing processes deposit thick and amorphous semiconductor layers that result in poorly performing organic field-effect transistors (OFETs) that generally are not appropriate for incorporation into commercially viable circuits. Another undesirable property of OFETs is their high operating voltage (~40 V). Organic metal-semiconductor FETs (OMESFETs) are proposed as alternatives to OFETs for use with printing methods. OMESFETs operate at low voltages (~5 V) and are expected to show better on/off current ratios than OFETs in a thick-film semiconductor. Simulations of OFETs and OMESFETs are performed assuming regioregular poly (3-hexylthiophene) (rr-P3HT) as the amorphous semiconductor layer with localized states close to the band edge. The results of the simulations show a current ratio of 104in the OMESFET and of 700 in the OFET for a 400-nm-thick semiconductor layer. Because the OMESFET operates in the depletion mode, versus the accumulation mode in the OFET, the calculated mobility in the OMESFET is two orders of magnitude smaller than that in the OFET. Simulations suggest that the OMESFET design offers performance advantages over printable OFETs, where low-voltage operation is demanded.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".