Effects of FeCl3 doping on polymer-based thin film transistors
Bibliographic record
Abstract
Polymer-based thin film transistors (PTFTs) were fabricated on glass substrates with anodized Al2O3 as gate insulators. RR-P3HT (regioregular poly–3-hexylthiophene) and MEH-PPV [poly(2-methoxy-5-(2′-ethyl-hexyloxy)-1,4-phenylene vinylene)] were respectively used as semiconducting active layers for the transistors. A two orders of magnitude increase in field effect mobility (from 7.2×10−4 cm2/V s to 7.4×10−2 cm2/V s) deduced from electrical data of transistors fabricated using FeCl3 doped RR-P3HT was observed. This increase is believed to be mainly due to a large reduction in contact resistance (from 108 Ω to 103 Ω) to the source and drain Au contacts. The conductivity of RR-P3HT was found to increase only slightly with the doping. For MEH-PPV, doping with FeCl3 also decreased its contact resistance. However, it (4 GΩ) was still much larger than the channel (polymer) resistance (1 MΩ), leading to a slight improvement in its field effect mobility. Theoretically, contacts between Au and P3HT should have very small energy barrier heights (<0.2 eV) for hole injection. We believe that a negative vacuum level shift introduced by metal to organic interfacial dipoles might be the origin of this large energy barrier, as well as to large contact resistance.
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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) | 0.000 | 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 | 0.001 | 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".