Highly UV‐Sensitive and Responsive Benzothiophene/Dielectric Polymer Blend‐Based Organic Thin‐Film Phototransistor
Bibliographic record
Abstract
It is reported on drain current modulation by UV light, in an organic thin‐film phototransistor, based on a small molecule semiconductor 2,7‐dipentylbenzo[b]benzo[4,5]thieno[2,3‐d]thiophene (BTBT‐C5) blended with a linear unsaturated polyester (L‐upe) to form the active channel material. The electrical properties of the phototransistor (L‐upe+BTBT‐C5) and physical properties of thin‐films are evaluated by means of two‐ and three‐terminal current–voltage characteristics (in the dark and under UV light) and structure–morphology analysis, respectively. Upon illumination with UV light, a dramatic change in the electrical properties of the L‐upe+BTBT‐C5 transistors is observed, compared to low responsive control transistors based on a blend of poly(methyl methacrylate) and BTBT‐C5. Drain current is increased by more than six orders of magnitude with maximum photosensitivity and responsivity of 4.0 × 106 and 11.1 A W−1, respectively, using a VG = 0 V. Modulated photoelectrical properties are explained by structure–morphology characteristics and efficient charge trapping at the polymer/semiconductor interface due to the presence of electron‐withdrawing groups in the polymer. Fast rise time of 1.80 s and slow relaxation time of 24.27 s, estimated using bi‐exponential fitting models, confirm a charge trapping/releasing mechanism and reveal sensing‐memory properties of the devices.
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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".