Nano-Crystalline &Amorphous Silicon PhotoTransistor Performance Analysis
Bibliographic record
Abstract
In this thesis, we compared electrical performance and stability of a novel nanocrystalline Si (nc-Si) thin film phototransistor (TFT) phototransistor and a regular amorphous silicon (a-Si:H) TFT phototransistor for large area imaging applications. The electrical performance parameters of nc-Si TFT phototransistor were extracted from the electrical (current-voltage) testing in dark and under illumination. The field-effect mobility is found to be around 1.2 cm2V-1s-1, the threshold voltage around 3.9V and the sub-threshold voltage slope around 0.47V/Dec. Optical properties of nc-Si TFT phototransistor have been evaluated under the green light illumination in the range of 1014 – 1017 lum, and the photocurrent gain and the external quantum efficiency were extracted from the experimental results. By comparing the results with those for a-Si:H TFTs measured under the same conditions, we found that nc-Si TFT has higher photo current gain under low illumination intensity, 5 ×1014 to 7 ×1015 lum. This thesis shows the relations bewteen the photo current gain, the external quantum efficiency, TFT drain and TFT gate bias; the photo current gain and the external quantum efficiency can be controlled by the Vds and the Vgs.
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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) | 0.003 | 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".