Low frequency noise in amorphous silicon thin-film transistors
Bibliographic record
Abstract
Hydrogenated amorphous silicon thin-film transistors (a-Si:H TFTs) are used as charge switches in flat-panel X-ray detectors. The inherent noise in the TFTs contributes to the overall noise figure of the detectors and degrades the image quality. Measurements of the noise provide an important parameter for modeling the performance of the detectors and contribute to understanding the origins of the noise that could lead to improvements in TFT design. We have measured the low-frequency, conductance noise in a-Si:H TFTs with an inverted staggered structure. We find that the noise power density spectrum fits well to a 1/fapower law with a near one. The noise power is inversely proportional to the gate voltage and also inversely proportional to channel length in both the linear and saturation regions. The results are in accord with theory. The Hooge parameter for the devices is approximately 1xW-3
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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 | 0.002 |
| 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".