An Assessment of µ-Czochralski, Single-Grain Silicon Thin-Film Transistor Technology for Large-Area, Sensor and 3-D Electronic Integration
Bibliographic record
Abstract
Single-grain (SG) thin-film transistors (TFTs) fabricated inside location-controlled silicon grains using the mu-Czochralski method are benchmarked for analog and RF applications. Each silicon grain is defined by excimer laser recrystallization of polysilicon. Thin-film transistors may be fabricated in this manner on silicon or low-cost flexible plastic substrates as processing temperatures remain below 350degC, making the SG-TFT a potential enabling technology for large-area highly integrated electronic systems or systems-in-package with low manufacturing cost. Operational amplifier and voltage reference circuits of varying complexity were designed and measured in order to evaluate the effects of channel position and processing variation on analog circuits. A two-stage telescopic cascode operational amplifier fabricated in an experimental 1.5 mum SG-TFT technology demonstrates a DC gain of 55 dB (unity-gain bandwidth of 6.3 MHz), while a prototype CMOS voltage reference with a power supply rejection ratio (PSRR) of 50 dB is also demonstrated. With fTcomparable to single-crystal MOSFETs of comparable gate length, the SG-TFT can also enable RF circuits for wireless applications. A 12 dB gain RF cascode amplifier with on-chip inductors and operating in the 433 MHz ISM band is demonstrated. Excellent agreement with simulations is attained using a modified BSIM-SOI model extracted from measurements of experimental SG-TFT 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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".