Process Development of Amorphous Indium Tin Gallium Oxide (ITGO) Thin Film Transistors
Bibliographic record
Abstract
The invention of portable electronic devices had a huge impact on the growing interest in flat panel displays. Since the first report in 2004 on amorphous Indium Gallium Zinc Oxide (a-IGZO) thin film transistors (TFTs), many companies have become interested in this material. The main advantage of a-IGZO over conventional amorphous silicon TFTs is its steep subthreshold, low off state current, and high channel mobility. However, the demand for larger displays with higher resolution and refresh rates is driving the demand for TFTs with higher performance, while avoiding the cost and complexity associated with low temperature polycrystalline silicon. There is an increased focus on alternative amorphous oxide semiconductors for use as TFT channel materials, due to the success of a-IGZO. The focus of this study is an investigation on Indium-Tin-Gallium-Oxide (ITGO) TFTs. Unpassivated bottom-gate devices were fabricated with a 30nm a-ITGO film, sputter deposited with 1% and 10% oxygen gas ambient, followed by a 2 hour anneal at 300oC in oxygen. Devices fabricated with PO2 = 1% resulted in a highly conductive channel. Devices with PO2 = 10% displayed semiconducting behavior and a shallow subthreshold. This trend held for all device dimensions tested; lengths of 24µm, 12µm, and 6µm with a width of 24µm. Compared to a-IGZO devices with a length of 4µm, ITGO devices with a length of 12µm exhibit an equivalent current drive, implying a 3 to 4 times improvement in mobility. Following aging in room ambient for multiple days, a-ITGO devices displayed improved yet left-shifted transfer characteristics. In unpassivated a-IGZO devices, similar behavior can also be observed and is attributed to an inhomogeneous trap distribution across the channel. As the exposed channel reacts with room air, oxygen vacancies are filled resulting in a more homogeneous trap distribution. A radial variation of device performance from the center of the wafer to the edge was also observed. When measuring devices towards the edge of the wafer a considerable left shift in transfer characteristics was observed. This variation in device performance is believed to be attributed to non-uniformities in the as deposited ITGO film and will be related to material optical parameters. Figure 1
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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) | 0.000 | 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".