Effect of Hydrogen on Reliability with Various Deposition Temperatures of Al<sub>2</sub>O<sub>3</sub> Gate Insulator in In-Ga-Zn-O Thin Film Transistors
Bibliographic record
Abstract
To achieve the next generation displays, it is becoming increasingly important to develop backplane technology with superior characteristics such as high mobility, high stability, and high transparency. Among the several candidates for suitable backplane in high definition display, amorphous In-Ga-Zn-O (a-IGZO) oxide semiconductor TFTs have attracted much interest due to its high mobility, optical transparency, and large area uniformity. However, due to the intrinsic problem of a-IGZO TFTs caused by oxygen vacancy and hydrogen, it is hard to control of threshold voltage (Vth) and stability under various stress conditions. One of them, hydrogen is the main factor closely related to reliability. According to previous studies, hydrogen acts as positive roles by defect passivation and also play negative roles in creating new defects in a-IGZO active layer. However, incorporation and diffusion of hydrogen into the active layer is an unavoidable issue during the TFTs fabrication, and it is important to control it so that hydrogen plays a positive role. So, in this study, we conducted experiments to verify the effect of hydrogen on the reliability by modifying the Al2O3 gate insulator layer (GI) deposition process using atomic layer deposition (ALD) method. In order to verify the relationship between the hydrogen and electrical properties of a-IGZO TFTs, we fabricated top gate bottom contact (TGBC) structures and applied different GI deposition temperature (Tdep) for controlling the amount of hydrogen. [1] Al2O3 GI deposited using trimethylaluminum (TMA) and H2O precursor. Each Tdep are 200, 250, 270 and 300 degree, respectively. As a result of Al2O3 single thin film analysis using secondary ion mass spectroscopy (SIMS) method, it was confirmed that the Al2O3 thin film deposited at high Tdep has a relatively small amount of hydrogen than the Al2O3 thin film deposited at low Tdep. And then, TFT devices a, b, c, and d were fabricated using Al2O3 GI with different Tdep of 200, 250, 270 and 300 degrees, respectively. As a result, there was no significant difference between the devices. All devices had subthreshold swing (SS), value of 0.178 ~ 0.225 V, turn on voltage (Von) of -0.16 ~ -0.44V, hysteresis of 0.13 ~ 0.27 V and field effect mobility (μFE) of 9.6 ~ 10.55 cm2/Vs. This trend was similar to positive bias temperature stress (PBTS) and negative bias temperature stress (NBTS) reliability. However, the reliability of negative bias illumination stress (NBIS) was significantly different for each device. Under the NBIS condition, the Vth shift of each TFT was -4.36 V for a TFT, -4.36 V for b TFT, -3.72V for c TFT, -2.48 V for d TFT. These results indicate that the NBIS characteristic is improved as the Tdep of Al2O3 GI increases and proves that reliability varies with the amount of hydrogen. This suggests that as hydrogen increases, more hydrogen-induced defects are formed at the interface between GI and a-IGZO active layer, which causes trapping of positive charges. This phenomenon can be explained by non-bridging oxygen hole center (NBOHC) method, which is one of the positive charge trapping models, and the mechanism for the role of hydrogen in the a-IGZO TFTs can be identified. [2] Base on these experimental results, we will propose the way to optimize condition of GI deposition process for high stability and high performance in a-IGZO TFTs. [1] S.J. Yun, K.-H. Lee, J. Skarp, H.-R. Kim and K.-S. Nam, J. Vac. Sci. Technol. A, 15(6) (1997) [2] M. Tsubuku, R. Watanabe, N. Ishihara, H. Kishida, M. Takahashi, S. Yamazaki, Y. Kanzaki, H. Matsukizono, S. Mori, T. Matsue, SID 2013 DIGEST. 169 (2013)
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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 | 0.001 |
| 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 | 0.000 | 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".