journal article·2022-07

Defect Engineering for High Performance and Extremely Reliable a‐IGZO Thin‐Film Transistor in QD‐OLED

Young‐Gil Park, Dong Yeon Cho, Ran Kim, Kang Hyun Kim, Ju Won Lee, Doo Hyoung Lee, Soo Im Jeong, Na Ri Ahn, Woo‐Geun Lee, Jae Beom Choi, Min Jung Kim, Donghyun Kim, Seunghee Jin, Dong Geun Park, Jungchun Kim, Saeyan Choi, Seain Bang, Jae Woo Lee

Advanced Electronic Materials· Volume 8· Issue 7
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Abstract

Abstract An amorphous indium‐gallium‐zinc‐oxide (a‐IGZO) thin‐film transistor (TFT), which exhibits the best electrical stability (PBTS ≤ 0.009 V), is implemented to create quantum‐dot organic light‐emitting diode product. Electrical stability has been explained through various mechanisms involving defects related to oxygen and hydrogen. The defects of a‐IGZO are identified and the parameters of the deposition process are utilized to obtain Vo+ and VZn− values of 1.7 × 1017 and 2.4 × 1018 spins cm−3, respectively, which are quantified using electron spin resonance for the first time. The defects of the gate insulator (GI) in the upper and lower parts of the a‐IGZO TFT and the oxygen and hydrogen inflow/diffusion generated during the process are also controlled. From well‐controlled a‐IGZO and GI, the defect density at the top‐channel interface and near‐interface of the a‐IGZO TFT is reduced by 85% and 70%, respectively. The defects in the bottom‐channel are also reduced by 83% and 75% for the interface and near‐interface, respectively. Electrical stability is secured by controlling Vo+ and VZn− and reducing sub‐gap trap density among interface defects that are not directly observed until now. In this paper, it is reported that the best a‐IGZO TFT performance is achieved through defect engineering.
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Research context

OpenAlex topics: Thin-Film Transistor Technologies · ZnO doping and properties · Semiconductor materials and devices

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Samsung Display Co., LTD. Giheung‐gu Yongin‐si Gyeonggi‐do 17133 Republic of Korea

Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology Korea University Sejong 30019 Republic of Korea

Funding

Korea University

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