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基于氧化锌的无序薄膜晶体管的亚阈值传导

Subthreshold Conduction of Disordered ZnO-Based Thin-Film Transistors.

作者信息

Yoon Minho

机构信息

Department of Physics and Institute of Quantum Convergence Technology, Kangwon National University, Chuncheon 24341, Republic of Korea.

出版信息

Micromachines (Basel). 2023 Aug 13;14(8):1596. doi: 10.3390/mi14081596.

DOI:10.3390/mi14081596
PMID:37630132
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10456918/
Abstract

This study presents the disorderedness effects on the subthreshold characteristics of atomically deposited ZnO thin-film transistors (TFTs). Bottom-gate ZnO TFTs show n-type enhancement-mode transfer characteristics but a gate-voltage-dependent, degradable subthreshold swing. The charge-transport characteristics of the disordered semiconductor TFTs are severely affected by the localized trap states. Thus, we posit that the disorderedness factors, which are the interface trap capacitance and the diffusion coefficient of electrons, would result in the degradation. Considering the factors as gate-dependent power laws, we derive the subthreshold current-voltage relationship for disordered semiconductors. Notably, the gate-dependent disorderedness parameters are successfully deduced and consistent with those obtained by the / method, which was for the FinFETs. In addition, temperature-dependent current-voltage analyses reveal that the gate-dependent interface traps limit the subthreshold conduction, leading to the diffusion current. Thus, we conclude that the disorderedness factors of the ZnO films lead to the indefinable subthreshold swing of the ZnO TFTs.

摘要

本研究展示了无序性对原子沉积氧化锌薄膜晶体管(TFT)亚阈值特性的影响。底栅氧化锌TFT呈现n型增强模式转移特性,但具有与栅极电压相关的、可降解的亚阈值摆幅。无序半导体TFT的电荷传输特性受到局部陷阱态的严重影响。因此,我们假定无序性因素,即界面陷阱电容和电子扩散系数,会导致这种降解。将这些因素视为与栅极相关的幂律,我们推导出了无序半导体的亚阈值电流-电压关系。值得注意的是,成功推导出了与栅极相关的无序性参数,且这些参数与通过用于鳍式场效应晶体管(FinFET)的/方法获得的参数一致。此外,温度相关的电流-电压分析表明,与栅极相关的界面陷阱限制了亚阈值传导,导致扩散电流。因此,我们得出结论,氧化锌薄膜的无序性因素导致了氧化锌TFT难以确定的亚阈值摆幅。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7b3/10456918/c0fafbc10a1c/micromachines-14-01596-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7b3/10456918/dc54acd20b06/micromachines-14-01596-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7b3/10456918/adc0157eb9d2/micromachines-14-01596-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7b3/10456918/0b95a419afce/micromachines-14-01596-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7b3/10456918/7301c23ce0f1/micromachines-14-01596-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7b3/10456918/c0fafbc10a1c/micromachines-14-01596-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7b3/10456918/dc54acd20b06/micromachines-14-01596-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7b3/10456918/adc0157eb9d2/micromachines-14-01596-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7b3/10456918/0b95a419afce/micromachines-14-01596-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7b3/10456918/7301c23ce0f1/micromachines-14-01596-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7b3/10456918/c0fafbc10a1c/micromachines-14-01596-g005.jpg

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