GaN/α-In2Se3 HEMT 中由铁电二维层的面外局部极化实现的可重构物理储层,ACS Nano

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GaN/α-In2Se3 HEMT 中由铁电二维层的面外局部极化实现的可重构物理储层
ACS Nano ( IF 15.8 ) Pub Date : 2023-04-04 , DOI: 10.1021/acsnano.3c00187
Jeong Yong Yang ₁ , Minseong Park ₂ , Min Jae Yeom ₁ , Yongmin Baek ₂ , Seok Chan Yoon ₁ , Yeong Je Jeong ₁ , Seung Yoon Oh ₁ , Kyusang Lee _{2,

3} , Geonwook Yoo ₁

Affiliation

由于缺乏合适的材料、栅极结构，阻碍了通过简单脉冲操作演示基于氮化镓 (GaN) 的铁电金属氧化物半导体 (MOS)-高电子迁移率晶体管 (HEMT) 进行可重构操作的重大努力和内在的去极化效应。_{在这项研究中，我们展示了使用与 α-In 2} Se ₃铁电半导体集成的基于 GaN 的 MOS-HEMT 的人工突触。_{GaN/α-In 2} Se ₃的范德华异质结构提供了实现由铁电耦合二维电子气 (2DEG) 驱动的高频操作的潜力。此外，半导体α-In ₂ Se ₃具有陡峭的亚阈值斜率和高开/关比 (∼10 ¹⁰ )。带有栅电极的自对准 α-In ₂ Se _{3层抑制面内极化，同时促进 α-In}₂ Se ₃的面外 (OOP) 极化，导致陡峭的亚阈值斜率 (10 mV /dec) 并产生较大的滞后 (2 V)。此外，基于制造的铁电 HEMT 的短期可塑性 (STP) 特性，我们展示了用于图像分类的储层计算 (RC)。我们相信，铁电 GaN/α-In ₂ Se ₃ HEMT 可以为超快神经形态计算提供一条可行的途径。

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Reconfigurable Physical Reservoir in GaN/α-In2Se3 HEMTs Enabled by Out-of-Plane Local Polarization of Ferroelectric 2D Layer

Significant effort for demonstrating a gallium nitride (GaN)-based ferroelectric metal–oxide–semiconductor (MOS)-high-electron-mobility transistor (HEMT) for reconfigurable operation via simple pulse operation has been hindered by the lack of suitable materials, gate structures, and intrinsic depolarization effects. In this study, we have demonstrated artificial synapses using a GaN-based MOS-HEMT integrated with an α-In₂Se₃ ferroelectric semiconductor. The van der Waals heterostructure of GaN/α-In₂Se₃ provides a potential to achieve high-frequency operation driven by a ferroelectrically coupled two-dimensional electron gas (2DEG). Moreover, the semiconducting α-In₂Se₃ features a steep subthreshold slope with a high ON/OFF ratio (∼10¹⁰). The self-aligned α-In₂Se₃ layer with the gate electrode suppresses the in-plane polarization while promoting the out-of-plane (OOP) polarization of α-In₂Se₃, resulting in a steep subthreshold slope (10 mV/dec) and creating a large hysteresis (2 V). Furthermore, based on the short-term plasticity (STP) characteristics of the fabricated ferroelectric HEMT, we demonstrated reservoir computing (RC) for image classification. We believe that the ferroelectric GaN/α-In₂Se₃ HEMT can provide a viable pathway toward ultrafast neuromorphic computing.

更新日期：2023-04-04

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