SNUEI

Synaptic Barristor Based on Phase‐Engineered 2D Heterostructures

2018 · Advanced Materials

저자

Woong Huh, Seonghoon Jang, Jae Yoon Lee, Donghun Lee, Donghun Lee, Jung Min Lee, Hong‐Gyu Park, Jong Chan Kim, Hu Young Jeong, Gunuk Wang, 이철호 (Chul‐Ho Lee)

연구주제

Advanced Memory and Neural Computing · 2D Materials and Applications · Ferroelectric and Negative Capacitance Devices

NTIS 과학기술표준분류

에너지/자원만에너지·환경·원자력 확장

가장 가까운 분류(재료 > 고분자재료 > 전기/전자정보용 소재기술)가 에너지·환경·원자력 확장 범위 밖이다.

AI 연구 키워드·방법

인공 시냅스 barristor 그래핀 phase engineering 이셀레늄화텅스텐(WSe2)

키워드 (OpenAlex)

artificial synapses memristors tungsten oxide tungsten selenide graphene Schottky diodes van der Waals heterostructures synaptic plasticity

초록

The development of energy-efficient artificial synapses capable of manifoldly tuning synaptic activities can provide a significant breakthrough toward novel neuromorphic computing technology. Here, a new class of artificial synaptic architecture, a three-terminal device consisting of a vertically integrated monolithic tungsten oxide memristor, and a variable-barrier tungsten selenide/graphene Schottky diode, termed as a 'synaptic barrister,' are reported. The device can implement essential synaptic characteristics, such as short-term plasticity, long-term plasticity, and paired-pulse facilitation. Owing to the electrostatically controlled barrier height in the ultrathin van der Waals heterostructure, the device exhibits gate-controlled memristive switching characteristics with tunable programming voltages of 0.2-0.5 V. Notably, by electrostatic tuning with a gate terminal, it can additio…

이 논문을 지원한 국가R&D 과제 (NTIS 성과)

NTIS 성과DB(2020–24)에서 DOI 매칭 없음

인접 그래프

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교수 1

이철호

연구주제 1

Advanced Memory and Neural Computing

키워드 3

그래핀 · 이셀레늄화텅스텐(WSe2) · 인공 시냅스