SNU CBE

Bifacially Engineered Perovskite‐Based Synaptic Memristors Achieve High Linearity and Symmetricity for Accurate and Robust Neuromorphic Computing

2025 · Advanced Science

저자

Jang Woo Lee, Liang Cai, Jeong‐Seok Nam, Dawoon Kim, Taehoon Kim, Sihyeok Kim, Jae Ho Lee, Cheolhwa Jang, Sungpyo Baek, Jiye Han, Ki‐Yong Kim, Seongpil An, 정인 (In Jae Chung), Eunsang Kwon, Sungjoo Lee, Il Jeon

연구주제

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

NTIS 과학기술표준분류

가장 가까운 분류(전기/전자 > 반도체 소자·회로 > SoC)가 화학·화공 범위 밖이다. 배정 근거: AI 키워드가 잡은 NTIS 과제의 분류.

AI 연구 키워드·방법

conductive filament halide perovskite memristor 뉴로모픽 컴퓨팅 2차원 페로브스카이트

키워드 (OpenAlex)

conductive filament formation ion migration suppression long-term potentiation long-term depression linearity neuromorphic computing tensile strain grain size uniformity

초록

Abstract Achieving both high linearity and symmetricity in metal halide perovskite (MHP)‐based memristors remains challenging, primarily due to their abrupt switching behaviors and irregular conductive filament (CF) pathways. Here, bifacially engineered MHP memristors exhibiting simultaneous high linearity, symmetricity, and reliability are reported. Top‐surface passivation using phenylethylammonium iodide (PEAI) facilitates the formation of an ultrathin 2D perovskite layer (PEA 2 PbI 4 ), promoting gradual switching and effectively suppressing ion migration during CF formation, thereby significantly enhancing the linearity of long‐term potentiation. Meanwhile, bottom‐side PEAI treatment alleviates tensile strain and enhances perovskite grain uniformity, leading to stable CF rupture and improved linearity in long‐term depression as well as symmetricity. The resulting bifacially engineere…

이 논문을 지원한 국가R&D 과제 (NTIS 성과)

NTIS 성과DB(2020–24)에서 DOI 매칭 없음

인접 그래프

노드 hover = 이웃 강조 · 1회 클릭 = 고정 · 고정된 노드 다시 클릭 = 페이지 이동

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교수 1

정인

연구주제 1

Advanced Memory and Neural Computing

키워드 2

뉴로모픽 컴퓨팅 · 2차원 페로브스카이트