Phenol-Assisted Electrochemical Metallization of Peptide-Based Bimodal Memristors
2023 · ACS Materials Letters
저자
Min‐Kyu Song, Seok Daniel Namgung, Jun Min Suh, Jeong Hyun Yoon, 남기태 (Ki Tae Nam), Jang‐Yeon Kwon
연구주제
Advanced Memory and Neural Computing · Molecular Junctions and Nanostructures · Conducting polymers and applications
NTIS 과학기술표준분류
에너지/자원만에너지·환경·원자력 확장
가장 가까운 분류(전기/전자 > 반도체소자 및 시스템 > SoC)가 에너지·환경·원자력 확장 범위 밖이다.
AI 연구 키워드·방법
electrochemical metallization 뉴로모픽 컴퓨팅 펩타이드 멤리스터
키워드 (OpenAlex)
memristors electrochemical metallization ionic conductivity neuromorphic computing functional group effects biomimetic devices
초록
Neuromorphic computing is an emerging approach designed to handle massive amounts of data, and memristors have gained significant attention as a means of realizing this technology. However, the operation of memristors is inherently stochastic, which compromises device controllability. This unpredictability creates a substantial disparity between the synthetic devices and actual biological systems in terms of the cognitive processing efficiency. To address this challenge, we use bioderived materials to develop a bimodal memristor that is activated by either voltage or protons. This mimics biological systems in which the interactions between electrons and ions play a crucial role in cognitive processing. Furthermore, we investigate the influence of functional groups on the bimodally operating memristor characteristics at the molecular level. Our findings show that the phenolic functional g…
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교수 1
연구주제 1
Advanced Memory and Neural Computing