SNUEI

Nanoparticle-based computing architecture for nanoparticle neural networks

2020 · Science Advances

저자

Sungi Kim, Namjun Kim, Jinyoung Seo, Jeong‐Eun Park, Eun Ho Song, So Young Choi, Ji Eun Kim, Seungsang Cha, Ha H. Park, 남좌민 (Jwa‐Min Nam)

연구주제

Advanced biosensing and bioanalysis techniques

NTIS 과학기술표준분류

에너지/자원만에너지·환경·원자력 확장

지원 과제·AI 키워드로 잡을 근거가 없어 분류하지 않았다.

AI 연구 키워드·방법

dna logic circuit 분자 컴퓨팅 nanoparticle computing architecture nanoparticle neural network

키워드 (OpenAlex)

von Neumann architecture DNA logic circuits molecular computing feedforward neural networks perceptron Boolean operations programmable logic circuits

초록

The lack of a scalable nanoparticle-based computing architecture severely limits the potential and use of nanoparticles for manipulating and processing information with molecular computing schemes. Inspired by the von Neumann architecture (VNA), in which multiple programs can be operated without restructuring the computer, we realized the nanoparticle-based VNA (NVNA) on a lipid chip for multiple executions of arbitrary molecular logic operations in the single chip without refabrication. In this system, nanoparticles on a lipid chip function as the hardware that features memory, processors, and output units, and DNA strands are used as the software to provide molecular instructions for the facile programming of logic circuits. NVNA enables a group of nanoparticles to form a feed-forward neural network, a perceptron, which implements functionally complete Boolean logic operations, and pro…

이 논문을 지원한 국가R&D 과제 (NTIS 성과)

연도과제부처사업수행기관NTIS 분류(1순위)
2020화학분자공학사업단교육부BK21플러스사업(R&D)서울대학교–

인접 그래프

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교수 1

남좌민

키워드 1

분자 컴퓨팅