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)
| 연도 | 과제 | 부처 | 사업 | 수행기관 | NTIS 분류(1순위) |
|---|---|---|---|---|---|
| 2020 | 화학분자공학사업단 | 교육부 | BK21플러스사업(R&D) | 서울대학교 | – |
인접 그래프
노드 hover = 이웃 강조 · 1회 클릭 = 고정 · 고정된 노드 다시 클릭 = 페이지 이동