journal article·2023-11

Boolean Logic Computing Based on Neuromorphic Transistor

Yifei Wang, Qijun Sun, Jinran Yu, Nuo Xu, Yichen Wei, Jeong Ho Cho, Zhong Lin Wang

Advanced Functional Materials· Volume 33· Issue 47
Publisher page

Abstract

Abstract General‐purpose computers usually use logic gate computing units based on complementary metal oxide semiconductors (CMOS). Due to the separate memory and computing units in Von Neumann architecture, data transmission requires great energy and time consumption. Developing novel neuromorphic devices and comprehensively investigating their logical computing mode are crucial to achieve high‐performance and low‐power neuromorphic computation. Here, a systematic summary of Boolean logic computing based on emerging neuromorphic transistors is presented. This summary encompasses logical operation modes, materials, device structures, and working mechanisms. The input mode of Boolean logic operation is classified into electrical input, optical input, and synergistic optical/electrical input. Besides, additional modulation strategies to construct programmable logic functions by electrical, optical, and thermal signals are also summarized. These strategies hold great significance as they enable dynamic reconfiguration of logic operations and provide neuromorphic devices with decision‐making capabilities. Finally, the application prospects and current challenges to Boolean logic computing based on dendritic integration are discussed from the aspects of device integration, synergistic input/modulation modes, auxiliary peripheral circuit, software/hardware system, etc. It is believed that comprehensive investigations on neuromorphic Boolean logic operations are crucial to push forward the development of future neuromorphic computing toward high efficiency and high integration density.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Neural Networks and Reservoir Computing

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences Beijing 101400 P. R. China

School of Nanoscience and Engineering University of Chinese Academy of Sciences Beijing 100049 P. R. China

Center on Nanoenergy Research School of Physical Science and Technology Guangxi University Nanning 530004 China

Division of R&D Shandong Zhongke Naneng Energy Technology Co., Ltd. Dongying 7061 P. R. China

Department of Chemical and Biomolecular Engineering Yonsei University Seoul 03722 Republic of Korea

School of Materials Science and Engineering Georgia Institute of Technology Atlanta GA 30332 USA

Funding

National Key Research and Development Program of China · National Natural Science Foundation of China · Beijing Nova Program · Fundamental Research Funds for the Central Universities

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