Recent Progress of Protein‐Based Data Storage and Neuromorphic Devices

Abstract

By virtue of energy efficiency, high speed, and parallelism, brain-inspired neuromorphic computing is a promising technology to overcome the von Neumann bottleneck and capable of processing massive sophisticated tasks in the background of big data. The abilities of perceiving and reacting to events in artificial neuromorphic systems allow us to build the communicative electronic-biological interfaces to get closer to electronic life. Protein materials offer great application potentials in such a system due to their sustainability, low cost, controllable hierarchical structure, intrinsic biocompatibility, and biodegradability. Herein, a timely review of the development of protein-based memories for data storage and neuromorphic computing is provided. Proteins' unique mechanical, electronic, optical properties, and their broad applications are discussed. Then, the progress of protein-based two-terminal memristor and three-terminal transistor-type memory is reviewed, and their applications for data storage, logic circuit, and neuromorphic computing are introduced. Finally, the major challenges and outlook toward the future developing directions of protein-based computing systems are pointed out. FU - National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61974093]; Guangdong Province Special Support Plan for High-Level Talents [2017TQ04X082]; Guangdong Provincial Department of Science and Technology [2018B030306028]; Science and Technology Innovation Commission of Shenzhen [JCYJ20180507182042530, JCYJ20180507182000722]; NTUT-SZU Joint Research Program; Natural Science Foundation of SZU FX - The authors acknowledge grants from National Natural Science Foundation of China (grant no. 61974093), Guangdong Province Special Support Plan for High-Level Talents (grant no. 2017TQ04X082), Guangdong Provincial Department of Science and Technology (grant no. 2018B030306028), the Science and Technology Innovation Commission of Shenzhen (grant nos. JCYJ20180507182042530 and JCYJ20180507182000722), and NTUT-SZU Joint Research Program and the Natural Science Foundation of SZU. NR - 158 PU - WILEY PI - HOBOKEN PA - 111 RIVER ST, HOBOKEN 07030-5774, NJ USA