Recent Progress of Protein‐Based Data Storage and Neuromorphic Devices
Junjie Wang, Fangsheng Qian, Shenming Huang, Ziyu Lv, Yan Wang, Xuechao Xing, Meng Chen, Su‐Ting Han, Ye Zhou
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.