Nanomaterials-Based Memristors for Neuromorphic Systems

Dear Colleagues, 

Neuromorphic computing, inspired by the architecture and efficiency of biological neural networks, holds immense potential to revolutionize artificial intelligence and energy-efficient computing. Memristors, as emerging non-volatile memory devices, are pivotal to this paradigmatic shift due to their ability to emulate synaptic plasticity and enable neural behavior. The integration of nanomaterials, including metal oxides, 2D materials, organic polymers, and hybrid nanostructures, into a memristor design has unlocked unprecedented opportunities to enhance device performance, scalability, and functionality. 

This Special Issue of Nanomaterials focuses on cutting-edge advancements in nanomaterials-based memristors for neuromorphic systems and applications, including optimization in nanomaterial synthesis, innovations in device design and fabrication, and the design of neuromorphic architectures and systems for the hardware implementation of biological behaviors. So far, multifarious nanomaterial-based neuromorphic devices have been proposed and utilized in applications in constructing bio-inspired artificial systems with complex biological functions. 

We invite researchers to contribute original research and review articles, highlighting the synergy between nanomaterials science and neuromorphic engineering and bridging material innovation with system-level applications. Potential topics include but are not limited to the following: nanomaterials-based two-terminal memristors or three-terminal memtransistors; memristor design and integration; memristor-based neuromorphic computing applications and systems; architecture design for memristor-based neuromorphic computing system and simulation; the hardware demonstration of neuromorphic systems with memristor chips; memristor-based neuromorphic computing platform with functional nanomaterials; etc.

Prof. Dr. Lifeng Liu
Dr. Zheng Zhou
Dr. Yulin Feng
Guest Editors

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