Memristors Based on 2D Materials as an Artificial Synapse for Neuromorphic Electronics. Issue 51 (27th September 2020)

• Record Type: Journal Article
• Authors: Huh, Woong; Lee, Donghun; Lee, Chul‐Ho
• Is Part Of: Advanced materials. Volume 32:Issue 51(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-09-27
• Subjects: 2D materials -- artificial synapses -- memristors -- neuromorphic electronics -- transition metal dichalcogenides; Materials -- Periodicals; Chemical vapor deposition -- Periodicals; 620.11
• DOI: 10.1002/adma.202002092
• Languages: English
• ISSNs: 0935-9648

Abstract

Abstract: The memristor, a composite word of memory and resistor, has become one of the most important electronic components for brain‐inspired neuromorphic computing in recent years. This device has the ability to control resistance with multiple states by memorizing the history of previous electrical inputs, enabling it to mimic a biological synapse in the neural network of the human brain. Among many candidates for memristive materials, including metal oxides, organic materials, and low‐dimensional nanomaterials, 2D layered materials have been widely investigated owing to their outstanding physical properties and electrical tunability, low‐power‐switching capability, and hetero‐integration compatibility. Hence, a large number of experimental demonstrations on 2D material‐based memristors have been reported showing their unique memristive characteristics and novel synaptic functionalities, distinct from traditional bulk‐material‐based systems. Herein, an overview of the latest advances in the structures, mechanisms, and memristive characteristics of 2D material‐based memristors is presented. Additionally, novel strategies to modulate and enhance the synaptic functionalities of 2D‐memristor‐based artificial synapses are summarized. Finally, as a foreseeing perspective, the potentials and challenges of these emerging materials for future neuromorphic electronics are also discussed. Abstract : The recent progress regarding memristors based on 2D materials for neuromorphic electronics is reviewed. They are categorized by their various materials, structures, and mechanisms. Owing to their outstanding synaptic characteristics, neuromorphic devices based on 2D materials offer excellent performance, energy‐efficient operation, and modifiable synaptic functions applicable to complex learning.