Low-Dimensional-Materials-Based Flexible Artificial Synapse: Materials, Devices, and Systems

Abstract

With the rapid development of artificial intelligence and the Internet of Things, there is an explosion of available data for processing and analysis in any domain. However, signal processing efficiency is limited by the Von Neumann structure for the conventional computing system. Therefore, the design and construction of artificial synapse, which is the basic unit for the hardware-based neural network, by mimicking the structure and working mechanisms of biological synapses, have attracted a great amount of attention to overcome this limitation. In addition, a revolution in healthcare monitoring, neuro-prosthetics, and human–machine interfaces can be further realized with a flexible device integrating sensing, memory, and processing functions by emulating the bionic sensory and perceptual functions of neural systems. Until now, flexible artificial synapses and related neuromorphic systems, which are capable of responding to external environmental stimuli and processing signals efficiently, have been extensively studied from material-selection, structure-design, and system-integration perspectives. Moreover, low-dimensional materials, which show distinct electrical properties and excellent mechanical properties, have been extensively employed in the fabrication of flexible electronics. In this review, recent progress in flexible artificial synapses and neuromorphic systems based on low-dimensional materials is discussed. The potential and the challenges of the devices and systems in the application of neuromorphic computing and sensory systems are also explored.

Transforming medicine: artificial intelligence integration in the peripheral nervous system

“…AI and neuro-prosthetics are rapidly converging fields that hold immense promise in revolutionizing healthcare and improving the quality of life for individuals with neurological impairments ( 70 ). Neuro-prosthetics aims to restore lost sensory or motor functions by creating interfaces between the nervous system and external devices ( 71 ).…”

“…Within this realm, advancements in AI have been instrumental in enhancing the efficacy and usability of neuro-prosthetic devices. In particular, AI’s integration into neuro-prosthetics in the PNS has opened up new possibilities for patients with amputations, paralysis, or sensory deficits ( 70 ).…”

Enhancing Solar-to-Chemical Conversion through Tailoring Dimensions of Semiconductors in Biohybrid Systems

“…These systems achieve higher carbon yield and productivities by providing additional energy while reducing or eliminating carbon loss 8 . Low-dimensional nanomaterials 9 , typically smaller than 100 nm, including zero-dimensional (0D) nanoparticles or quantum dots (QDs), one-dimensional (1D) nanotubes or nanorods (NRs), and twodimensional (2D) nanosheets or nanoplatelets (NPLs), have been recognized for their cost-effectiveness, enhanced biocompatibility, photocatalytic activity, and stability [10][11][12][13] . These nanomaterials dominate in contemporary semiconductor biohybrid systems 14,15 .…”

Resistive Switching Transparent SnO2 Thin Film Sensitive to Light and Humidity

“…The stability of synaptic weights is crucial for precise and dependable computation in a neuromorphic computing system. 44 Hence, attention is to employ materials that possess characteristics comparable to those of neural synapses, which encompass the capacity to store and process data. 43 Exploring the use of such materials and devices for developing advanced neuromorphic computing systems is under debate 45 toward implementation in pattern recognition, image processing, and machine learning.…”

“…The concurrent manifestation of the NDR phenomenon and resistive switching (RS) memory characteristics are highly advantageous for applications in synaptic and neuromorphic computing, as evidenced in ref. 44…”