Recent Advances of Graphene and Related Materials in Artificial Intelligence

Abstract

Biological brains perform real‐time processing of unstructured data with ultralow energy consumption and represent the most efficient computing systems. Emulating the working principles of biological brains brings a revolutionary breakthrough in artificial intelligence (AI), generating two kinds of imitation approaches including machine learning (ML) and neuromorphic computing (NC) with artificial neurons/synapses. Herein this review, a general description of ML methods, the concept, and principle of artificial synapses (ASs) in NC derived from biological synapses, and their relationships, is provided. Graphene, one of the most representative 2D materials, arouses considerable attention due to its unique structure and properties. The application of ML in properties prediction (electronic properties, mechanical properties, thermal properties, cytotoxicity), structure recognition (atomic structure, microscopic dimensions/shapes), inverse design (composition, structure), and task recognition (chemical recognition, motion recognition, 3D imaging) of graphene and its derivatives and composites are summarized, and corresponding methods are discussed in the case studies. Recent progress in the development and application of graphene‐based ASs (synaptic transistors and memristors) is briefly introduced, where graphene‐based materials serve as the channel materials of synaptic transistors, the memristive materials, or back electrodes of synaptic memristors. Finally, the main challenges and prospects of graphene‐incorporated ML and ASs are presented.

Artificial Intelligence (AI) and Internet of Medical Things (IoMT) Assisted Biomedical Systems for Intelligent Healthcare

“…Graphene has demonstrated a potential application for fabricating biomedical sensing devices, including optoelectronics and wearable devices. Biomimetic sensors imitating the sensory functions of the human brain, such as touch, smell, taste, and hearing, have been developed using graphene-based materials [ 69 ]. The high surface area of graphene allows the construction of biosensing devices with excellent sensitivity.…”

Applications of Graphene in Five Senses, Nervous System, and Artificial Muscles

“…By each sensory organ, the receptive field is transduced into the changes in electric current or potential, which can be transmitted by signaling pathways and fused with other senses in the brain. The graphene memristor based individual artificial synapse , can transmit a pulse signal, and graphene synapse arrays host the neuromorphic computing for memory and data processing . Upon stimulus to skin or electronic skin, , the human responds by nervous reflexes or the brain system.…”

Graphene nanoparticles as data generating digital materials in industry 4.0

“…[118][119][120][121][122] . On the other hand, AI tools such as machine and deep learning can not only accelerate the discovery, design and optimization of 2D materials [123][124][125][126] , but also can interpret the signals generated by sensors based on 2D materials. Here, since we are discussing graphene as potential sensor, we will restrict our discussions to AI tools for signal processing.…”