Piezotronic Graphene Artificial Sensory Synapse

Abstract

The human somatosensory system, consisting of receptors, transmitters, and synapses, functions as the medium for external mechanical stimuli perception and sensing signal delivery/processing. Developing sophisticated artificial sensory synapses with a high performance, uncomplicated fabrication process, and low power consumption is still a great challenge. Here, a piezotronic graphene artificial sensory synapse developed by integrating piezoelectric nanogenerator (PENG) with an ion gel-gated transistor is demonstrated. The piezopotential originating from PENG can efficiently power the synaptic device due to the formation of electrical double layers at the interface of the ion gel/ electrode and ion gel/graphene. Meanwhile, the piezopotential coupling is capable of linking the spatiotemporal strain information (strain amplitude and duration) with the postsynaptic current. The synaptic weights can be readily modulated by the strain pulses. Typical properties of a synapse including excitation/inhibition, synaptic plasticity, and paired pulse facilitation are successfully demonstrated. The dynamic modulation of a sensory synapse is also achieved based on dual perceptual presynaptic PENGs coupling to a single postsynaptic transistor. This work provides a new insight into developing piezotronic synaptic devices in neuromorphic computing, which is of great significance in future self-powered electronic skin with artificial intelligence, a neuromorphic interface for neurorobotics, human-robot interaction, an intelligent piezotronic transistor, etc.

Mimicking Human and Biological Skins for Multifunctional Skin Electronics

“…b) Piezotronic graphene artificial sensory synapse. Reproduced with permission . Copyright 2019, Wiley‐VCH.…”

“…Although two‐terminal electronic devices, such as memristors, emulate sensory neuronal functions of synapse and artificial sensory systems with integration of tactile sensors, they cannot simultaneously perform the signal transmission and learning functions . As another candidate for artificial synapses, three‐terminal transistors with an additional input terminal have attracted intense research interests aimed at closer mimicking of neuromorphic configurations and functions of biological synapses . In the three‐terminal transistors, gate electrodes act as presynaptic terminals and channel layers with source–drain electrodes are treated as the postsynaptic membrane.…”

“…The piezotronics, which uses piezopotential as a gate voltage, can also modulate the afferent sensory nerve. Sun and co‐workers demonstrated piezotronics‐based artificial sensory nerve systems, where P(VDF‐TrFE) thin film–based piezoelectric strain sensors enabled self‐powered encoding of external tactile stimuli into piezopotential, which capacitively modulates the charge carrier in the channel of graphene transistor through the ion gel (Figure b) . In this design, the strain pulse‐induced piezopotential, polarization of ions through the ion gel, and output signals of transistor are highly analogous with the action potential, chemical release and migration of neurotransmitters, and postsynaptic output in biological sensory synapses, respectively.…”

Fingerprint‐Inspired Conducting Hierarchical Wrinkles for Energy‐Harvesting E‐Skin

“…Electronic skins (E‐skins), afferent nerves, and neuromorphic devices have been extensively investigated for mimicking, and even surpassing, the performance of human skin for tasks such as protection, perception, regulation, and feedback . Large amounts of memory and numerous sensors, processors, and actuators are required in an intelligent interactive system; such a system also consumes vast amounts of energy . Hence, utilization of an E‐skin with energy‐harvesting capacity is of great significance for the realization of a self‐powered system for mechanosensation.…”

Graphdiyne-Based Ultra-Responsive Artificial Synapse with Multi-Ion Diffusive Dynamics for Mimicking Efferent Nerves

“…Complex human nervous systems, which have the edges of being highly compact, parallel, and reliable, are gaining more and more attention in various elds such as neuromorphic computing, bioinspired sensory systems, and prosthetics. [1][2][3][4][5][6] Somatosensory nerves transfer signals through synaptic connections, to achieve a variety of perceptions, memories and motion outputs with different depths. [7][8][9][10] Therefore, the imitation of synapses as building blocks for neural processing are of crucial importance for constructing an e cient arti cial neuromorphic system.…”