Flexible Artificial Synapses Based on Field Effect Transistors: From Materials, Mechanics towards Applications

Abstract

Von Neumann-based computation, which is the basis for solving complex and well-structured problems, plays an essential role in commercial computing units such as microcontrollers, microprocessors, and field-programmable gate arrays (FPGAs). However, the efficiency of von Neumann computers inevitably decreases when processing a large amount of data owing to the separate storage and processing units. Additionally, the energy consumption of these computers is high when data are switched frequently between the microprocessor and memory. [1][2][3] An efficient biological computing system, the human brain is capable of handling various complex tasks and consumes energy only on the order of several fJ/spike. Therefore, brain-inspired flexible artificial synapses are widely used in prosthetics, neurorobotics, and health monitoring. [4,5] The synapse is composed of a presynaptic membrane, synaptic cleft, and postsynaptic membrane. The cell membrane potential of the postsynaptic membrane changes in accordance with the action transmitted to the axon terminal of the presynaptic neuronal membrane. Since "neuromorphic electronic systems" were first proposed by Carver Mead in 1990, several synaptic devices based on two-terminal and three-terminal structures have been successfully fabricated to mimic the information processing function of the human brain. [6] Although two-terminal devices, such as memristors and phase-change memories, have low power consumption and simple device structures, [7][8][9] threeterminal transistors are more suitable for synaptic devices because of the advantages of parallel processing and memory functions. Furthermore, they comprise several gates to obtain signals from many sources compared with two-terminal devices. As a typical three-terminal element, the structure of field-effect transistors (FETs) is extremely similar to that of biological synapses (Figure 1a). [10] The gate voltage, V GS, serves as the presynaptic input terminal while the source-drain channel current I SD is used as the post-synaptic output terminal. The transmission of neurotransmitters from the pre-synapse to the post-synapse corresponds to carrier transportation. Synaptic devices with different device configurations have been employed in implementing synaptic functions by controlling the carrier transport (Figure 1b), such as floating-gate transistors, electrolyte-gate transistors, ferroelectric-gate transistors, and optoelectronic transistors. Thus, a clear understanding of the carrier transport mechanisms is the basis for designing artificial synapses with multiple functions.Communication between neurons is facilitated by changing the connection strength of the neurons, which is referred to as synaptic weight. [11] The basic characteristics of synaptic devices include excitatory postsynaptic currents (EPSC) and inhibitory postsynaptic currents (IPSC). These characteristics rely on the signals generated under external activation. [12] Synaptic plasticity is grouped into short-term plasticity (STP) and long-term

Mechanoresponsive Flexible Crystals

“…With highly ordered aggregation structure, flexible crystals might be engineered to exhibit fascinating optical, electrical, and mechanical properties, promising their potential flexible electronics and actuation applications. On account of the broad applications prospect in the fields of information sensing, − biomedicine, ,,− wearable devices, laser media, , fluorescence detection, renewable biomass resources development, etc., flexible crystals have attracted increasing attention from academia and industry.…”

Bio-inspired artificial synaptic transistors: evolution from innovative basic units to system integration

“…15,36 Compared with two-terminal devices like memristors, atomic switches and phase change memories, 37,38 three-terminal transistors possess higher fault tolerance, higher signal-to-noise ratio and a greater signal modulation property. [39][40][41] Mainstream neuronal synaptic transistors cover both vertical structures and planar structures, and the channel length could be regulated more accurately by vertical structure transistors and thus achieve a low power consumption. 42,43 According to the different implementation principles of synaptic transistors, they can be divided into polyelectrolyte, 44 ion-gel, 45 floating-gate, 46 electret, 47…”

Progress of Materials and Devices for Neuromorphic Vision Sensors

“…Generally, mobile cations with small radii are used, such as protons (H + ), alkali metals (Li + , Na + , and K + ), and alkaline earth metal ions (Ca 2+ and Mg 2+ ). According to the matrix phase, electrolytes can be classified into liquid (ionic liquid), gel (ionic gel), and solid electrolytes (polymeric electrolyte and inorganic electrolyte) [ 16 , 17 ]. When a positive bias input is applied to the gate terminal, the mobile cations in the electrolyte start to drift to the electrolyte/channel interface, owing to the positive bias-induced electric field (Fig.…”