Emulation of Synaptic Plasticity on a Cobalt-Based Synaptic Transistor for Neuromorphic Computing

Abstract

Neuromorphic computing (NC), which emulates neural activities of the human brain, is considered for the low-power implementation of artificial intelligence. Toward realizing NC, fabrication, and investigations of hardware elementssuch as synaptic devices and neuronsare crucial. Electrolyte gating has been widely used for conductance modulation by massive carrier injections and has proven to be an effective way of emulating biological synapses. Synaptic devices, in the form of synaptic transistors, have been studied using various materials. Despite the remarkable progress, the study of metallic channel-based synaptic transistors remains massively unexplored. Here, we demonstrated a three-terminal electrolyte gatingmodulated synaptic transistor based on a metallic cobalt thin film to emulate biological synapses. We have realized gating-controlled, non-volatile, and distinct multilevel conductance states in the proposed device. The essential synaptic functions demonstrating both short-term and long-term plasticity have been emulated in the synaptic device. A transition from short-term to long-term memory has been realized by tuning the gate pulse parameters, such as amplitude and duration. The crucial cognitive behavior, including learning, forgetting, and re-learning, has been emulated, showing a resemblance to the human brain. Beyond that, dynamic filtering behavior has been experimentally implemented in the synaptic device. These results provide an insight into the design of metallic channel-based synaptic transistors for NC.

Demonstration of Synaptic Behavior in a Heavy-Metal-Ferromagnetic-Metal-Oxide-Heterostructure-Based Spintronic Device for On-Chip Learning in Crossbar-Array-Based Neural Networks

“…Song et al have reported simulation-based on-chip learning in ANNs using experimentally obtained synaptic characteristic in a skyrmionic device . But the remaining experimental spintronic studies only show device-level data (without any system-level simulation based on the device data), ,, or show training of an SNN or some other biologically motivated network ,, (which is different from an ANN and does not use LTD and LTP of a synapse the way an ANN does), or use binary spintronic synapses/magnetic tunnel junctions (MTJs) , as opposed to the multibit synapses we focus on here (one device stores 5 bits in our case).…”

“…Nanomagnetic and spintronic devices based on the heavy-metal-ferromagnetic-metal-oxide heterostructures have been considered very attractive for various applications including nonvolatile memory (NVM), − logic, and neuromorphic computing. − These devices heavily use interfacial phenomena like perpendicular magnetic anisotropy (PMA) and spin–orbit torque (SOT) for their functionalities. − ,− PMA is considered to originate primarily from the ferromagnet–oxide interface, , while the following mechanisms have been considered as origins of SOT: Spin Hall effect inside the heavy metal leads to accumulation of spin-polarized electrons at the heavy-metal–ferromagnet interface; these spin-polarized electrons subsequently flow from the heavy metal to the ferromagnet to apply SOT on the magnetic moments of the ferromagnetic layer. ,, Rashba effect at the heavy-metal–ferromagnet interface Additional interface-originated effects like the orbital Rashba–Edelstein effect, recently reported by Chen et al …”

Proton-Gated Synaptic Transistors, Based on an Electron-Beam Patterned Nafion Electrolyte

“…Synaptic functions have been emulated in two-terminal devices such as phase change memory, , resistive random-access memory, − atomic switches, , magnetoresistive random-access memory, , and in three-terminal devices such as electrolyte-gated transistors (EGTs), − and ferroelectric field effect transistors. − Of the various EGTs, proton-gated transistors are considered to be one of the core elements for building physical neural networks because of their favorable characteristics, such as low power consumption (down to aJ), smaller charge carriers, faster operation, and compatibility with flexible electronics. , In these devices, organic and inorganic electrolytes such as chitosan, Nafion, and mesoporous silica (MSC) have been used as the gate electrolyte, which acts as proton (H + ) conductors and reservoirs. ,− Protons with an ionic radius of 0.04 Å have a higher diffusion rate than other ions, leading to faster operation of EGTs by interfacial ionic effects such as proton insertion and extraction without affecting the stability of the channel material. , Several groups have shown various synaptic behaviors in chitosan-based EGTs with an indium–tin-oxide (ITO) or indium–zinc-oxide (IZO) channel, , Nafion-based EGTs with a poly­(3,4-ethylene-dioxythiophene): polystyrenesulfonate (PEDOT:PSS) or tungsten oxide (WO 3 ) channel, ,, and MSC-based EGTs with an ITO channel. , Note that synaptic functions can be achieved in transistors without the use of electrolytes or ferroelectric gates, as recently demonstrated by Dai et al…”

Enhanced Synaptic Properties in Biocompatible Casein Electrolyte via Microwave-Assisted Efficient Solution Synthesis

“…This limitation represents an incomplete implementation of biological synapses in two-terminal devices. In contrast, a three-terminal synaptic device can simultaneously learn and transmit signals through different parts, the gate terminal and the channel, respectively [ 20 ]. As a result, synaptic behavior can be fully emulated by a three-terminal device.…”