Title | An artificial synaptic transistor using an α-In 2 Se 3 van der Waals ferroelectric channel for pattern recognition |
Publication Type | Journal Article |
Year of Publication | 2021 |
Authors | Mohta, N, Rao, A, Remesh, N, Muralidharan, R, Nath, DN |
Journal | RSC Advances |
Volume | 11 |
Pagination | 36901–36912 |
Abstract | Despite being widely investigated for their memristive behavior, ferroelectrics are barely studied as channel materials in field-effect transistor (FET) configurations. In this work, we use multilayer α-In2Se3 to realize a ferroelectric channel semiconductor FET, i.e., FeS-FET, whose gate-triggered and polarization-induced resistive switching is then exploited to mimic an artificial synapse. The FeS-FET exhibits key signatures of a synapse such as excitatory and inhibitory postsynaptic current, potentiation/depression, and paired pulsed facilitation. Multiple stable conductance states obtained by tuning the device are then used as synaptic weights to demonstrate pattern recognition by invoking a hidden layer perceptron model. Detailed artificial neural network (ANN) simulations are performed on binary scale MNIST data digits, invoking 784 input (28 × 28 pixels) and 10 output neurons which are used in the training of 42 |
DOI | 10.1039/D1RA07728G |