Search for: All records

Abstract Memristors for neuromorphic computing have gained prominence over the years for implementing synapses and neurons due to their nano-scale footprint and reduced complexity. Several demonstrations show two-dimensional (2D) materials as a promising platform for the realization of transparent, flexible, ultra-thin memristive synapses. However, unsupervised learning in a spiking neural network (SNN) facilitated by linearity and symmetry in synaptic weight update has not been explored thoroughly using the 2D materials platform. Here, we demonstrate that graphene/MoS₂/SiO_x/Ni synapses exhibit ideal linearity and symmetry when subjected to identical input pulses, which is essential for their role in online training of neural networks. The linearity in weight update holds for a range of pulse width, amplitude and number of applied pulses. Our work illustrates that the mechanism of switching in MoS₂-based synapses is through conductive filaments governed by Poole-Frenkel emission. We demonstrate that the graphene/MoS₂/SiO_x/Ni synapses, when integrated with a MoS₂-based leaky integrate-and-fire neuron, can control the spiking of the neuron efficiently. This work establishes 2D MoS₂as a viable platform for all-memristive SNNs. 

Abstract Optical data sensing, processing and visual memory are fundamental requirements for artificial intelligence and robotics with autonomous navigation. Traditionally, imaging has been kept separate from the pattern recognition circuitry. Optoelectronic synapses hold the special potential of integrating these two fields into a single layer, where a single device can record optical data, convert it into a conductance state and store it for learning and pattern recognition, similar to the optic nerve in human eye. In this work, the trapping and de-trapping of photogenerated carriers in the MoS 2 /SiO 2 interface of a n-channel MoS 2 transistor was employed to emulate the optoelectronic synapse characteristics. The monolayer MoS 2 field effect transistor (FET) exhibits photo-induced short-term and long-term potentiation, electrically driven long-term depression, paired pulse facilitation (PPF), spike time dependent plasticity, which are necessary synaptic characteristics. Moreover, the device’s ability to retain its conductance state can be modulated by the gate voltage, making the device behave as a photodetector for positive gate voltages and an optoelectronic synapse at negative gate voltages.