Second order Synaptic Plasticity with multistate memory in flexible MoO3-Aloe vera composite Devices for low energy Neuromorphic applications

Human brain can adopt to the signals and evaluate them accordingly to create short term and long- term memories. The prior activity can influence such short-term and long-term memory. Artificial synapse which can modulate its weight updates depending on the history of stimulation is analogues to human brain. Here, we show that such second order memristive can be fabricated using a simple pencil-on-paper (POP) technique with MoO3 - Aloe vera composite as active layer and few layer graphene (FLG) as electrodes. Apart from achieving fundamental synaptic characteristics in the device, strain dependent synaptic performance is also evaluated. FLG/MoO3 - Aloe vera/FLG de- vice demonstrates very stable memory states, with multi-bit memory capabilities when configured to various conductance states under both flat and strained conditions. The devices can be operated at low energy (∼ pJ) which is essential for low energy consuming neuromorphic devices. Synaptic weight updates strongly depend on the prior activity which helps to control learning and forgetting characteristics. Further, the nonlinearity factors (NLF) in neuromorphic characteristics can be con- trolled by optimizing the stimulation parameters. This work proposes a platform for developing an environmentally friendly, flexible neuromorphic devices for next generation low energy neuromorphic applications.