Achieving neuronal dynamics with spike encoding and spatial-temporal summation in vanadium-based threshold switching memristor for asynchronous signal integration.

Abstract

Artificial neuronal devices that emulate the dynamics of biological neurons are pivotal for advancing brain emulation and developing bio-inspired electronic systems. This paper presents the design and demonstration of an artificial neuron circuit based on a Pt/V/AlO_x/Pt threshold switching memristor (TSM) integrated with an external resistor. By applying voltage pulses, we successfully exhibit the leaky integrate-and-fire (LIF) behavior, as well as both spatial and spatiotemporal summation capabilities, achieving the asynchronous signal integration. Notably, the Pt/V/AlO_x/Pt TSM demonstrates ultrafast switching speeds (on/off times ∼165 ns/310 ns) and remarkable stability (endurance >10² cycles with cycle-to-cycle variations <2.5%). These attributes render the circuit highly suitable as a spike generator in neuromorphic computing applications. The Pt/V/AlO_x/Pt TSM-based spike encoder can output current spikes at frequencies ranging from approximately 200 kHz to 800 kHz. The modulation of output spike frequency is achievable by adjusting the external resistor and capacitor within the spike encoder circuit, providing considerable operational flexibility. Additionally, the Pt/V/AlO_x/Pt TSM boasts a lower threshold voltage (V_th ∼ 0.84 V) compared to previously reported VO_x-based TSMs, leading to significantly reduced energy consumption for spike generation (∼2.75 nJ per spike).