AIP Advances (Aug 2024)
Emulating Ebbinghaus forgetting behavior in a neuromorphic device based on low dimensional h-BN
Abstract
Artificial synaptic devices that can mimic the biological synaptic functions of learning and forgetting are essential for the realization of neuromorphic computation, which could replace the von Neumann architecture. In this Letter, we have described a high-performing ultraviolet photodetector (wavelength 375 nm) using thin films of single-layer hexagonal boron nitride (h-BN) for potential use in fabricating a neuromorphic device. Furthermore, the classical Ebbinghaus forgetting curve can be optimized using various parameters such as the optical pulse width, number of pulses, and frequency of pulses. Our results show that the characteristic time constant (τ) has much more variability, indicating better performance control than the Ebbinghaus exponent (β). Furthermore, the performance of the optical synapse is very stable for low energy consumption, as low as 2–3 pJ.