As an increasing amount of multimodal sensors are used in intelligent electronics, energy expenditure gets more massive. Consequently, researchers aim to develop efficient computing paradigms or integrate energy harvesting from ambient sources. Halide perovskites possess unique photophysics and coupled ionic-electronic dynamics that actualize memory devices for brain-inspired computing. Synergizing the computing capability with their conventional light harvesting efficacy could address this issue.
Researchers from Singapore's Nanyang Technological University and Hong Kong's City University of Hong Kong recently examined the use of halide perovskite photovoltaics for in-sensor reservoir computing (RC).
In a novel approach, the transient open circuit voltage (VOC) of a methylammonium lead bromide-based solar cell was exploited to serve as a self-powered volatile short-term memory for optoelectronic in-sensor reservoir computing.
The origin of the memory is attributed to the influence of mobile ions on the carrier generation and recombination in the device. The system's versatility and task specificity were shown by engineering the volatility of the memory. The benchmarking task of MNIST handwritten digit recognition was performed with the highly reproducible and robust transformation of optical inputs into unique reservoir states. To demonstrate the high nonlinearity, second-order time-series prediction (NARMA2) was performed.
Finally, a cardiac health-monitoring application was showcased by monolithic reading and processing of a physiological time series known as photoplethysmography (PPG) to identify atrial fibrillation with increased computational efficiency.
The team demonstrated a novel approach to realizing an optoelectronic self-powered in-sensor physical reservoir computing. Through a functional interpretation of the transient VOC decay, suitable dynamics for RC were found in halide perovskite solar cells. While presently the PV cell is not configured to drive the rest of the elements of the system, utilizing the VOC as the internal state variable for RC is advantageous regarding integration and power consumption.
