Perovskite nickelate ionotronics for AI and brain-machine interfaces

Abstract

Human brain is the ultimate computing machine in nature. Creating brain-like devices that emulate how the brain works and can communicate with the brain is crucial for fabricating highly efficient computing circuits, monitoring the onset of diseases at early stages, and transferring information across brain-machine interfaces. Simultaneous transduction of ionic-electronic signals would be of particular interest in this context since ionic transmitters are the means of information transfer in human brain while traditional electronics utilize electrons or holes. In this perspective, we propose strongly correlated oxides (mainly focused on perovskite nickelates) as potential candidates for this purpose. The capability of reversibly accepting small ions and converting ionic signal to electrical signals renders perovskite nickelates strong candidates for neuromorphic computing and bioelectrical applications. We will discuss the mechanism behind the interplay between ionic doping and the resistivity modulation in perovskite nickelates. We will also present case studies of using the perovskite nickelates in neuromorphic computing and brain-machine interface applications. We then conclude by pointing out the challenges in this field and provide our perspectives. We hope the utilization of strong electron correlation in the perovskite nickelates will provide exciting new opportunities for future computation devices and brain-machine interfaces.