In-cell neuromorphic computing in solid oxide fuel cells for bifunctional electrochemical power generation and artificial intelligence

Abstract

Solid oxide fuel cells (SOFCs) are all-solid-state electrochemical devices that directly convert the chemical energy of fuel into electricity, and they represent one of the most efficient and versatile means of clean power generation. Herein, we report the potential of SOFCs as neuromorphic computing devices and verify the synaptic properties, including paired-pulse facilitation (PPF) and potentiation and depression characteristics, under specific operating conditions, which enable the implementation of a brain-like computing system. We simulate image classification tasks using an artificial neural network (ANN) and confirm that the classification accuracy is 85.4%, indicating that the SOFC system is capable of performing cognitive computing in addition to having power generation functionality. This work examines the concept of in-cell computing using bifunctional SOFCs that handle computation/memory functions in electric power generation devices, and our findings suggest opportunities for power management in various sectors, including smart grid systems, electric vehicles, and smart mobility.