Data-driven failure diagnosis and prognosis of solid-state ceramic membrane reactor under harsh conditions using deep learning technology with internal voltage sensors

This research will investigate in situ the effects of different components on the degradation behavior in a solid-state ceramic membrane reactor by embedding sensors that will collect current and impedance data during operation. Artificial intelligence will be used to understand the large amounts of data and predict reactor failure under harsh operating conditions.