Abstract

Protonic ceramic electrochemical cells (PCEC), including solid oxide fuel/electrolysis cell, present promising routes to energy harvest and value-added chemical production. Despite tremendous efforts, PCEC still encounters several challenges, including poor thermal/chemical/mechanical compatibility and inferior solid-solid contact at the interfaces between electrolytes and electrodes. In this presentation, we will demonstrate in-line electrochemical characterization of interfacial electrical sensor embedded PCEC that can lead to fast identification of the failure mechanism of electrode supported PCECs. Upon the acquisition of quantitative contributions from different cell components to total degradation, data-driven machine learning is employed to further predict the long-term performance of the full cell up to 3000 hours. This presents novel insights into the degradation mechanism analysis in the solid-state electrochemical units, allowing ones to better modify the electrolyte and electrode materials and the interface between them, and develop more robust PCEC systems. The technology can be appliable to other electrochemical systems, including higher temperature counterpart (e.g., oxygen ion conducting solid oxide electrolysis cells, o-SOEC)

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call