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Path to proton-conducting ceramic commercialization: data mining to better understand processing, performance, and stability

Meisel, Charlie
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Abstract
Proton-conducting ceramic electrochemical cells (PCCs) offer promising solutions for green hydrogen production, energy storage, and industrial decarbonization. PCCs are efficient, reversible, and scalable devices that operate at 350--600 °C. Despite promising lab-scale results, scale-up and commercialization face challenges, particularly with reproducibility. This thesis investigates key aspects of PCCs, including processing, performance, and stability, by analyzing data from numerous cells. The goal is to advance PCC commercial viability. Elastic Net machine learning (ML) models were applied to data from up to 199 half cells, encompassing 20 processing parameters. These models reveal that sintering temperature, NiO particle size, cerium content, and electrolyte application methods most significantly influence negatrode shrinkage and electrolyte grain growth. The Furnace atmosphere during sintering also substantially impacts sinterability. Gaussian Process and Random Forest Regressor ML models were used to analyze data from over 84 cells, encompassing 68 processing parameters. These models revealed key factors for improving fuel cell and electrolysis performance. Performance is enhanced by lowering the electrolyte thickness to grain size ratio (< 1) and utilizing NiO particles smaller than 6 μm. Evaporating off organics from processing steps before sintering can also significantly impact performance. Performance improvements in fuel cell operation are primarily driven by lowering polarization resistance through tailoring the positrode morphology. Electrolysis operation benefits from refined electrolyte microstructures that minimize ohmic resistance. Stability studies emphasize the essential role of gas-tight electrolytes in long-term PCC operation, as oxygen transport through pinholes accelerates degradation. Effective strategies for attaining gas-tight electrolytes include Two-step sintering schedules, altering the furnace environment, fabricating functional layers, and using thicker electrolytes. Electrochemical impedance spectroscopy (EIS), distribution of relaxation times (DRT), and electron microscopy were used to connect changes in nickel microstructure to electrochemical responses. These comprehensive findings offer valuable insights into PCC optimization and reproducibility, paving the way for accelerated commercialization of this promising technology and contributing to a more sustainable future.
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