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Machine Learning and High Throughput Synthesis Acceleration of the Discovery of Alkaline Electrolyte Oxygen Evolution Reaction Electrocatalysts

析氧 过电位 电催化剂 催化作用 电化学能量转换 电解水 材料科学 电解质 电解 电化学 纳米技术 化学工程 化学 电极 工程类 生物化学 物理化学
作者
Ahmed Sabry Farghaly,Magali Ferrandon,Daniel Schwalbe‐Koda,James Damewood,Jessica Karaguesian,Rafael Gómez‐Bombarelli,Deborah J. Myers
出处
期刊:Meeting abstracts 卷期号:MA2022-02 (44): 1673-1673 被引量:1
标识
DOI:10.1149/ma2022-02441673mtgabs
摘要

Accelerating the development and discovery of new catalysts is vital for advancing many electrochemical energy conversion technologies (EECT) required to achieve a sustainable future utilizing carbon-free fuel, a circular economy, and to meet the grand energy challenges of the 21 st century. The oxygen evolution reaction (OER) is at the heart of many EECT such as water and carbon dioxide electrolyzers, fuel cells, and metal-oxygen batteries. The sluggish kinetics of oxygen electrocatalysis, resulting high overpotential necessary to attain practical current densities, and the high cost of the state-of-the-art OER platinum group metal (PGM) and precious metals catalysts (i.e., IrO 2 and RuO 2 ) limit the cost-effective implementation and development of several promising electrolysis technologies. 1-3 The development of alternative PGM-free OER catalysts, with comparable or superior activity and durability to the PGM catalysts and derived from earth-abundant materials has thus been an active research area for decades. The application of perovskite oxides as PGM-free electrocatalysts for the OER in alkaline environments has seen significant research interest in the last decade, with tri-metallic and tetra-metallic compounds showing activities comparable to PGM-based catalysts. 4,5 The chemical space of these compounds is exceptionally large, yet the development of new perovskite oxides with high OER performance (activity and durability) has been limited and often discovered through trial and error, a time and cost inefficient route that restricted the discovery of more advanced materials. Recent advances in high-performance computing, machine learning (ML), and high throughput material synthesis and screening technologies have enabled high-throughput catalyst design and discovery. 4-10 This presentation will describe how the machine learning and high throughput synthesis technologies worked synergistically to accelerate the discovery of alkaline oxygen evolution reaction electrocatalysts. The role of ML in accelerating the materials synthesis and the role of high throughput synthesis in optimizing the ML model predictions will be discussed. Acknowledgments This work was supported by the U.S. Department of Energy, Advanced Research Projects Agency-Energy (ARPA-E) under the DIFFERENTIATE program. This work was authored in part by Argonne National Laboratory, a U.S. Department of Energy (DOE) Office of Science laboratory operated for DOE by UChicago Argonne, LLC under contract no. DE-AC02-06CH11357. References Katsounaros, Ioannis, Serhiy Cherevko, Aleksandar R. Zeradjanin, and Karl JJ Mayrhofer. "Oxygen electrochemistry as a cornerstone for sustainable energy conversion." Angewandte Chemie International Edition 53, no. 1 (2014): 102-121. Lee, Youngmin, Jin Suntivich, Kevin J. May, Erin E. Perry, and Yang Shao-Horn. "Synthesis and activities of rutile IrO2 and RuO2 nanoparticles for oxygen evolution in acid and alkaline solutions." The journal of physical chemistry letters 3, no. 3 (2012): 399-404. Cherevko, S. et al. Oxygen and hydrogen evolution reactions on Ru, RuO2, Ir, and IrO2 thin film electrodes in acidic and alkaline electrolytes: A comparative study on activity and stability. Today 262 , 170–180 (2016). Nahar, Lamia, Ahmed A. Farghaly, Richard J. Alan Esteves, and Indika U. Arachchige. "Shape controlled synthesis of Au/Ag/Pd nanoalloys and their oxidation-induced self-assembly into electrocatalytically active aerogel monoliths." Chemistry of Materials 29, no. 18 (2017): 7704-7715. Farghaly, Ahmed A., Rezaul K. Khan, and Maryanne M. Collinson. "Biofouling-resistant platinum bimetallic alloys." ACS applied materials & interfaces 10, no. 25 (2018): 21103-21112. Khan, Rezaul K., Ahmed A. Farghaly, Tiago A. Silva, Dexian Ye, and Maryanne M. Collinson. "Gold-Nanoparticle-Decorated Titanium Nitride Electrodes Prepared by Glancing-Angle Deposition for Sensing Applications." ACS Applied Nano Materials 2, no. 3 (2019): 1562-1569. Farghaly, Ahmed A., Mai Lam, Christopher J. Freeman, Badharinadh Uppalapati, and Maryanne M. Collinson. "Potentiometric measurements in biofouling solutions: comparison of nanoporous gold to planar gold." Journal of The Electrochemical Society 163, no. 4 (2015): H3083. Suntivich, Jin, Kevin J. May, Hubert A. Gasteiger, John B. Goodenough, and Yang Shao-Horn. "A perovskite oxide optimized for oxygen evolution catalysis from molecular orbital principles." Science 334, no. 6061 (2011): 1383-1385. Hwang, Jonathan, Zhenxing Feng, Nenian Charles, Xiao Renshaw Wang, Dongkyu Lee, Kelsey A. Stoerzinger, Sokseiha Muy et al. "Tuning perovskite oxides by strain: electronic structure, properties, and functions in (electro) catalysis and ferroelectricity." Materials Today 31 (2019): 100-118. Gómez-Bombarelli, Rafael, Jennifer N. Wei, David Duvenaud, José Miguel Hernández-Lobato, Benjamín Sánchez-Lengeling, Dennis Sheberla, Jorge Aguilera-Iparraguirre, Timothy D. Hirzel, Ryan P. Adams, and Alán Aspuru-Guzik. "Automatic chemical design using a data-driven continuous representation of molecules." ACS central science 4, no. 2 (2018): 268-276.

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