Catalyst design with machine learning
Catalyst design with machine learning
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DOI：
10.1038/s41560-022-01112-8
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发表时间：
2022-09
期刊：
影响因子：
56.7
通讯作者：
Hongliang Xin
中科院分区：
文献类型：
--
作者：
Hongliang Xin
氧还原催化剂的开发对一系列能源技术至关重要;然而，该过程长期依赖于缓慢的试错方法。现在，通过机器学习，可以加速发现钙钛矿氧化物在固体氧化物燃料电池中用作空气电极。
Development of oxygen reduction catalysts is of key importance to a range of energy technologies; however, the process has long relied on slow trial-and-error approaches. Now, accelerated discovery of perovskite oxides for use as air electrodes in solid-oxide fuel cells is achieved with machine learning.