Benchmarking the performance of Bayesian optimization across multiple experimental materials science domains

Benchmarking the performance of Bayesian optimization across multiple experimental materials science domains

<jats:title>Abstract</jats:title><jats:p>Bayesian optimization (BO) has been leveraged for guiding autonomous and high-throughput experiments in materials science. However, few have evaluated the efficiency of BO across a broad range of experimental materials domains. In this work,...

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Main Authors: Liang, Qiaohao (Author), Gongora, Aldair E (Author), Ren, Zekun (Author), Tiihonen, Armi (Author), Liu, Zhe (Author), Sun, Shijing (Author), Deneault, James R (Author), Bash, Daniil (Author), Mekki-Berrada, Flore (Author), Khan, Saif A (Author), Hippalgaonkar, Kedar (Author), Maruyama, Benji (Author), Brown, Keith A (Author), Fisher III, John (Author), Buonassisi, Tonio (Author)
Format: Article
Language:English
Published: Springer Science and Business Media LLC, 2021-12-14T19:19:24Z.
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