Two-step machine learning enables optimized nanoparticle synthesis

<jats:title>Abstract</jats:title><jats:p>In materials science, the discovery of recipes that yield nanomaterials with defined optical properties is costly and time-consuming. In this study, we present a two-step framework for a machine learning-driven high-throughput microfluidic p...

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Bibliographic Details
Main Authors: Mekki-Berrada, Flore (Author), Ren, Zekun (Author), Huang, Tan (Author), Wong, Wai Kuan (Author), Zheng, Fang (Author), Xie, Jiaxun (Author), Tian, Isaac Parker Siyu (Author), Jayavelu, Senthilnath (Author), Mahfoud, Zackaria (Author), Bash, Daniil (Author), Hippalgaonkar, Kedar (Author), Khan, Saif (Author), Buonassisi, Tonio (Author), Li, Qianxiao (Author), Wang, Xiaonan (Author)
Format: Article
Language:English
Published: Springer Science and Business Media LLC, 2021-12-14T19:21:47Z.
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