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...
Main Authors: | Mekki-Berrada, Flore, Ren, Zekun, Huang, Tan, Wong, Wai Kuan, Zheng, Fang, Xie, Jiaxun, Tian, Isaac Parker Siyu, Jayavelu, Senthilnath, Mahfoud, Zackaria, Bash, Daniil, Hippalgaonkar, Kedar, Khan, Saif, Buonassisi, Tonio, Li, Qianxiao, Wang, Xiaonan |
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Other Authors: | Singapore-MIT Alliance in Research and Technology (SMART) |
Format: | Article |
Language: | English |
Published: |
Springer Science and Business Media LLC
2021
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Online Access: | https://hdl.handle.net/1721.1/138479 |
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