Two-step machine learning enables optimized nanoparticle synthesis

Two-step machine learning enables optimized nanoparticle synthesis

Abstract 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 platform to rapidly produce silver nanoparticles wi...

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Bibliographic Details
Main Authors: Flore Mekki-Berrada, Zekun Ren, Tan Huang, Wai Kuan Wong, Fang Zheng, Jiaxun Xie, Isaac Parker Siyu Tian, Senthilnath Jayavelu, Zackaria Mahfoud, Daniil Bash, Kedar Hippalgaonkar, Saif Khan, Tonio Buonassisi, Qianxiao Li, Xiaonan Wang
Format: article
Language:EN
Published: Nature Portfolio 2021
Subjects:
Materials of engineering and construction. Mechanics of materials
TA401-492
Computer software
QA76.75-76.765
Online Access:https://doaj.org/article/0ac9eaf9fc9e46a2ad63c0e8d956006b
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https://doaj.org/article/0ac9eaf9fc9e46a2ad63c0e8d956006b

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