Phys Org
•91% Informative
Researchers from PNNL harnessed the power of data science and ML techniques to help streamline synthesis development for iron oxide particles.
Their approach addressed two pivotal issues: identifying feasible experimental conditions and foreseeing potential particle characteristics for a given set of synthetic parameters.
The study is published in the Chemical Engineering Journal .
VR Score
94
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99
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English
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