Machine Learning Holds Water (1 of 2) (IMAGE)
Caption
Molecular dynamics simulations based on machine learning show how grains of ice form and coalesce in supercooled water, which results in ice with imperfections. These simulations help scientists learn about the movement of the boundary between ice grains (yellow/green/cyan) and the stacking disorder that occurs when hexagonal (orange) and cubic (blue) pieces of ice freeze together. This information is important in applications such as climate modeling and cryogenics. Researchers performed these simulations on Mira at the Argonne Leadership Computing Facility and Carbon at the Center for Nanoscale Materials; ALCF and CNM are both DOE Office of Science User Facilities.
Credit
Argonne National Laboratory
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