Uncovering the effects of interface-induced ordering of liquid on crystal growth using machine learning

Freitas, Rodrigo; Reed, Evan J.

doi:10.1038/s41467-020-16892-4

Title: Uncovering the effects of interface-induced ordering of liquid on crystal growth using machine learning

Journal Article · 26 June 2020 · Nature Communications

DOI: https://doi.org/10.1038/s41467-020-16892-4 · OSTI ID:1635123

^[1]; Reed, Evan J. ^[1]

Stanford University, CA (United States). Department. of Materials Science and Engineering

The process of crystallization is often understood in terms of the fundamental microstructural elements of the crystallite being formed, such as surface orientation or the presence of defects. Considerably less is known about the role of the liquid structure on the kinetics of crystal growth. Here atomistic simulations and machine learning methods are employed together to demonstrate that the liquid adjacent to solid-liquid interfaces presents significant structural ordering, which effectively reduces the mobility of atoms and slows down the crystallization kinetics. Through detailed studies of silicon and copper we discover that the extent to which liquid mobility is affected by interface-induced ordering (IIO) varies greatly with the degree of ordering and nature of the adjacent interface. Physical mechanisms behind the IIO anisotropy are explained and it is demonstrated that incorporation of this effect on a physically-motivated crystal growth model enables the quantitative prediction of the growth rate temperature dependence.

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Research Organization:: Washington State Univ., Pullman, WA (United States); Stanford Univ., CA (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA), Office of Defense Programs (DP); National Science Foundation (NSF)

Grant/Contract Number:: NA0002007; DMREF-1922312; CAREER-1455050

OSTI ID:: 1635123

Alternate ID(s):: OSTI ID: 1647000; OSTI ID: 1673759

Journal Information:: Nature Communications, Vol. 11, Issue 1; ISSN 2041-1723

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

Citation Metrics:

Cited by: 28 works

Citation information provided by
Web of Science

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