Decoding the growth kinetics of complex crystals via local structural analysis

The growth kinetics of materials with complex crystal structures, such as clathrates and Frank Kasper phases, are poorly described by the standard attachment-based models used for simple, close-packed structures. We can bridge this gap by simulating the self-assembly of identical particles that interact via isotropic pair potentials [1], and study how particles take on different “roles” as they settle into different crystal sites, or local environments. Identical particles that occupy distinct crystal sites exhibit different kinetic behaviors, which we observe via a machine-learning powered order parameter [2] that classifies particles into different local environments during the self-assembly process. This analysis is performed and compared for a variety of structures with different complexities and coordination numbers, and can provide insight for the design and assembly of materials with desired structures and functionalities.

 

[1] J. Dshemuchadse, P. F. Damasceno, C. L. Phillips, M. Engel, S. C. Glotzer., Proc. Natl. Acad. Sci. USA 118 (21), e2024034118 (2021). 

[2] M. Spellings, S. C. Glotzer, AIChE J. 64 (6), 2198–2206 (2018).