Inverse Design of Self-Assembling Frank-Kasper Phases and Insights Into Emergent Quasicrystals

The Journal of Physical Chemistry. B
Beth A LindquistThomas M Truskett

Abstract

We discuss how a machine learning approach based on relative entropy optimization can be used as an inverse design strategy to discover isotropic pair interactions that self-assemble single- or multicomponent particle systems into Frank-Kasper phases. In doing so, we also gain insights into the self-assembly of quasicrystals.

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Citations

Sep 16, 2019·The Journal of Chemical Physics·Beth A LindquistThomas M Truskett
Mar 7, 2020·Soft Matter·Nathan A MahynskiJeetain Mittal
Dec 7, 2018·The Journal of Chemical Physics·Carl S AdorfSharon C Glotzer
Dec 16, 2019·The Journal of Chemical Physics·Daniel F TraceyJonathan P K Doye
Apr 1, 2019·The Journal of Chemical Physics·D BanerjeeT M Truskett
Apr 17, 2020·The Journal of Chemical Physics·Zachary M ShermanThomas M Truskett
May 21, 2021·Proceedings of the National Academy of Sciences of the United States of America·Jonathan P K Doye, Eva G Noya
Jul 10, 2021·The Journal of Chemical Physics·Beth A Lindquist
Aug 16, 2021·The Journal of Chemical Physics·Philip H HandleNicoletta Gnan

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