Computational explorations in the space of one-component crystals

Doye, Jonathan P. K.; Noya, Eva G.

doi:10.1073/pnas.2107024118

Cited by 1 publication

(1 citation statement)

References 22 publications

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“…In the case of complex crystals, growth models and experimentally observed mechanisms do not account for the presence of more than one local environment or a large periodic unit cell in the crystallizing structure. How do identical particles find their specific role to occupy in a structure with multiple local environments, , and what role does the liquid play in crystal growth? , As such one-component complex structures are being studied on the mesoscale , and engineering such materials with DNA-functionalization is becoming an ever more powerful tool for design, − achieving a better understanding of the structural transitions and pathways during crystal growth for complex structures is critical for directing self-assembly.…”

Section: Introductionmentioning

confidence: 99%

Local Structural Features Elucidate Crystallization of Complex Structures

Martirossyan,

Spellings,

Pan

et al. 2024

ACS Nano

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Complex crystal structures are composed of multiple local environments, and how this type of order emerges spontaneously during crystal growth has yet to be fully understood. We study crystal growth across various structures and along different crystallization pathways, using self-assembly simulations of identical particles that interact via multiwell isotropic pair potentials. We apply an unsupervised machine learning method to features from bond-orientational order metrics to identify different local motifs present during a given structure's crystallization process. In this manner, we distinguish different crystallographic sites in highly complex structures. Tailoring this order parameter to structures of varying complexity and coordination number, we study the emergence of local order along a multistep crystal growth pathway�from a low-density fluid to a high-density, supercooled amorphous liquid droplet and to a bulk crystal. We find a consistent under-coordination of the liquid relative to the average coordination number in the bulk crystal. We use our order parameter to analyze the geometrically frustrated growth of a Frank−Kasper phase and discover how structural defects compete with the formation of crystallographic sites that are more high-coordinated than the liquid environments. The method presented here for classifying order on a particle-by-particle level has broad applicability to future studies of structural self-assembly and crystal growth, and they can aid in the design of building blocks and for targeting pathways of formation of soft-matter structures.

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