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Classifying Crystals of Rounded Tetrahedra and Determining Their Order Parameters Using Dimensionality Reduction

[Image: see text] Using simulations we study the phase behavior of a family of hard spherotetrahedra, a shape that interpolates between tetrahedra and spheres. We identify 13 close-packed structures, some with packings that are significantly denser than previously reported. Twelve of these are cryst...

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Autores principales: van Damme, Robin, Coli, Gabriele M., van Roij, René, Dijkstra, Marjolein
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2020
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7690044/
https://www.ncbi.nlm.nih.gov/pubmed/33103878
http://dx.doi.org/10.1021/acsnano.0c05288
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author van Damme, Robin
Coli, Gabriele M.
van Roij, René
Dijkstra, Marjolein
author_facet van Damme, Robin
Coli, Gabriele M.
van Roij, René
Dijkstra, Marjolein
author_sort van Damme, Robin
collection PubMed
description [Image: see text] Using simulations we study the phase behavior of a family of hard spherotetrahedra, a shape that interpolates between tetrahedra and spheres. We identify 13 close-packed structures, some with packings that are significantly denser than previously reported. Twelve of these are crystals with unit cells of N = 2 or N = 4 particles, but in the shape regime of slightly rounded tetrahedra we find that the densest structure is a quasicrystal approximant with a unit cell of N = 82 particles. All 13 structures are also stable below close packing, together with an additional 14th plastic crystal phase at the sphere side of the phase diagram, and upon sufficient dilution to packing fractions below 50–60% all structures melt. Interestingly, however, upon compressing the fluid phase, self-assembly takes place spontaneously only at the tetrahedron and the sphere side of the family but not in an intermediate regime of tetrahedra with rounded edges. We describe the local environment of each particle by a set of l-fold bond orientational order parameters q̅(l), which we use in an extensive principal component analysis. We find that the total packing fraction as well as several particular linear combinations of q̅(l) rather than individual q̅(l)’s are optimally distinctive, specifically the differences q̅(4) – q̅(6) for separating tetragonal from hexagonal structures and q̅(4)–q̅(8) for distinguishing tetragonal structures. We argue that these characteristic combinations are also useful as reliable order parameters in nucleation studies, enhanced sampling techniques, or inverse-design methods involving odd-shaped particles in general.
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spelling pubmed-76900442020-11-27 Classifying Crystals of Rounded Tetrahedra and Determining Their Order Parameters Using Dimensionality Reduction van Damme, Robin Coli, Gabriele M. van Roij, René Dijkstra, Marjolein ACS Nano [Image: see text] Using simulations we study the phase behavior of a family of hard spherotetrahedra, a shape that interpolates between tetrahedra and spheres. We identify 13 close-packed structures, some with packings that are significantly denser than previously reported. Twelve of these are crystals with unit cells of N = 2 or N = 4 particles, but in the shape regime of slightly rounded tetrahedra we find that the densest structure is a quasicrystal approximant with a unit cell of N = 82 particles. All 13 structures are also stable below close packing, together with an additional 14th plastic crystal phase at the sphere side of the phase diagram, and upon sufficient dilution to packing fractions below 50–60% all structures melt. Interestingly, however, upon compressing the fluid phase, self-assembly takes place spontaneously only at the tetrahedron and the sphere side of the family but not in an intermediate regime of tetrahedra with rounded edges. We describe the local environment of each particle by a set of l-fold bond orientational order parameters q̅(l), which we use in an extensive principal component analysis. We find that the total packing fraction as well as several particular linear combinations of q̅(l) rather than individual q̅(l)’s are optimally distinctive, specifically the differences q̅(4) – q̅(6) for separating tetragonal from hexagonal structures and q̅(4)–q̅(8) for distinguishing tetragonal structures. We argue that these characteristic combinations are also useful as reliable order parameters in nucleation studies, enhanced sampling techniques, or inverse-design methods involving odd-shaped particles in general. American Chemical Society 2020-10-26 2020-11-24 /pmc/articles/PMC7690044/ /pubmed/33103878 http://dx.doi.org/10.1021/acsnano.0c05288 Text en © 2020 American Chemical Society This is an open access article published under a Creative Commons Non-Commercial No Derivative Works (CC-BY-NC-ND) Attribution License (http://pubs.acs.org/page/policy/authorchoice_ccbyncnd_termsofuse.html) , which permits copying and redistribution of the article, and creation of adaptations, all for non-commercial purposes.
spellingShingle van Damme, Robin
Coli, Gabriele M.
van Roij, René
Dijkstra, Marjolein
Classifying Crystals of Rounded Tetrahedra and Determining Their Order Parameters Using Dimensionality Reduction
title Classifying Crystals of Rounded Tetrahedra and Determining Their Order Parameters Using Dimensionality Reduction
title_full Classifying Crystals of Rounded Tetrahedra and Determining Their Order Parameters Using Dimensionality Reduction
title_fullStr Classifying Crystals of Rounded Tetrahedra and Determining Their Order Parameters Using Dimensionality Reduction
title_full_unstemmed Classifying Crystals of Rounded Tetrahedra and Determining Their Order Parameters Using Dimensionality Reduction
title_short Classifying Crystals of Rounded Tetrahedra and Determining Their Order Parameters Using Dimensionality Reduction
title_sort classifying crystals of rounded tetrahedra and determining their order parameters using dimensionality reduction
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7690044/
https://www.ncbi.nlm.nih.gov/pubmed/33103878
http://dx.doi.org/10.1021/acsnano.0c05288
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