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

computer simulation. dimensionality reduction machine learning nanoparticles quasicrystal self-assembly tetrahedra

Journal

ACS nano
ISSN: 1936-086X
Titre abrégé: ACS Nano
Pays: United States
ID NLM: 101313589

Informations de publication

Date de publication:
24 Nov 2020
Historique:
pubmed: 27 10 2020
medline: 27 10 2020
entrez: 26 10 2020
Statut: ppublish

Résumé

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

Identifiants

pubmed: 33103878
doi: 10.1021/acsnano.0c05288
pmc: PMC7690044
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

15144-15153

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Auteurs

Robin van Damme (R)

Soft Condensed Matter, Debye Institute for Nanomaterials Science, Utrecht University, Princetonplein 1, 3584 CC Utrecht, The Netherlands.

Gabriele M Coli (GM)

Soft Condensed Matter, Debye Institute for Nanomaterials Science, Utrecht University, Princetonplein 1, 3584 CC Utrecht, The Netherlands.

René van Roij (R)

Institute for Theoretical Physics, Utrecht University, Princetonplein 5, 3584 CC Utrecht, The Netherlands.

Marjolein Dijkstra (M)

Soft Condensed Matter, Debye Institute for Nanomaterials Science, Utrecht University, Princetonplein 1, 3584 CC Utrecht, The Netherlands.

Classifications MeSH