Publication | Closed Access
Predictive Self-Assembly of Polyhedra into Complex Structures
1.1K
Citations
36
References
2012
Year
Building BlocksAnisotropic ShapeEngineeringMolecular Self-assemblyLiquid Crystalline ElastomerPredictive Self-assemblyComputer-aided DesignStructural OptimizationComputational MechanicsSoft MatterParticle ShapeCrystal FormationBiophysicsMaterials ScienceGeometric ModelingCrystallographyHierarchical Assembly3D PrintingNatural SciencesSelf-assembly
Predicting material structure from building‑block attributes remains a central challenge, and isolating shape effects in self‑assembly illuminates ordering in molecules, colloids, nanoparticles, proteins, and viruses. We investigated 145 convex polyhedra whose assembly arises solely from their anisotropic shape. The study finds a high propensity for thermodynamic self‑assembly and structural diversity, and shows that simple shape and local order metrics can predict whether a shape assembles into a liquid crystal, plastic crystal, or crystal.
Predicting structure from the attributes of a material's building blocks remains a challenge and central goal for materials science. Isolating the role of building block shape for self-assembly provides insight into the ordering of molecules and the crystallization of colloids, nanoparticles, proteins, and viruses. We investigated 145 convex polyhedra whose assembly arises solely from their anisotropic shape. Our results demonstrate a remarkably high propensity for thermodynamic self-assembly and structural diversity. We show that from simple measures of particle shape and local order in the fluid, the assembly of a given shape into a liquid crystal, plastic crystal, or crystal can be predicted.
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