Predictive Self-Assembly of Polyhedra into Complex Structures

被引：883

作者：

Damasceno, Pablo F. ^{[1
]}

Engel, Michael ^{[2
]}

Glotzer, Sharon C. ^{[1
,2
,3
]}

机构：

[1] Univ Michigan, Appl Phys Program, Ann Arbor, MI 48109 USA

[2] Univ Michigan, Dept Chem Engn, Ann Arbor, MI 48109 USA

[3] Univ Michigan, Dept Mat Sci & Engn, Ann Arbor, MI 48109 USA

来源：

SCIENCE | 2012年 / 337卷 / 6093期

关键词：

QUASI-CRYSTALLINE; DENSEST PACKINGS; PHASE; ENTROPY; SUPERLATTICES; NANOCRYSTALS;

D O I：

10.1126/science.1220869

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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.

引用

页码：453 / 457

页数：5

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