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Digital Alchemy for Materials Design: Colloids and Beyond

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† Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109-2136, United States
‡ School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
§ Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
⊥ Department of Materials Science and Engineering, University of Michigan, Ann Arbor, Michigan 48109-2136, United States
∥ Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan 48109-2800, United States
*Address correspondence to [email protected]
Cite this: ACS Nano 2015, 9, 10, 9542–9553
Publication Date (Web):September 24, 2015
https://doi.org/10.1021/acsnano.5b04181
Copyright © 2015 American Chemical Society
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    Abstract

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    Starting with the early alchemists, a holy grail of science has been to make desired materials by modifying the attributes of basic building blocks. Building blocks that show promise for assembling new complex materials can be synthesized at the nanoscale with attributes that would astonish the ancient alchemists in their versatility. However, this versatility means that making a direct connection between building-block attributes and bulk structure is both necessary for rationally engineering materials and difficult because building block attributes can be altered in many ways. Here we show how to exploit the malleability of the valence of colloidal nanoparticle “elements” to directly and quantitatively link building-block attributes to bulk structure through a statistical thermodynamic framework we term “digital alchemy”. We use this framework to optimize building blocks for a given target structure and to determine which building-block attributes are most important to control for self-assembly, through a set of novel thermodynamic response functions, moduli, and susceptibilities. We thereby establish direct links between the attributes of colloidal building blocks and the bulk structures they form. Moreover, our results give concrete solutions to the more general conceptual challenge of optimizing emergent behaviors in nature and can be applied to other types of matter. As examples, we apply digital alchemy to systems of truncated tetrahedra, rhombic dodecahedra, and isotropically interacting spheres that self-assemble diamond, fcc, and icosahedral quasicrystal structures, respectively. Although our focus is on colloidal systems, our methods generalize to any building blocks with adjustable interactions.

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