"Digital Alchemy for Materials Design"
Since the early alchemists, scientists have strived for ways 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, the genomes of target structures are typically unknown, with a nearly infinite number of available building blocks that could potentially assemble the structure. Here we show how to exploit the malleability of the valence of colloidal nanoparticle "elements" to link building block attributes to bulk behavior 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. 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.