Digital Alchemy for Materials Design: Colloids and Beyond
Greg van Anders, Daphne Klotsa, Andrew S. Karas, Paul M. Dodd, Sharon, C. Glotzer

TL;DR
This paper introduces 'digital alchemy,' a statistical thermodynamic framework that links colloidal nanoparticle attributes to bulk material behavior, enabling rational design and optimization of self-assembling structures.
Contribution
The paper presents a novel thermodynamic approach to directly connect building block attributes with bulk structures, facilitating targeted material design.
Findings
Successfully applied digital alchemy to various nanoparticle systems
Identified key attributes influencing self-assembly
Provided a method for optimizing building blocks for desired structures
Abstract
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 direct connection between building block attributes and bulk behavior 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 behavior through a statistical thermodynamic framework we term "digital alchemy". We use this framework to optimize building blocks for a given…
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Taxonomy
TopicsMachine Learning in Materials Science · History and advancements in chemistry · Chemistry and Chemical Engineering
