Synthesizable nanoparticle eigenshapes for colloidal crystals. Issue 31 (20th July 2021)

• Record Type: Journal Article
• Authors: Geng, Yina; van Anders, Greg; Glotzer, Sharon C.
• Is Part Of: Nanoscale. Volume 13:Issue 31(2021)
• Page Start: 13301
• Page End: 13309
• Publication Date: 2021-07-20
• Subjects: Nanoscience -- Periodicals; Nanotechnology -- Periodicals; 620.505
• DOI: 10.1039/d1nr01429c
• Languages: English
• ISSNs: 2040-3364

Abstract

Abstract : Eigenshapes are nanoparticle shapes that minimize the free energy of a target structure for fixed thermodynamic conditions. We determine eigenshapes for several structures using Alchemical Monte-Carlo (Alch-MC), inverse design techniques. Abstract : The gulf between the complexity and diversity of colloidal crystal phases predicted to form in computer simulation and that realized to date in experiment is narrowing, but is still wide. Prior work shows that many synthesized particles are far from optimal "eigenshapes" for target superlattice structures. We use digital alchemy to determine eigenshapes for possible target colloidal crystal structures for eight families of polyhedral nanoparticle shapes already synthesized in the laboratory. Within each family we predict optimal building block shapes to obtain several target superlattice structures, as a guide for future experiments. For three target crystal structures common to multiple families, we identify which of the optimal shapes is most optimal under the same thermodynamic conditions.