title: Integrated Computational and Experimental Structure Refinement for Nanoparticles.
abstract: Determining the three-dimensional (3D) atomic structure of nanoparticles is critical to identifying the structures controlling their properties. Here, we demonstrate an integrated genetic algorithm (GA) optimization tool that refines the 3D structure of a nanoparticle by matching forward modeling to experimental scanning transmission electron microscopy (STEM) data and simultaneously minimizing the particle energy. We use the tool to create a refined 3D structural model of an experimentally observed ∼6000 atom Au nanoparticle.
authors.affiliation: Department of Materials Science and Engineering, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States.
authors.forename: Min
authors.initials: M
authors.lastname: Yu
authors.affiliation: Department of Materials Science and Engineering, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States.
authors.forename: Andrew B
authors.initials: AB
authors.lastname: Yankovich
authors.affiliation: Department of Materials Science and Engineering, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States.
authors.forename: Amy
authors.initials: A
authors.lastname: Kaczmarowski
authors.affiliation: Department of Materials Science and Engineering, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States.
authors.forename: Dane
authors.initials: D
authors.lastname: Morgan
authors.affiliation: Department of Materials Science and Engineering, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States.
authors.forename: Paul M
authors.initials: PM
authors.lastname: Voyles
keywords: genetic algorithm; nanoclusters; nanoparticles; scanning transmission electron microscopy; structure optimization