期刊
ACS NANO
卷 10, 期 4, 页码 4031-4038出版社
AMER CHEMICAL SOC
DOI: 10.1021/acsnano.5b05722
关键词
structure optimization; genetic algorithm; scanning transmission electron microscopy; nanoparticles; nanoclusters
类别
资金
- NSF [DMR-1332851, 1148011]
- Department of Energy, Office of Basic Energy Sciences [DE-FG02-08ER46547]
- UW Materials Research Science and Engineering Center [DMR-1121288]
- Division Of Materials Research
- Direct For Mathematical & Physical Scien [1332851] Funding Source: National Science Foundation
- Office of Advanced Cyberinfrastructure (OAC)
- Direct For Computer & Info Scie & Enginr [1148011] Funding Source: National Science Foundation
- U.S. Department of Energy (DOE) [DE-FG02-08ER46547] Funding Source: U.S. Department of Energy (DOE)
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.
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