Original paper
Probing Atomic Distributions in Mono- and Bimetallic Nanoparticles by Supervised Machine Learning
Abstract
Properties of mono- and bimetallic metal nanoparticles (NPs) may depend strongly on their compositional, structural (or geometrical) attributes, and their atomic dynamics, all of which can be efficiently described by a partial radial distribution function (PRDF) of metal atoms. For NPs that are several nanometers in size, finite size effects may play a role in determining crystalline order, interatomic distances, and particle shape. Bimetallic...
Paper Details
Title
Probing Atomic Distributions in Mono- and Bimetallic Nanoparticles by Supervised Machine Learning
Published Date
Dec 3, 2018
Journal
Volume
19
Issue
1
Pages
520 - 529
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Notes
History