Development and initial applications of an e-ReaxFF description of Ag nanoclusters

Metal nanocrystals are of considerable scientific interest because of their uses in electronics, catalysis, and spectroscopy, but the mechanisms by which nanocrystals nucleate and grow to achieve selective shapes are poorly understood. Ab initio calculations and experiments have consistently shown that the lowest energy isomers for small silver nanoparticles exhibit twodimensional (2D) configurations and that a transition into three-dimensional (3D) configurations occurs with the addition of only a few atoms. We parameterized an e-ReaxFF potential for Ag nanoclusters (N ≤ 20 atoms) that accurately reproduces the 2D-3D transition observed between the Ag5 and Ag7 clusters. This potential includes a four-body dihedral term that imposes an energetic penalty to 3D structures that is significant for small clusters, but is overpowered by the bond energy from out-of-plane Ag-Ag bonds in larger 3D clusters. The potential was fit to data taken from density-functional theory and coupled-cluster calculations and compared to an embedded atom method potential to gauge its quality. We also demonstrate the potential of e-ReaxFF to model redox reactions in silver halides and plasmon motion using molecular dynamics simulations. This is the first case in which e-ReaxFF is used to describe metals. Furthermore, the inclusion of a bond-order dependent dihedral angle in this force field is a unique solution to modelling the 2D-3D transition seen in small metal nanoclusters.

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Work Title Development and initial applications of an e-ReaxFF description of Ag nanoclusters
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Open Access
Creators Adrianus Van Duin; Benjamin Evangelisti
Version number 1
Keyword ReaxFF
License All rights reserved
Work Type Article
Acknowledgments We acknowledge support and training provided by the Computational Materials Education and Training (CoMET) NSF Research Traineeship (grant number DGE-1449785). Simulations in this work were conducted in part with Advanced Cyberinfrastructure computational resources provided by the Institute for Cyber Science at the Pennsylvania State University
Publication Date 2020
Deposited February 23, 2021 20:14

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  • Updated Acknowledgments Show Changes
    Acknowledgments
    • We acknowledge support and training provided by the Computational Materials Education and Training (CoMET) NSF Research Traineeship (grant number DGE-1449785). Simulations in this work were conducted in part with Advanced Cyberinfrastructure computational resources provided by the Institute for Cyber Science at the Pennsylvania State University
  • Added Creator Adrianus Van Duin
  • Added Creator Benjamin Evangelisti
  • Added Evangelisti_JCP20-AR-CLMD2020-02365_accepted.pdf
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