Abstract
Locating global minimum of certain atomistic ensemble is known to be a highly challenging and resource consuming task. This dataset represents joint usage of the semi-empirical PM7 Hamiltonian, Broyden–Fletcher–Goldfarb–Shanno algorithm and basin hopping scheme to navigate a potential energy surface. The Au20 nanocluster was used for calibration as its global minimum structure is well-known. Furthermore, Au18Ag2 and Au15Ag5 were simulated for illustration of the algorithm performance. The work shows encouraging results and, particularly, underlines proper accuracy of PM7 as applied to this type of heavy metal systems. The reported dataset motivates to use the benchmarked method for studying potential energy surfaces of manifold systems and locate their global-minimum atomistic configurations.
Highlights
Locating global minimum of certain atomistic ensemble is known to be a highly challenging and resource consuming task
The Au20 nanocluster was used for calibration as its global minimum structure is well-known
Computer simulations at the Neumann supercomputing cluster Computer simulations at the Neumann supercomputing cluster São Paulo, Brazil All data are in this article
Summary
Systematic and efficient navigating potential energy surface: Data for silver doped gold clusters. Article history: Received 7 December 2015 Received in revised form 8 February 2016 Accepted 5 April 2016 Available online 11 April 2016. Locating global minimum of certain atomistic ensemble is known to be a highly challenging and resource consuming task. This dataset represents joint usage of the semi-empirical PM7 Hamiltonian, Broyden–Fletcher–Goldfarb–Shanno algorithm and basin hopping scheme to navigate a potential energy surface. The reported dataset motivates to use the benchmarked method for studying potential energy surfaces of manifold systems and locate their global-minimum atomistic configurations. & 2016 Elsevier Inc. Published by Elsevier Inc. Published by Elsevier Inc
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