Abstract
Atomistic scale simulation can predict state transition processes such as adsorption, diffusion, and reaction. The challenge of the accurate prediction is to obtain a global view of many local minima and saddle points on the potential energy surface (PES) of a material system. The transition conditions are determined by the saddle points on the PES with the minimum energy barrier between local minima. In this paper, a new algorithm is developed to exhaustively search local minima and saddle points within a region of PES in order to provide a global view of the energy landscape. Unlike the existing saddle point search methods, the algorithm represents a transition path by a parametric Bézier curve with control points. It uses multiple groups of such curves, each of which represents a multistage transition path. During the searching process, each group of curves communicates with others to maintain cohesion and avoid collision based on a collective potential model. The algorithm is integrated with density functional theory calculation and demonstrated by diffusion of hydrogen atoms in the FeTiH system.
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He, L., Wang, Y. (2015). A Curve Swarm Algorithm for Global Search of State Transition Paths. In: Poole, W., et al. Proceedings of the 3rd World Congress on Integrated Computational Materials Engineering (ICME 2015). Springer, Cham. https://doi.org/10.1007/978-3-319-48170-8_17
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DOI: https://doi.org/10.1007/978-3-319-48170-8_17
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-48612-3
Online ISBN: 978-3-319-48170-8
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