Determination of the energy landscape of Pd12Pt1 using a combined genetic algorithm and threshold energy method

Abstract

In this work we present a thorough exploration of the potential energy surface (PES) of Pd–Pt bimetallic nanoparticles at the specific composition Pd₁₂Pt₁, using the combination of a genetic algorithm and the threshold method for global optimization and exploration of the barrier structure, employing the semi-empirical Gupta many-body potential for modeling the interatomic interactions. The structural and energetic analysis of Pd₁₂Pt₁ nanoparticles, including binding energies (E_b), symmetries and common-neighbor analysis (CNA) allowed us to identify a large set of representative structures of local minima, with an icosahedral motif found to be the putative global minimum for Pd₁₂Pt₁. A detailed study of the icosahedral motif was carried out by an exhaustive exploration of low energy isomers, in order to understand qualitatively structural interconversion. 2-D tree (disconnectivity) graphs are plotted to map the structures of minima on the PES of Pd₁₂Pt₁. DFT calculations were performed on representative structures to establish the energetic hierarchy and structural stability.