Data of Stable Structure of Ag-Au-Pd Nanoparticles Based on Fish Swarm Algorithm

Ternary alloy nanoparticles have high activity and selectivity, and are widely used in catalytic reactions. However, under high temperature, high pressure, and high catalytic reaction conditions, ternary alloy nanoparticles are prone to agglomeration and precipitation, thereby reducing their stability. How to improve the stability of Au-Ag-Pd nanoparticles during their preparation has become a challenge. This article conducts data analysis on the stable structure of Au-Ag-Pd nanoparticles based on the Fish Swarm Algorithm (FSA). Firstly, through literature review, this article introduces the current research achievements in nanomaterials, providing a foundation for this study. Then, the concept and steps of the FSA are introduced in detail, and a method to improve the traditional artificial FSA is proposed. The improved FSA is used to analyze the stable structure of Ag-Au-Pd nanoparticles, and comparative experiments are designed to verify the superiority of the improved FSA. The stability of Ag-Au-Pd nanoparticles based on FSA is tested through experiments. After interpreting and discussing the results, this article determines the feasibility of analyzing the stable structure of Ag-Au-Pd nanoparticles through the FSA, and also finds the shortcomings of the FSA compared with other algorithms.