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A Density Functional Theory-Based Particle Swarm Optimization Investigation of Metal Sulfide Phases for Ni-Based
Houyu Zhu1, Xiaohan Li1, Xiaoxin Zhang2
1Shandong Key Laboratory of Intelligent Energy Materials, School of Materials Science and Engineering, China University of Petroleum (East China), Qingdao 266580, China.
Abstract:
Nickel (Ni) catalysts have numerous applications in the chemical industry, but they are susceptible to sulfurization, with their sulfurized structures and underlying formation mechanisms remaining unclear. Herein, density functional theory (DFT) combined with the particle swarm optimization (PSO) algorithm is employed to investigate the low-energy structures and formation mechanisms of sulfide phases on Ni(111) surfaces, especially under high-sulfur-coverage conditions where traditional DFT calculations fail to reach convergence. Using (3×3 ) Ni(111) slab models, we identify a sulfurization limit, finding that each pair of deposited sulfur atoms can sulfurize one layer of three Ni atoms at most (Ni:S = 3:2), with additional sulfur atoms penetrating deeper layers until saturation. Under typical reactive adsorption desulfurization conditions, the ab initio thermodynamics analysis indicates that Ni3S2 is the most stable sulfide phase, consistent with sulfur K-edge XANES data. Unsaturated phases, including Ni3S, Ni2S, and Ni9S5, represent intermediate states towards saturation, potentially explaining the diverse Ni sulfide compositions observed in experiments.

