A Density Functional Theory-Based Particle Swarm Optimization Investigation of Metal Sulfide Phases for Ni-Based Catalysts

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.