含水合物沉积物体系分子模拟势函数的发展与应用OA

This review examines advancements in potential functions for hydrate-bearing sediments,analyzing the evolution of single-phase optimization,multiphase interface parameter correction,and machine learning integration methodologies to elucidate how parameterization strategies regulate multiphysics simulation accuracy.Current potential functions face challenges in extreme temperature-pressure adaptability,multiphase parameter compatibility,computational efficiency-accuracy balance,and experimental validation.Future research should focus on developing extreme-environment adaptive multiphase potential function systems,constructing multi-physics coupling models integrating traditional force fields with machine learning potentials,and establishing experimental-simulation collaborative validation frameworks.to provide multi-scale theoretical support from atomic mechanisms to reservoir responses for safe hydrate exploitation.