Hybrid molecule/cluster statistical thermodynamics (HMCST) method is an efficient tool to simulate nano-scale systems under quasi-static loading at finite temperature.In this paper,a self-adaptive algorithm is developed for this method.Explicit refinement criterion based on the gradient of slip shear deformation and a switching criterion based on generalized Einstein approximation is proposed respectively.Results show that this self-adaptive method can accurately find clusters to be refined or transferred to molecules,and efficiently refine or transfer the clusters.Furthermore,compared with fully atomistic simulation,the high computational efficiency of the self-adaptive method appears very attractive.