Generalized ensemble method applied to study systems with strong first order transitions

[摘要] At strong first-order phase transitions, the entropy versus energy or, at constant pressure, enthalpy, exhibits convex behavior, and the statistical temperature curve correspondingly exhibits an S-loop or back-bending. In the canonical and isothermal-isobaric ensembles, with temperature as the control variable, the probability density functions become bimodal with peaks localized outside of the S-loop region. Inside, states are unstable, and as a result simulation of equilibrium phase coexistence becomes impossible. To overcome this problem, a method was proposed by Kim, Keyes and Straub [1], where optimally designed generalized ensemble sampling was combined with replica exchange, and denoted generalized replica exchange method (gREM). This new technique uses parametrized effective sampling weights that lead to a unimodal energy distribution, transforming unstable states into stable ones. In the present study, the gREM, originally developed as a Monte Carlo algorithm, was implemented to work with molecular dynamics in an isobaric ensemble and coded into LAMMPS, a highly optimized open source molecular simulation package. The method is illustrated in a study of the very strong solid/liquid transition in water.

[发布机构] Department of Chemistry, Boston University, Boston; MA; 02215-2521, United States^1;Broad Institute of MIT and Harvard, Cambridge; MA; 02142, United States^2

[效力级别] 计算机科学 [学科分类] 计算机科学（综合）

[关键词] Energy distributions;First order transitions;First-order phase transitions;Molecular simulations;Monte carlo algorithms;Replica exchange method;Solid/liquid transitions;Statistical temperature