Hatch Harold W, Siderius Daniel W, Shen Vincent K
Chemical Informatics Research Group, Chemical Sciences Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899-8380, USA.
J Chem Phys. 2024 Sep 7;161(9). doi: 10.1063/5.0224283.
FEASST is an open-source Monte Carlo software package for particle-based simulations. This software, which was released in 2017, has been used to study phase equilibrium, self-assembly, aggregation or gelation in biological materials, colloids, polymers, ionic liquids, and adsorption in porous networks. We highlight some of the unique features available in FEASST, such as flat-histogram grand canonical ensemble, Gibbs ensemble, and Mayer-sampling simulations with support for anisotropic models and parallelization with flat-histogram and prefetching. We also discuss how the challenges of supporting a variety of Monte Carlo algorithms were overcome by an object-oriented design. This also allows others to extend classes, which improves software interoperability, as inspired by LAMMPS classes and user packages. This article describes version 0.25.1 with benchmarks, compilation instructions, and introductory tutorials for running, restarting, and testing simulations, user guidelines, software design strategies, alternative interfaces, and the test-driven development strategy.
FEASST是一个用于基于粒子模拟的开源蒙特卡罗软件包。该软件于2017年发布，已被用于研究生物材料、胶体、聚合物、离子液体中的相平衡、自组装、聚集或凝胶化，以及多孔网络中的吸附。我们重点介绍了FEASST中一些独特的功能，如平直方图巨正则系综、吉布斯系综以及支持各向异性模型的迈耶抽样模拟，并通过平直方图和预取实现并行化。我们还讨论了如何通过面向对象设计克服支持多种蒙特卡罗算法所面临的挑战。这也允许其他人扩展类，从而提高软件的互操作性，其灵感来自于LAMMPS类和用户包。本文介绍了0.25.1版本，包括基准测试、编译说明以及运行、重启和测试模拟的入门教程、用户指南、软件设计策略、替代接口和测试驱动开发策略。
