| Literature DB >> 30844269 |
Michael T Humbert1, Yong Zhang1, Edward J Maginn1.
Abstract
Reproducibility and accuracy have become increasingly important issues for the molecular simulation community. The availability of validated open-source postprocessing tools to analyze simulation trajectories and compute properties is key to helping researchers conduct more accurate and reproducible simulations. Here we describe a suite of open-source Python-based postprocessing routines we have developed called PyLAT. PyLAT is compatible with the popular molecular dynamics package LAMMPS and enables users to compute viscosities, self-diffusivities, ionic conductivities, molecule or ion pair lifetimes, dielectric constants, and radial distribution functions using best-practice methods.Mesh:
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Year: 2019 PMID: 30844269 DOI: 10.1021/acs.jcim.9b00066
Source DB: PubMed Journal: J Chem Inf Model ISSN: 1549-9596 Impact factor: 4.956