Nicholas C. Craven, Ramanish Singh, Co D. Quach, Justin B. Gilmer, Brad Crawford, Eliseo Marin-Rimoldi, Ryan Smith, Ryan DeFever, Maxim S. Dyukov, Jenny W. Fothergill, Chris Jones, Timothy C. Moore, Brandon L. Butler, Joshua A. Anderson, Christopher R. Iacovella, Eric Jankowski, Edward J. Maginn, Jeffrey J. Potoff, Sharon C. Glotzer, Peter T. Cummings*, Clare McCabe* and J. Ilja Siepmann*,
{"title":"利用分子模拟设计框架(MoSDeF)实现分子动力学和蒙特卡罗模拟的再现性和可复制性","authors":"Nicholas C. Craven, Ramanish Singh, Co D. Quach, Justin B. Gilmer, Brad Crawford, Eliseo Marin-Rimoldi, Ryan Smith, Ryan DeFever, Maxim S. Dyukov, Jenny W. Fothergill, Chris Jones, Timothy C. Moore, Brandon L. Butler, Joshua A. Anderson, Christopher R. Iacovella, Eric Jankowski, Edward J. Maginn, Jeffrey J. Potoff, Sharon C. Glotzer, Peter T. Cummings*, Clare McCabe* and J. Ilja Siepmann*, ","doi":"10.1021/acs.jced.5c0001010.1021/acs.jced.5c00010","DOIUrl":null,"url":null,"abstract":"<p >Molecular simulations are increasingly used to predict thermophysical properties and explore molecular-level phenomena beyond modern imaging techniques. To make these tools accessible to nonexperts, several open-source molecular dynamics (MD) and Monte Carlo (MC) codes have been developed. However, using these tools is challenging, and concerns about the validity and reproducibility of the simulation data persist. In 2017, Schappals et al. reported a benchmarking study involving several research groups independently performing MD and MC simulations using different software to predict densities of alkanes using common molecular mechanics force fields [ <cite><i>J. Chem. Theory Comput.</i></cite> <span>2017</span>, 4270−4280]. Although the predicted densities were reasonably close (mostly within 1%), the data often fell outside of the combined statistical uncertainties of the different simulations. Schappals et al. concluded that there are unavoidable errors inherent to molecular simulations once a certain degree of complexity of the system is reached. The Molecular Simulation Design Framework (MoSDeF) is a workflow package designed to achieve TRUE (<u>T</u>ransparent, <u>R</u>eproducible, <u>U</u>sable-by-others, and <u>E</u>xtensible) simulation studies by standardizing the implementation of molecular models for various simulation engines. This work demonstrates that using MoSDeF to initialize a simulation workflow results in consistent predictions of system density, even while increasing model complexity.</p>","PeriodicalId":42,"journal":{"name":"Journal of Chemical & Engineering Data","volume":"70 6","pages":"2178–2199 2178–2199"},"PeriodicalIF":2.1000,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/epdf/10.1021/acs.jced.5c00010","citationCount":"0","resultStr":"{\"title\":\"Achieving Reproducibility and Replicability of Molecular Dynamics and Monte Carlo Simulations Using the Molecular Simulation Design Framework (MoSDeF)\",\"authors\":\"Nicholas C. Craven, Ramanish Singh, Co D. Quach, Justin B. Gilmer, Brad Crawford, Eliseo Marin-Rimoldi, Ryan Smith, Ryan DeFever, Maxim S. Dyukov, Jenny W. Fothergill, Chris Jones, Timothy C. Moore, Brandon L. Butler, Joshua A. Anderson, Christopher R. 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Achieving Reproducibility and Replicability of Molecular Dynamics and Monte Carlo Simulations Using the Molecular Simulation Design Framework (MoSDeF)
Molecular simulations are increasingly used to predict thermophysical properties and explore molecular-level phenomena beyond modern imaging techniques. To make these tools accessible to nonexperts, several open-source molecular dynamics (MD) and Monte Carlo (MC) codes have been developed. However, using these tools is challenging, and concerns about the validity and reproducibility of the simulation data persist. In 2017, Schappals et al. reported a benchmarking study involving several research groups independently performing MD and MC simulations using different software to predict densities of alkanes using common molecular mechanics force fields [ J. Chem. Theory Comput.2017, 4270−4280]. Although the predicted densities were reasonably close (mostly within 1%), the data often fell outside of the combined statistical uncertainties of the different simulations. Schappals et al. concluded that there are unavoidable errors inherent to molecular simulations once a certain degree of complexity of the system is reached. The Molecular Simulation Design Framework (MoSDeF) is a workflow package designed to achieve TRUE (Transparent, Reproducible, Usable-by-others, and Extensible) simulation studies by standardizing the implementation of molecular models for various simulation engines. This work demonstrates that using MoSDeF to initialize a simulation workflow results in consistent predictions of system density, even while increasing model complexity.
期刊介绍:
The Journal of Chemical & Engineering Data is a monthly journal devoted to the publication of data obtained from both experiment and computation, which are viewed as complementary. It is the only American Chemical Society journal primarily concerned with articles containing data on the phase behavior and the physical, thermodynamic, and transport properties of well-defined materials, including complex mixtures of known compositions. While environmental and biological samples are of interest, their compositions must be known and reproducible. As a result, adsorption on natural product materials does not generally fit within the scope of Journal of Chemical & Engineering Data.