(39a) The Molecular Simulation Design Framework (MoSDeF) Project: A Collaboration Towards Transparent, Reproducible, Usable By Others, Extensible (TRUE) Simulations | AIChE

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(39a) The Molecular Simulation Design Framework (MoSDeF) Project: A Collaboration Towards Transparent, Reproducible, Usable By Others, Extensible (TRUE) Simulations

Authors 

Gilmer, J. - Presenter, Vanderbilt University
Quach, C. D., Vanderbilt University
Matsumoto, R., Vanderbilt University
Shamaprasad, P., Vanderbilt University
DeFever, R. S., Clemson University
Singh, R., Department of Chemical Engineering, University of
Crawford, B., Wayne State University
Jankowski, E., Boise State University
Jayaraman, A., University of Delaware, Newark
Palmer, J., University of Houston
Maginn, E., University of Notre Dame
Anderson, J.
Glotzer, S. C., University of Michigan
Siepmann, J., University of Minnesota-Twin Cities
Potoff, J., Wayne State University
Iacovella, C., Vanderbilt University
Lédeczi, Á., Vanderbilt University
McCabe, C., Vanderbilt University
Cummings, P., Vanderbilt University

The MoSDeF project is a multi-university collaboration focused on the development of software that enables more reproducible scientific workflows [1]. MoSDeF consists of a collection of Python libraries that facilitate the programmatic initialization of arbitrarily complex systems, force field parameterization, and creation of syntactically correct input files for a variety of molecular dynamics and Monte Carlo simulation engines. This project has enabled multiple large-scale computational screening studies of various soft-matter systems [2-5]. A key aspect of the MoSDeF project is the ability to use a single initialization workflow to support different simulation engines (i.e., GROMACS, LAMMPS, HOOMD-Blue, Cassandra, GOMC) and algorithms, enabling direct comparison and validation of results and software [4,6-8]. In recent years, the collaboration has been focusing on further improving the interoperability between tools within the MoSDeF ecosystem (e.g. mBuild, Foyer, Signac, Cassandra, GOMC), as well as with tools that are widely adopted by the simulation community (e.g. GROMACS, LAMMPS). These efforts result in more integration between different packages, and making them more accessible for user groups coming from different backgrounds. The MoSDeF collaboration also promotes a common set of practices to improve the reproducibility of computational simulation researches, namely the TRUE (Transparent, Reproducible, Usable by others, and Extensible) [9]. The TRUE standard essentially encourages better effort in documenting and reporting the simulation workflows, including all the softwares utilized in the process, in a way such that the results can be regenerated by the audience [9]. Libraries in the MoSDeF ecosystem provide utilities necessary to streamline simulation workflow and ease the reporting process, which have been demonstrated in several studies [4, 6-10]. Here, we provide an overview of the continued improvement, development, and updates to the MoSDeF software stack, highlighting recent case studies [4, 9].



References:

  1. MoSDeF, https://github.com/mosdef-­hub.
  2. A. Z. Summers, J. B. Gilmer, C. R. Iacovella, P.T. Cummings, and C. McCabe. “MoSDeF, a Python Framework Enabling Large-Scale Computational Screening of Soft Matter: Application to Chemistry-Property Relationships in Lubricating Monolayer Films”, Journal of Chemical Theory and Computation 2020 16 (3), 1779-1793, DOI: 10.1021/acs.jctc.9b01183. Chem. B 123, 1340–1347.
  3. M. W. Thompson, R. Matsumoto, R. L. Sacci, N.C. Sanders, P. T. Cummings, 2019. Scalable Screening of Soft Matter: A Case Study of Mixtures of Ionic Liquids and Organic Solvents. J. Phys https://doi.org/10.1021/acs.jpcb.8b11527
  4. P.T. Cummings, C. McCabe, C. R. Iacovella, et al. “Open‐source molecular modeling software in chemical engineering focusing on the Molecular Simulation Design Framework”. AIChE J. 2021; 67:e17206. https://doi.org/10.1002/aic.17206
  5. A. Z. Summers, C. R. Iacovella, P. T. Cummings, and C. McCabe. “Investigating Alkylsilane Monolayer Tribology at a Single-Asperity Contact with Molecular Dynamics Simulation”. Langmuir 2017 33 (42), 11270-11280. DOI: 10.1021/acs.langmuir.7b02479
  6. C. Klein, A. Z. Summers, M. W. Thompson, J. B. Gilmer, C. McCabe, P. T. Cummings, J. Sallai, C. R. Iacovella. Formalizing atom-typing and the dissemination of force fields with foyer. Computational Materials Science 2019, 167, 215-227.
  7. C. Klein, et al. A Hierarchical, Component Based Approach to Screening Properties of Soft Matter BT - Foundations of Molecular Modeling and Simulation: Select Papers from FOMMS 2015. Edited by Randall Q Snurr et al., Springer Singapore, 2016, pp. 79–92, doi:10.1007/978-981-10-1128-3_5.
  8. GMSO: https://github.com/mosdef-hub/gmso.
  9. M. W. Thompson, Justin B. Gilmer, Ray A. Matsumoto, Co D. Quach, Parashara Shamaprasad, Alexander H. Yang, Christopher R. Iacovella, Clare McCabe & Peter T. Cummings (2020) Towards molecular simulations that are transparent, reproducible, usable by others, and extensible (TRUE), Molecular Physics, 118:9-10.
  10. B. Crawford, J. J. Potoff, M. Jansons. “Prediction of Physical Properties and Phase Behavior for Future Jet Fuel Selection Via Monte Carlo Simulations”. November 17 2020, 2020 AIChE Annual Meeting, https://youtu.be/GPaP8tIUY88

Topics 

Computational Molecular Engineering

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