Evidence map›Paper›PMID 40528899›Full record

ReviewJournal of chemical and engineering data2025

Achieving Reproducibility and Replicability of Molecular Dynamics and Monte Carlo Simulations Using the Molecular Simulation Design Framework (MoSDeF).

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 and 12 more

Abstract readReview
In one paragraph

Review in Journal of chemical and engineering data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Nicholas C CravenInterdisciplinary Materials Science Program, Vanderbilt University, Nashville, Tennessee 37235-0106, United States.ORCID https://orcid.org/0000-0002-4607-4377
Ramanish SinghDepartment of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, Minnesota 55455-0132, United States.ORCID https://orcid.org/0000-0002-7908-060X
Co D QuachDepartment of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, Tennessee 37235-1604, United States.ORCID https://orcid.org/0000-0002-1255-4161
Justin B GilmerInterdisciplinary Materials Science Program, Vanderbilt University, Nashville, Tennessee 37235-0106, United States.ORCID https://orcid.org/0000-0002-6915-5591
Brad CrawfordDepartment of Chemical Engineering, Wayne State University, Detroit, Michigan 48202-4050, United States.ORCID https://orcid.org/0000-0003-0638-7333
Eliseo Marin-RimoldiDepartment of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States.
Ryan SmithDepartment of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States.
Ryan DeFeverDepartment of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States.
Maxim S DyukovDepartment of Chemical Engineering, Wayne State University, Detroit, Michigan 48202-4050, United States.
Jenny W FothergillMicron School of Materials Science and Engineering, Boise State University, Boise, Idaho 83725, United States.ORCID https://orcid.org/0000-0001-9665-5420
Chris JonesMicron School of Materials Science and Engineering, Boise State University, Boise, Idaho 83725, United States.
Timothy C MooreDepartment of Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109-2800, United States.ORCID https://orcid.org/0000-0002-5709-7259
Brandon L ButlerDepartment of Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109-2800, United States.
Joshua A AndersonDepartment of Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109-2800, United States.
Christopher R IacovellaDepartment of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, Tennessee 37235-1604, United States.
Eric JankowskiMicron School of Materials Science and Engineering, Boise State University, Boise, Idaho 83725, United States.ORCID https://orcid.org/0000-0002-3267-1410
Edward J MaginnDepartment of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States.ORCID https://orcid.org/0000-0002-6309-1347
Jeffrey J PotoffDepartment of Chemical Engineering, Wayne State University, Detroit, Michigan 48202-4050, United States.ORCID https://orcid.org/0000-0002-4421-8787
Sharon C GlotzerDepartment of Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109-2800, United States.ORCID https://orcid.org/0000-0002-7197-0085
Peter T CummingsDepartment of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, Tennessee 37235-1604, United States.ORCID https://orcid.org/0000-0002-9766-2216
Clare McCabeDepartment of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, Tennessee 37235-1604, United States.ORCID https://orcid.org/0000-0002-8552-9135
J Ilja SiepmannDepartment of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, Minnesota 55455-0132, United States.ORCID https://orcid.org/0000-0003-2534-4507

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Identifiers

PMID40528899
PMCPMC12169611

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.