BOCS: Bottom-up Open-source Coarse-graining Software

Nicholas J.H. Dunn, Kathryn M. Lebold, Michael R. Delyser, Joseph F. Rudzinski, W. G. Noid

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

We present the BOCS toolkit as a suite of open source software tools for parametrizing bottom-up coarse-grained (CG) models to accurately reproduce structural and thermodynamic properties of high-resolution models. The BOCS toolkit complements available software packages by providing robust implementations of both the multiscale coarse-graining (MS-CG) force-matching method and also the generalized-Yvon-Born-Green (g-YBG) method. The g-YBG method allows one to analyze and to calculate MS-CG potentials in terms of structural correlations. Additionally, the BOCS toolkit implements an extended ensemble framework for optimizing the transferability of bottom-up potentials, as well as a self-consistent pressure-matching method for accurately modeling the pressure equation of state for homogeneous systems. We illustrate these capabilities by parametrizing transferable potentials for CG models that accurately model the structure, pressure, and compressibility of liquid alkane systems and by quantifying the role of many-body correlations in determining the calculated pair potential for a one-site CG model of liquid methanol.

Original languageEnglish (US)
Pages (from-to)3363-3377
Number of pages15
JournalJournal of Physical Chemistry B
Volume122
Issue number13
DOIs
StatePublished - Apr 5 2018

Bibliographical note

Funding Information:
The authors gratefully acknowledge financial support from the National Science Foundation (NSF Grant Nos. MCB-1053970, CHE-1565631), from the Alfred P. Sloan Foundation, and from a Camille Dreyfus Teacher-Scholar Award. This work was also supported by ACS PRF under Grant No. 52100-ND6. We gratefully acknowledge the Donors of the American Chemical Society Petroleum Research fund for support of this research. This work was partially supported by funding from the Penn State Materials Computation Center. Portions of this research were conducted with Advanced CyberInfrastructure computational resources provided by The Institute for CyberScience at The Pennsylvania State University (http://ics.psu.edu). Figure 3 employed VMD. VMD is developed with NIH support by the Theoretical and Computational Biophysics group at the Beckman Institute, University of Illinois at Urbana−Champaign.

Publisher Copyright:
© 2017 American Chemical Society.

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