MCCCS-MN

RESOURCE

Abstract

The MCCCS‒MN (Monte Carlo for Complex Chemical Systems‒Minnesota) software is developed by the Siepmann research group at the University of Minnesota. MCCCS‒MN allows for the simulation of multi-component molecular systems in the canonical, isobaric-isothermal (including constant stress for solids), grand-canonical, semi-grand, and Gibbs (NVT, NPT, and more than two simulation boxes) ensembles. It uses the configurational-bias Monte Carlo method to efficiently sample phase space for linear, branched and cyclic chain molecules, the adiabatic nuclear and electronic sampling Monte Carlo method to treat many-body polarization effects, and the aggregation-volume-bias Monte Carlo algorithm to efficiently sample the spatial distribution of associating molecules. MCCCS-MN employs a molecular representation of the system where force fields contain bonded and non-bonded terms. Funding for the development of MCCCS-MN through grants from the National Science Foundation (simulation of fluid phase equilibria and chromatography) and the Department of Energy (simulation of adsorption equilibria) is gratefully acknowledged.
Developers:
Siepmann, J. [1] Martin, Marcus [1] Chen, Bin [1] Wick, Collin [1] Stubbs, John [1] Potoff, Jeffrey [1] Eggimann, Becky [1] McGrath, Matthew [1] Zhao, Xin [1] Anderson, Kelly [1] Rafferty, Jake [1] Rai, Neeraj [1] Maerzke, Katie [1] Keasler, Samuel [1] Bai, Peng [1] Fetisov, Evgenii [1] Shah, Mansi [1] Chen, Qile [1] DeJaco, Robert [1] Chen, Jingyi [1] Xue, Bai [1] Bunner, Colin [1] Sun, Yangzesheng [1] Josephson, Tyler [1] Chang, Chun-Kai [1] Singh, Ramanish [1] Liu, Hsiao-Feng [1]
  1. University of Minnesota - Twin Cities (United States)
Release Date:
2025-12-28
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Programming Languages:
Fortran
Version:
25.1
Licenses:
GNU General Public License v3.0
Sponsoring Org.:
Code ID:
172633
Research Org.:
University of Minnesota - Twin Cities
Country of Origin:
United States

RESOURCE

Citation Formats

Siepmann, J. I., Martin, Marcus G., Chen, Bin, Wick, Collin D., Stubbs, John M., Potoff, Jeffrey J., Eggimann, Becky L., McGrath, Matthew J., Zhao, Xin S., Anderson, Kelly E., Rafferty, Jake L., Rai, Neeraj, Maerzke, Katie A., Keasler, Samuel J., Bai, Peng, Fetisov, Evgenii O., Shah, Mansi S., Chen, Qile P., DeJaco, Robert F., Chen, Jingyi L., Xue, Bai, Bunner, Colin, Sun, Yangzesheng, Josephson, Tyler R., Chang, Chun-Kai, Singh, Ramanish, and Liu, Hsiao-Feng. MCCCS-MN. Computer Software. https://github.com/SiepmannGroup/MCCCS-MN_v25.1.git. USDOE Office of Science (SC), Basic Energy Sciences (BES), US National Science Foundation. 28 Dec. 2025. Web. doi:10.11578/dc.20251228.7.
Siepmann, J. I., Martin, Marcus G., Chen, Bin, Wick, Collin D., Stubbs, John M., Potoff, Jeffrey J., Eggimann, Becky L., McGrath, Matthew J., Zhao, Xin S., Anderson, Kelly E., Rafferty, Jake L., Rai, Neeraj, Maerzke, Katie A., Keasler, Samuel J., Bai, Peng, Fetisov, Evgenii O., Shah, Mansi S., Chen, Qile P., DeJaco, Robert F., Chen, Jingyi L., Xue, Bai, Bunner, Colin, Sun, Yangzesheng, Josephson, Tyler R., Chang, Chun-Kai, Singh, Ramanish, & Liu, Hsiao-Feng. (2025, December 28). MCCCS-MN. [Computer software]. https://github.com/SiepmannGroup/MCCCS-MN_v25.1.git. https://doi.org/10.11578/dc.20251228.7.
Siepmann, J. I., Martin, Marcus G., Chen, Bin, Wick, Collin D., Stubbs, John M., Potoff, Jeffrey J., Eggimann, Becky L., McGrath, Matthew J., Zhao, Xin S., Anderson, Kelly E., Rafferty, Jake L., Rai, Neeraj, Maerzke, Katie A., Keasler, Samuel J., Bai, Peng, Fetisov, Evgenii O., Shah, Mansi S., Chen, Qile P., DeJaco, Robert F., Chen, Jingyi L., Xue, Bai, Bunner, Colin, Sun, Yangzesheng, Josephson, Tyler R., Chang, Chun-Kai, Singh, Ramanish, and Liu, Hsiao-Feng. "MCCCS-MN." Computer software. December 28, 2025. https://github.com/SiepmannGroup/MCCCS-MN_v25.1.git. https://doi.org/10.11578/dc.20251228.7.
@misc{ doecode_172633,
title = {MCCCS-MN},
author = {Siepmann, J. I. and Martin, Marcus G. and Chen, Bin and Wick, Collin D. and Stubbs, John M. and Potoff, Jeffrey J. and Eggimann, Becky L. and McGrath, Matthew J. and Zhao, Xin S. and Anderson, Kelly E. and Rafferty, Jake L. and Rai, Neeraj and Maerzke, Katie A. and Keasler, Samuel J. and Bai, Peng and Fetisov, Evgenii O. and Shah, Mansi S. and Chen, Qile P. and DeJaco, Robert F. and Chen, Jingyi L. and Xue, Bai and Bunner, Colin and Sun, Yangzesheng and Josephson, Tyler R. and Chang, Chun-Kai and Singh, Ramanish and Liu, Hsiao-Feng},
abstractNote = {The MCCCS‒MN (Monte Carlo for Complex Chemical Systems‒Minnesota) software is developed by the Siepmann research group at the University of Minnesota. MCCCS‒MN allows for the simulation of multi-component molecular systems in the canonical, isobaric-isothermal (including constant stress for solids), grand-canonical, semi-grand, and Gibbs (NVT, NPT, and more than two simulation boxes) ensembles. It uses the configurational-bias Monte Carlo method to efficiently sample phase space for linear, branched and cyclic chain molecules, the adiabatic nuclear and electronic sampling Monte Carlo method to treat many-body polarization effects, and the aggregation-volume-bias Monte Carlo algorithm to efficiently sample the spatial distribution of associating molecules. MCCCS-MN employs a molecular representation of the system where force fields contain bonded and non-bonded terms. Funding for the development of MCCCS-MN through grants from the National Science Foundation (simulation of fluid phase equilibria and chromatography) and the Department of Energy (simulation of adsorption equilibria) is gratefully acknowledged.},
doi = {10.11578/dc.20251228.7},
url = {https://doi.org/10.11578/dc.20251228.7},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20251228.7}},
year = {2025},
month = {dec}
}