Publications around the MoSDeF Ecosystem
Klein, C., Sallai, J., Jones, T.J., Iacovella, C.R., McCabe, C., Cummings, P.T.,
2016. A Hierarchical, Component Based Approach to Screening Properties of Soft Matter, in: Snurr, R.Q.,
Adjiman, C.S., Kofke, D.A. (Eds.), Foundations of Molecular Modeling and Simulation: Select Papers from
FOMMS 2015, Molecular Modeling and Simulation. Springer Singapore, Singapore, pp. 79–92. https://doi.org/10.1007/978-981-10-1128-3_5
Klein, C., Summers, A.Z., Thompson, M.W., Gilmer, J.B., McCabe, C., Cummings, P.T.,
Sallai, J., Iacovella, C.R., 2019. Formalizing atom-typing and the dissemination of force fields with
foyer. Computational Materials Science 167, 215–227. https://doi.org/10.1016/j.commatsci.2019.05.026
Thompson, M.W., Matsumoto, R., Sacci, R.L., Sanders, N.C., Cummings, P.T., 2019.
Scalable Screening of Soft Matter: A Case Study of Mixtures of Ionic Liquids and Organic Solvents. J.
Phys. Chem. B 123, 1340–1347. https://doi.org/10.1021/acs.jpcb.8b11527
Cummings, Peter T, and Justin B Gilmer. “Open-Source Molecular Modeling Software in
Chemical Engineering.” Current Opinion in Chemical Engineering, Frontiers of Chemical
Engineering: Molecular Modeling, 23 (March 1, 2019): 99–105. https://doi.org/10.1016/j.coche.2019.03.008.
Jankowski, Eric, Neale Ellyson, Jenny W. Fothergill, Michael M. Henry, Mitchell H.
Leibowitz, Evan D. Miller, Mone’t Alberts, et al. “Perspective on Coarse-Graining, Cognitive Load, and
Materials Simulation.” Computational Materials Science 171 (January 1, 2020): 109129. https://doi.org/10.1016/j.commatsci.2019.109129.
Thompson, Matthew W., Ray Matsumoto, Robert L. Sacci, Nicolette C. Sanders, and Peter
T. Cummings. “Scalable Screening of Soft Matter: A Case Study of Mixtures of Ionic Liquids and Organic
Solvents.” The Journal of Physical Chemistry B 123, no. 6 (February 14, 2019): 1340–47. https://doi.org/10.1021/acs.jpcb.8b11527.
Dice, Bradley D., Vyas Ramasubramani, Eric S. Harper, Matthew P. Spellings, Joshua A.
Anderson, and Sharon C. Glotzer. “Analyzing Particle Systems for Machine Learning and Data Visualization
with Freud.” Proceedings of the 18th Python in Science Conference, 2019, 27–33. https://doi.org/10.25080/Majora-7ddc1dd1-004.