Jump to main content
Jump to site search


Addressing the temperature transferability of structure based coarse graining models

Author affiliations

Abstract

Systematically derived coarse grained (CG) models for molecular liquids do not inherently guarantee transferability to a state point different from its reference, especially when derived on the basis of structure based CG methods like Inverse Monte Carlo (IMC). Several efforts made in the past years to improve the transferability of these models focused on including thermodynamic constraints or on the application of multistate parametrization. Das and Andersen (DA) [Das et al., J. Chem. Phys., 2010, 132, 164106.] proposed a different Ansatz. They derived a correction term added to the system's Hamiltonian to reproduce the virial pressure and the volume fluctuations of the reference system in the CG resolution which does not require further adjustment of the effective pair potential. Herein, we discuss the possibility to achieve temperature transferability with IMC models for selected alkanes following the optimization of the DA approach as proposed by Dunn and Noid (DN) [Dunn et al., J. Chem. Phys., 2015, 143, 243148.]. The work focuses on a novel approach to determine the DN correction term for different state points by linear interpolation.

Graphical abstract: Addressing the temperature transferability of structure based coarse graining models

Back to tab navigation

Publication details

The article was received on 08 Dec 2017, accepted on 12 Feb 2018 and first published on 12 Feb 2018


Article type: Paper
DOI: 10.1039/C7CP08246K
Citation: Phys. Chem. Chem. Phys., 2018, Advance Article
  •   Request permissions

    Addressing the temperature transferability of structure based coarse graining models

    D. Rosenberger and N. F. A. van der Vegt, Phys. Chem. Chem. Phys., 2018, Advance Article , DOI: 10.1039/C7CP08246K

Search articles by author

Spotlight

Advertisements