$\mathcal{C}-$IBI: Targeting cumulative coordination within an iterative protocol to derive coarse-grained models of (multi-component) complex fluids

Abstract

We present a coarse-graining strategy that we test for aqueous mixtures. The method uses pair-wise cumulative coordination as a target function within an iterative Boltzmann inversion (IBI) like protocol. We name this method coordination iterative Boltzmann inversion ($\mathcal{C}-$IBI). While the underlying coarse-grained model is still structure based and, thus, preserves pair-wise solution structure, our method also reproduces solvation thermodynamics of binary and/or ternary mixtures. Additionally, we observe much faster convergence within $\mathcal{C}-$IBI compared to IBI. To validate the robustness, we apply $\mathcal{C}-$IBI to study test cases of solvation thermodynamics of aqueous urea and a triglycine solvation in aqueous urea.

Cited by in corpus (6)

• Adversarial-Residual-Coarse-Graining: Applying machine learning theory to systematic molecular coarse-graining
• Sequence transferable coarse-grained model of amphiphilic copolymer
• Connecting density fluctuations and Kirkwood-Buff integrals for finite-size systems
• Computing chemical potentials of solutions from structure factors
• Robust Kirkwood-Buff inversion in complex mixtures via reciprocal-space methods
• MARTINI-based Coarse-grained Model for Poly(alpha-peptoid)s