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

TL;DR

This paper introduces $ ext{C-IBI}$, a novel coarse-graining method that targets cumulative coordination to efficiently derive models of complex fluids, accurately reproducing thermodynamics and converging faster than traditional IBI.

Contribution

The paper proposes $ ext{C-IBI}$, a new iterative coarse-graining approach that incorporates cumulative coordination, improving convergence speed and thermodynamic accuracy for complex fluid mixtures.

Findings

$ ext{C-IBI}$ converges faster than traditional IBI.

The method accurately reproduces solvation thermodynamics.

Robustness confirmed on aqueous urea and triglycine solutions.

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.