Dissipative particle dynamics (DPD) is one of the most efficient mesoscale coarse-grained
methodologies for modeling soft matter systems. Here, we comprehensively review the …

By focusing on essential features, while averaging over less important details, coarse-
grained (CG) models provide significant computational and conceptual advantages with …

Dissipative particle dynamics (DPD) belongs to a class of models and computational
algorithms developed to address mesoscale problems in complex fluids and soft matter in …

Coarse-grained (CG) models can provide computationally efficient and conceptually simple
characterizations of soft matter systems. While generic models probe the underlying physics …

Since their emergence in the 1990s, mesoscopic models of fluids have been widely used to
study complex organization and transport phenomena beyond the molecular scale. Even …

Mesoscopic models are widely used to study complex organization and transport
phenomena in chemical and biological systems. Defining a rigorous procedure by which a …

Molecular simulations provide a versatile tool to study the structure, anion conductivity, and
stability of anion-exchange membrane (AEM) materials and can provide a fundamental …

A force-matching-based method for supervised machine learning (ML) of coarse-grained
(CG) free energy (FE) potentials─ known as multiscale coarse-graining via force-matching …

The dynamics of a soft particle suspended in a viscous fluid can be changed by the
presence of an elastic boundary. Understanding the mechanisms and dynamics of soft–soft …

We address the challenge of representativity and dynamical consistency when unbonded
fine-grained particles are collected together into coarse-grained particles. We implement a …