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

A comprehensive understanding of interfacial behavior in water/oil/surfactant systems is
critical to evaluating the performance of emulsions in various industries, specifically in the oil …

Process-directed self-assembly refers to processes that reproducibly trap the kinetics of
structure formation that ensues after a sudden change (“quench”) of the thermodynamic …

Thermoset resin, which is commonly used as a matrix in carbon-fiber-reinforced plastic,
requires curing procedures. We propose a curing simulation technique involving a …

Understanding and predicting the equilibrium behaviour of chemically reacting systems in
highly non-ideal environments is critical to many fields of science and technology, including …

We present a new and computationally efficient methodology using osmotic ensemble
Monte Carlo (OEMC) simulation to calculate chemical potential–concentration curves and …

Hybrid molecular dynamics/Monte Carlo simulations are used to study melts of unentangled,
thermoreversibly associating supramolecular polymers. In this first of a series of papers, we …

We propose a kinetic chain growth algorithm for coarse‐grained (CG) simulations in this
work. By defining the reaction probability, it delivers a description of consecutive …

Biomembranes wrapping cells and organelles are not only the partitions that separate the
insides but also dynamic fields for biological functions accompanied by membrane shape …

We present a general, flexible framework for a constant-energy variant of the dissipative
particle dynamics method that allows chemical reactions (DPD-RX). In our DPD-RX …