Classical dynamical density functional theory (DDFT) is one of the cornerstones of modern
statistical mechanics. It is an extension of the highly successful method of classical density …

The rich and diverse dynamics of particle-based systems ultimately originates from the
coupling of their degrees of freedom via internal interactions. To arrive at a tractable …

We present a hybrid scheme based on classical density functional theory and machine
learning for determining the equilibrium structure and thermodynamics of inhomogeneous …

Hard-sphere systems are one of the fundamental model systems of statistical physics and
represent an important reference system for molecular or colloidal systems with soft …

In this tutorial review, we discuss the use of classical density functional theory (DFT) to
understand adsorption/desorption hysteresis phenomena for fluids confined in mesoporous …

The optical, electronic, and mechanical properties of graphite, few-layer, and two-
dimensional (2D) materials have prompted a considerable number of applications …

Interfacial liquid layers play a central role in a variety of phenomena ranging from friction to
molecular recognition. Liquids near a solid surface form an interfacial layer where the …

Stratification in binary colloidal mixtures was investigated using implicit-solvent molecular
dynamics simulations. For large particle size ratios and film Péclet numbers greater than …

The swift progression and expansion of machine learning (ML) have not gone unnoticed
within the realm of statistical mechanics. In particular, ML techniques have attracted attention …

We describe a test particle approach based on dynamical density functional theory (DDFT)
for studying the correlated time evolution of the particles that constitute a fluid. Our theory …