Navigating complex phase diagrams in soft matter systems

TL;DR

This paper introduces a method using dynamical density functional theory to predict complex phase behavior in soft matter systems, significantly speeding up phase diagram mapping and enabling the design of materials with diverse phases.

Contribution

The study demonstrates that the dispersion relation from dynamical density functional theory can predict phase formation, including quasicrystals, in complex soft matter systems.

Findings

The dispersion relation $oldsymbol{ ext{ω}}(k)$ predicts phase stability and crystal formation.

Regions with unstable wavenumbers correspond to crystalline phases.

Tuning interaction potentials can design systems with multiple phases, including quasicrystals.

Abstract

Colloidal fluids can exhibit complex phase behavior and determining phase diagrams via experiments or computer simulations can be laborious. We demonstrate that the dispersion relation $\omega(k)$, obtained from dynamical density functional theory for the uniform density system, is a highly versatile tool for {\it predicting} where in the phase diagram complex crystals form. The sign of $\omega(k)$ determines whether density modes with wavenumber $k$ grow or decay over time. We demonstrate the predictive power by investigating the complex phase behavior of particles interacting via core-shoulder pair potentials. With complementary Monte Carlo simulations, we show that regions of the phase diagram where $\omega(k)$ has one or several unstable (growing) wavenumbers are also where crystalline phases occur. Going further, by tuning these unstable wavenumbers via the interaction-potential and state-point parameters, we design systems with quasicrystals in the phase diagram. We identify a system with a certain shoulder-range exhibiting at least 10 different phases. Our general approach accelerates considerably the mapping of complex phase diagrams, crucial for the design of new materials.