AMDAT: An Open-Source Molecular Dynamics Analysis Toolkit for Supercooled Liquids, Glass-Forming Materials, and Complex Fluids

TL;DR

AMDAT addresses the need for validated, open-source analysis tools tailored to soft matter and glass-forming systems by delivering an in-memory, scriptable MD trajectory analysis toolkit. It combines exponential time sampling with a modular C++ architecture, enabling efficient long-timescale calculations of observables such as $g(r)$, $S(q)$, $F_s(q,t)$, and $G_s(r,t)$ while supporting per-bead and multibody analyses. The paper showcases AMDAT across six representative systems (binLJ, binLJ2D, KG, PNC, PS-30mer, PS-100mer) to highlight local resolution, ISFS, and advanced workflows like custom per-atom read-in and region-specific analysis. This approach offers reproducible, scalable workflows for studying glass formation, polymer dynamics, and complex fluids, providing a practical alternative to in-house analysis tools and enabling deeper insights into long-time relaxation and spatial heterogeneity.

Abstract

AMDAT (Amorphous Molecular Dynamics Analysis Toolkit) is an open-source C++ toolkit for post-processing molecular dynamics trajectories, focused on high-performance static and dynamic analyses of amorphous, glassy, and polymer materials, including supercooled liquids and complex fluids. In this paper, we describe AMDAT's design for efficient long-timescale analysis via in-memory trajectory handling and exponential time sampling, and we demonstrate representative workflows for widely used observables such as radial distribution functions, structure factors, intermediate scattering functions, and neighbor correlations.

Figures (12)

• Figure 1: Radial distribution functions (top) and structure factors (bottom) for binLJ, KG, and PS-30mer systems from left to right.
• Figure 2: Dynamical properties (MSD, ISFS, NGP, NDF) for binLJ, binLJ2D, KG, and PS-30mer systems from left to right.
• Figure 3: Self part of the Van Hove correlation function for the KG system. The figure shows isochronous curves versus distance colored by time according to the displayed color bar.
• Figure 4: Configurations of the binary Lennard-Jones system, colored by different per-particle properties. Panels show a) atom type, b) displacement after 1211.42 $\tau_{LJ}$, c) number of neighbors within a 1.4 $\sigma_{LJ}$ cutoff, and d) number of neighbors in a Voronoi-tessellated cell. Visualization was performed using OVITOOVITO.
• Figure 5: Configurations of the 2D binary Lennard-Jones system, colored by different per-particle properties. Panels show a) atom type, b) displacement after 1211.42 $\tau_{LJ}$, c) 2D (xy) 6-fold hexatic order parameter, d) number of neighbors within a 1.4 $\sigma_{LJ}$ cutoff, and e) number of neighbors in a Voronoi-tessellated box. Visualization was performed using OVITOOVITO.