A numerical toy model of Langevin dynamics provides real-time visualization of colloidal microdroplet evaporation

TL;DR

This paper introduces a GPU-accelerated numerical model of nanoparticle aggregation in evaporating microdroplets, validated against experiments, enabling real-time visualization of complex colloidal phenomena.

Contribution

The authors developed a versatile, real-time GPU-based Langevin dynamics model for nanoparticle aggregation in evaporating droplets, validated with experimental data and publicly available code.

Findings

Model successfully simulates nanoparticle aggregation and evaporation phenomena.

Validation against experiments shows accurate reproduction of scattering revival and nanoparticle structures.

The model handles up to 250,000 particles with various interactions and provides detailed statistical analysis.

Abstract

We have developed and tested a simplified but versatile numerical model of nanoparticles' aggregation using Langevin dynamics. The model is particularly capable of simulating aggregation in an evaporating (or condensing) microdroplet. It runs on a graphics processing unit (GPU), which makes it sufficiently fast for real-time conceptualization tasks. We have verified the results of modeling against the findings from two types of experiments we conducted in electrodynamic traps. Firstly, our model helped us to elucidate the phenomenon of scattering `revival', often observed during the evaporation of composite microdroplets. Further on, we were able to mimic our experiments, in which the microdroplets were dried up to form nanoparticle (NP) aggregates, and then soft-landed. Thus we could compare model predictions with SEM imaging. The model was tested for up to $2.5\times 10^5$ nanoparticles of several coexisting types. Several types of interactions can be accounted for: inter-particle: Lennard-Jones and Coulomb; external: dispersion medium viscosity, centrifugal force, gravity, surface tension, and interface movement. Brownian motion of nanoparticles can be freely controlled. The core program is accompanied by scripts extracting statistical NP aggregates properties in post-processing -- fractal dimension and radial distribution functions. The codes are made available in public repositories. Several diverse evolution scenarios are presented.