Data for the paper "Self-sorting of bidisperse particles in evaporating sessile droplets"

Dataset Description

This dataset contains simulation data corresponding to the study presented in the paper titled:"Self-sorting of bidisperse particles in evaporating sessile droplets"Authors: Aman Kumar Jain, Fabian Denner, and Berend van Wachem

Dataset Structure

The dataset includes six folders, each representing a distinct simulation case (C1 through C6) from Stage 2 of the simulation study, as outlined in Table 3 of the paper.

Cases C1 and C2: Simulate droplets with an initial contact angle of 60°.

Cases C3 and C4: Simulate droplets with an initial contact angle of 90°.

Cases C5 and C6: Correspond to additional conditions as specified in the publication.

In each pair of cases:

Odd-numbered cases (C1, C3, C5) neglect Marangoni stresses.

Even-numbered cases (C2, C4, C6) include Marangoni stresses.

The suffixes in the case folder names denote particle types:

“_S”: Standard silica particles

“_N”: Neutrally buoyant particles

Each case folder contains:

Subdirectories:

Fields: Fluid field data (e.g., velocity, pressure)

DMs: Particle and domain-related metadata

Meshes: Computational mesh files

Particles: Lagrangian particle data

Visualization files:

results.xmf: XMF wrapper for reading fluid data (velocity, pressure, liquid volume fraction α) in ParaView

results_DEM.xmf: XMF wrapper for particle data visualization (e.g., position, velocity)

Particle position data:

Five CSV files representing particle positions at five distinct time instances.

Analysis Script

A Python script named ParticleCombined.py is included. This script processes the particle position CSV files from each case folder to compute particle surface density over time.

Funding Acknowledgment

This research was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Grant No. 452916560.