A new algorithm for contact angle estimation in molecular dynamics simulations

TL;DR

This paper introduces a novel, efficient algorithm for estimating contact angles directly from molecular dynamics simulations, utilizing density filtering and circle fitting techniques to automate and streamline the analysis of wetting properties.

Contribution

The paper presents a new algorithm that automates contact angle estimation in MD simulations using density-based interface detection and circle fitting, improving efficiency and accuracy.

Findings

Algorithm successfully estimates contact angles across various MD setups.

Automates the process, reducing manual effort and potential errors.

Applicable to different potentials and thermostat methods in water simulations.

Abstract

It is important to study contact angle of a liquid on a solid surface to understand its wetting properties, capillarity and surface interaction energy. While performing transient molecular dynamics (MD) simulations it requires calculating the time evolution of contact angle. This is a tedious effort to do manually or with image processing algorithms. In this work we propose a new algorithm to estimate contact angle from MD simulations directly and in a computationally efficient way. This algorithm segregates the droplet molecules from the vapor molecules using Mahalanobis distance (MND) technique. Then the density is smeared onto a 2D grid using 4th order B-spline interpolation function. The vapor liquid interface data is estimated from the grid using density filtering. With the interface data a circle is fitted using Landau method. The equation of this circle is solved for obtaining the contact angle. This procedure is repeated by rotating the droplet about the vertical axis. We have applied this algorithm to a number of studies (different potentials and thermostat methods) which involves the MD simulation of water.