Physicists developed a "panda" to calculate wetting angles in numerical experiments.

The results have been published in the journal Colloids and Surfaces A: Physicochemical and Engineering Aspects.

Contact Angles characterize the interaction between molecules of a solid surface and liquid. Understanding the contact angle between materials allows for the prediction of their behavior, determination of surface cleanliness, and aids in the creation of hydrophobic and hydrophilic coatings. Theoretical and numerical methods for calculating the contact angle require the input of numerous parameters and depend on defining the position of the phase boundary. This poses a challenge, as the concept of a "phase boundary" is conditional, and there are many criteria for its determination.

“We have relieved researchers in molecular modeling from the need to find the position of the phase boundary — this has reduced the number of adjustable hyperparameters from 8-10 to just two, as used in similar methods. There’s no longer a need to tailor the angle calculation method for each liquid-solid pair; PANDA is universal in this respect. Moreover, there’s no longer any need to apply a transport measuring device to the system image,” said Ilya Kopanichuk, senior researcher at the Center for Computational Physics at MIPT.

The method is based on analytical expressions that describe the surface shapes of one-dimensional density profiles for various types of surfaces formed between immiscible liquids, such as between oil and water. The density profile illustrates how molecules are distributed within the gap space. The study examines all possible forms of the phase boundary between two liquids in a flat gap.

The PANDA method calculates the wetting angle using a one-dimensional density profile. The expressions for the analytical density profile are defined by three parameters: the volume fraction of the non-wetting liquid, the cell size, and the contact angle. If the first two are fixed, which is quite easy to do at the start of the calculation, the angle can be obtained through an optimization procedure that minimizes the deviation of the analytical density profile from that obtained in a numerical experiment.

The researchers tested the algorithm using synthetic data and data from molecular dynamics simulations. PANDA demonstrated high accuracy with an error of less than one percent for most contact angles on synthetic data. For the molecular dynamics data, the algorithm showed better agreement with real experiments than the experiments did with each other.

PANDA simplifies density analysis at the nanoscale by eliminating the need to find the phase boundary. It reduces the number of adjustable parameters to two, making it universal and easy to use. This means the algorithm is applicable to any system without prior adjustment of parameters for specific compositions.

One limitation of PANDA is the need to visualize the droplet shape according to a developed nomenclature (doughnut, droplet, etc.). The researchers plan to remove this limitation through training the PointNet neural network, which will make the calculation of the wetting contact angle using molecular dynamics completely automated.

The PANDA method still requires refinement for use in actual physical experiments. One of the tasks is to develop a universal method for estimating contact angles based on the interference pattern from liquid droplets. Solving this task requires close collaboration with experimental physicists.

The PANDA method is already being utilized in the oil industry for optimizing hydrocarbon extraction and developing new technologies. In the future, PANDA may also be applied in other fields, including materials science and coating technology.

The study involved researchers from the Center for Computational Physics at MIPT, the Institute of Theoretical and Applied Mechanics of the Russian Academy of Sciences, HSE, and AIRI.