Kwasi Nyandey

Polish Academy of Sciences

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Daniel Jakubczyk

Polish Academy of Sciences

G. Derkachov

Polish Academy of Sciences

Yaroslav Shopa

Cardinal Stefan Wyszyński University in Warsaw

Anastasiya Derkachova

Institute of Physics

M. Kolwas

Polish Academy of Sciences

Tomasz Wojciechowski

Institute of Physics

Izabela Kamińska

Polish Academy of Sciences

Tomasz Jakubczyk

University of Basel

Cooperative Institutions

Institute of Physics

Polish Academy of Sciences

Czech Academy of Sciences, Institute of Physics

Maj Institute of Pharmacology

Warsaw University of Technology

University of Warsaw

Cardinal Stefan Wyszyński University in Warsaw

Lviv University

Lviv State University of Internal Affairs

Heidelberg University

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Luminescent nanoparticles in a shrinking spherical cavity – probing the evaporating microdroplets of colloidal suspension – optical lattices and structural transitions

Journal of Quantitative Spectroscopy and Radiative Transfer (2022)

Yaroslav Shopa M. Kolwas Izabela Kamińska G. Derkachov Kwasi Nyandey

Suspension

10.1016/j.jqsrt.2022.108439

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Citations (2)

A convolutional neural network technique for online tracking of the radius evolution of levitating evaporating microdroplets of pure liquids, liquid mixtures and suspensions

arXiv (Cornell University) (2024)

Kwasi Nyandey G. Derkachov Daniel Jakubczyk

We have used convolutional neural network in a classification task to track the radius evolution of levitating evaporating microdroplets of pure diethylene glycol, diethylene glycol water polystyrene microparticles suspension, dipropylene glycol water mixture and dipropylene glycol water silica nanoparticles suspension. We discretized a wider radii range into short radii segments, labeled them with class numbers and generated theoretically light scattering patterns from Mie theory. Then the network was trained on the theoretical images and used to classify unlabeled experimentally recorded Mie scattering patterns from the evaporating microdroplets. A plot of the class average radii versus the camera s time step revealed the profile of the entire droplet radius evolution. We were able to work with approximately 1500 classes and showed that the technique has the potential to distinguish droplet size difference of 5 nm. We expect it to be applicable for online or real time tracking of droplet evaporation.

Tracking (education)

10.48550/arxiv.2410.08857

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