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30. Jul 2020 | Coatings Technologies

Computations of coating windows for reverse roll coating of liquid films

A new paper focuses on the flow stability of reverse roll coating flows employed in practical applications to coat thin liquid films on substrates of different materials.

A computer code on a monitor as a symbol image.

The results obtained formed the basis for a reverse roll coating computer program and its applications. Image source: Free-Photos - Pixabay (symbol image).

Various computer programs are purported to predict the set of parameters that permit stable coating conditions for other coating methods. The application of these programs yields so-called coating windows for each particular coating setup. Knowing these coating windows permits coating methods to be applied with preknowledge of the sets of parameters for stable coatings.

For reverse roll coating, computer codes for predicting coating windows are scarce or even nonexistent, which was the reason for the present work on the analytical considerations.

Results formed the basis for a reverse roll coating computer program

The results obtained formed the basis for a reverse roll coating computer program and its applications. The program is described, and computational results are provided. These are compared with experimental data available in the literature. Good agreement was obtained for high capillary number flows, but there were discrepancies between experimental and computational results for lower capillary numbers.

The experimental results for low capillary number flows also appeared less reliable, which triggered the present experimental work. Some experimental results are given for low capillary numbers and these results are also compared with corresponding numerical data. It is suggested that a test section should be built consisting of two rollers and one slot die to study experimentally the stability regions of reverse roll coating flows in a rigorous manner.

The paper has been published in Journal of Coatings Technology and Research volume 17 (2020).

Image source: Pixabay.

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