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Completed H2020 European Commission

Multiscale Modelling of Dissolutive Wetting

€224.9K EUR

Funder European Commission
Recipient Organization Queen Mary University of London
Country United Kingdom
Start Date Mar 01, 2022
End Date Feb 29, 2024
Duration 730 days
Number of Grantees 1
Roles Coordinator
Data Source European Commission
Grant ID 101022470
Grant Description

A moving contact line (MCL) is a moving line of intersection between a fluid/fluid interface and a solid wall.

MCLs are central to a wide range of flows in nature and industry, ranging from surface coating, spray cooling, displacement of oil by CO2, to the recent development of 3D printing, microreactors, and nanotechnology. However, the modelling of MCLs has been a classical challenge.

In particular, when the solid phase can dissolve into the wetting fluids, e.g., in soldering, formation of alloys and manufacturing of composite materials, there are still a few fundamental challenges which have handicapped the development of predictive computational models.

This fellowship project will address those challenges and it has three objectives: (1) to develop a new computational model for 3D direct numerical simulation (DNS) of MCLs on dissolvable solid surfaces, covering both inertial- and diffusion-dominant dissolutive wetting regimes, and resolving nanometer length scales; (2) to develop a novel experimental method using tapping mode atomic force microscopy to directly measure, for the first time of the world, the dynamic contact angle and interface profiles within tens to hundreds of nanometers near the dynamic dissolutive wetting line, and to formulate a theory relating the dynamic contact angle and interface profiles to system parameters; (3) to formulate a reduced-order macroscale computational model which can save computational effort by at least nine orders of magnitude compared with DNS models in numerical simulation of dissolutive wetting.

The project will lead to a step change in our modelling and understanding of dissolutive wetting.

It will enable accurate and affordable simulations which will greatly benefit design and optimization in a vast range of industrial applications.

All Grantees

Queen Mary University of London

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