Photo by Li Shen
Dr Li Shen has been awarded funding for work that aims to find a better way to measure the foaming process in drinks and oil lubricants.
Dr Shen (Tribology group) received a EPSRC Impact Acceleration Account (IAA) for the project “Machine-Learning Pattern Recognition Prototype for liquid foams”. The grant supports potentially marketable projects to create impact away from a strictly academic setting.
The aim of the research is to develop a foaming rig which, combined with a Machine-Learning analysis algorithm, will enable a consistent and quantitative analysis of the foaming process in beverages and oil lubricants. Ab Inbev, Pepsico, Shell and PCS instruments are industrial partners.
Dr Shen explains: "Hopefully, when we finish this project, we’ll be able to measure and optimise the “foam-ability” of a drink compared with desired targets, such as diet Colas and non-alcoholic beers having the same foam features as their full counterparts. This is quite an elusive area of food tribology, since taste panels in these areas are both expensive to organise and subjective in their opinions. Our bubble machine hopes to be a better and more objective way to measure the foaming process."
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Nadia Barbu
Department of Mechanical Engineering
