Department: Mechanical Engineering
Institution: Imperial College London
Email: j.ewen@imperial.ac.uk
Phone: 
Websitehttps://www.imperial.ac.uk/people/j.ewen

Research summary

James P. Ewen is a Royal Academy of Engineering (RAEng) Research Fellow in the Tribology Group, Department of Mechanical Engineering, Imperial College London.

He studies solid-liquid interfaces using molecular simulations run on supercomputers. Most of his research involves identifying links between the nanoscale behaviour of lubricants and their macroscale performance. His research is highly interdisciplinary in nature and is of direct relevance to industry. He has collaborated with several industrial (Shell, SKF, Afton Chemical, Baker Hughes, and Procter & Gamble) and academic (ETH Zürich, University of Bologna, University of Saarland, TU Delft, Russian Academy of Sciences, and University of California Merced) partners to help solve important engineering problems. He is also a Visiting Research Fellow at Swinburne University of Technology, Australia. He is current an Assistant Supervisor for five PhD students.

In 2020, he was awarded a RAEng Research Fellowship for the project ‘Controlling Friction through Molecular Engineering’. He was awarded the Innovation in Tribology Award by the Institute of Physics (IOP) in 2019 and the Tribology Bronze Medal in 2018 by the Institution of Mechanical Engineers (IMechE). In 2017, he received a Doctoral Prize Fellowship from the Engineering and Physical Sciences Research Council (EPSRC). In the same year, he was awarded the Margaret Fishenden Centenary Memorial Prize for the best PhD Thesis in the Department of Mechanical Engineering over the previous five-year period. He is also a co-organiser of Web Seminar Series on Tribology (WeSST).

Keywords

Adsorption, Chemo-Mechanical Processes, Confined Fluids, Fluid-Solid Interactions, Foams, Glass Transition, High Pressure, Molecular Adsorption, Nanotribology, Self-Assembly, Soft Condensed Matter, Extreme Conditions, Oxide Surfaces, Ab Initio M.D., Coarse Graining Techniques, Massively Parallel Computing, QM/MM

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