Friction and wear processes on the molecular scale (Nanotribology), stochastic processes, renewable energy conversion systems and machine learning

The works performed in our research group are important research topics especially in the areas of tribology, stochastic processes and wind energy. The works are highly appropriate for the future enhancement and implementation of superlubricity and utility-scale wind energy power systems.

Concerning tribology, we present the influence of the shape and orientation of the different surfaces in contact in atomic friction, and on the properties of the energy barriers opposing the sliding. The results on the dynamical super-lubricity to reduce friction due to mechanical vibrations are also presented. We show how the surface shape largely influences the behavior of the atomic friction force in the presence of thermal and/or mechanical excitations. For stochastic processes, our activities focused on stochastic resonance, transport and diffusion phenomena leading to the theoretical prediction of stochastic resonance of a damped brownian particle in a non-sinusoidal periodic shape deformable potential submitted to an external periodic field. Lastly, some of our results on the understanding and control of frictional power losses in renewable conversion systems under real-time operation conditions using AI are presented. The results obtained will both increase the energy conversion systems efficiency and decrease environmental impact.