IMX Talks - Random Walk on Foams

This presentation gives a perspective at foam physics research at Aalto. The story starts with basic studies of foam (an elastoplastic material) yielding mixed up with machine learning to understand the data. Then we move over to a lucky discovery and its consequences: how to make bio-based solid foams exploiting wet foam rheology, These materials may be and need to be tailored to various purposes like better water resistance or foam structure. We point to two start-ups that resulted from playing around with foams. Finally, the talk wraps up foam design by showing how this can be sped up exploiting Bayesian Optimization, a surrogate for machine learning.

Bio: Mikko Alava is a professor at Aalto University, Finland and held until recently a secondary appointment as the director at the NOMATEN Center of Excellence at the National Center for Nuclear Research in Poland. Alava has focused on the complex behavior of all kinds of materials from paper to dislocation physics in metals using the microscope of statistical physics. and lately this has expanded to (bio-based) foams as a plastics substitute. Foams are an example of the process-structure-property paradigm in materials science, and are thus a prime candidate for the application of machine learning tools.