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Monthly talks by academic and industry leaders from around the world.

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March 2020

Physics Guided Neural Networks for the Design and Understanding of Materials

March 30, 2020 @ 11:00 am - 12:00 pm

Tian Xie (MIT)


  Abstract: Climate change demands faster material innovations in multiple domains to reduce the carbon emissions of various industrial processes, but it currently takes 10-20 years to develop a single material with conventional human-driven approaches due to the large amounts of trail and errors needed. Machine learning approaches enable the direct learning of structure-property relations of materials from data, which have the potential to accelerate the search of materials and understand new scientific knowledge. However, one central challenge in developing…

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April 2020

Uncovering atomistic mechanisms of crystallization using Machine Learning

April 1, 2020 @ 11:00 am - 12:00 pm

Rodrigo Freitas (Stanford University)


  Abstract: Solid-liquid interfaces have notoriously haphazard atomic environments. While essentially amorphous, the liquid has short-range order and heterogeneous dynamics. The crystal, albeit ordered, contains a plethora of defects ranging from adatoms to dislocation-created spiral steps. All these elements are of paramount importance in the crystal growth process, which makes the crystallization kinetics challenging to describe concisely in a single framework. In this seminar I will introduce a novel data-driven approach to systematically detect, encode, and classify all atomic-scale mechanisms…

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