Dr. Yevgeny Rakita

My life before BGU:​

I was born in Kiev, Ukraine, and grew up in Kiryat Gat. I studied for my bachelor’s degree at the Department of Chemistry at BGU. I got my master’s at the Department of Materials Science and Engineering at Tel Aviv University and my PhD at the Department of Materials and Interfaces at the Weizmann Institute of Science. I then went to the Data Science Institute at Columbia University in New York for my postdoc.

Why BGU?

BGU is a young, expanding, accessible and professional university, making it a great place to develop new ideas!​

My rese​arch:

I've always been interested in how the order of materials affects their properties. The drive to make scientific and technological breakthroughs has led to a tendency to use increasingly complex materials with different levels of atomic order. Since the arrangement of atoms determines the properties of a given material to achieve breakthroughs in the current state-of-the-art capabilities needed for a certain technology, it is necessary to increase the complexity of those materials.

My research deals with complex material systems, and in particular, finding "order within the disorder" for advanced applications such as neuromorphic computations, materials for renewable energy and more. Glasses and multi-component alloys are an example of complex materials whose development usually involves a process of trial and error (“cook and look") rather than rational design that draws on detailed knowledge of their microscopic structure in its different forms. The goal of my research is to learn the order landscape of complex systems and develop the philosophy through which one can rationally design complex materials.

Glass-forming materials, for example, are “meta-stable" disordered structures, meaning that they are kinetically stabilized and will try to crystalize, or in other words, become more ordered. “Meta-stability" means that properties strongly depend on the history of how a material was made, where understanding and controlling the state or “meta-stability" is what we desire.

Since properties are intertwined with interatomic structure, finding a connection between the history and structure of materials is crucial to the rational design of disordered materials. The emerging machine learning tools, combined with the capability to generate relational data with high throughput, are great news for this task, as they enable the development of complex structural models driven by real experimental information, and thus, the development of “data-driven machine-learned intuition" for the rational design of complex materials.