Condensed Matter Seminar Series

Recycling information in quantum calculations of materials properties

 Prof. Stefano Curtarolo (http://alpha.mems.duke.edu)

Dept. of Mechanical Engineering and Materials Science, Duke University

Abstract:  Predicting and characterizing the crystal structure of materials is a key problem in materials research and development. It is typically addressed with highly accurate quantum mechanical computations on a small set of candidate structures, or with empirical rules that have been extracted from a large amount of experimental information, but have limited predictive power. In the case of alloys, it is not always easy to determine their structure and phase stability: a skilled scientist might guess a reasonable answer based on his/her own previous experience. Unfortunately, ab-initio techniques do not accumulate any experience or knowledge!  In this seminar, I describe a radically different approach, which informs new ab-initio investigations with knowledge obtained from results already collected on other systems through data mining methods. I show that the energies of different crystal structures are strongly correlated between different chemical systems, and demonstrate how this correlation can be used to boost phase stability investigation of new systems. This approach leads to a better and more quantifiable extraction of information from ab-initio calculations, and ultimately to a more efficient microscopic description.

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