2019 Van Horn Distinguished Lectures: 2: the materials genome
Channel: bhadeshia123
Date: 27/06/2019

2019 Van Horn Distinguished Lectures: Part 2 - the materials genome and the transformation of materials science through ab-initio computing.

The Kent R. van Horn Lectureship is an endowed Lectureship at the Case Western Reserve University and dates from 1974. It honours Kent R. van Horn, an alum, who had a distinguished career as a metallurgist, director of research, and ultimately corporate vice-president of Alcoa. Three lectures on varied topics are to be delivered over three successive days. The 2019  lectures were delivered by Gerbrand Ceder, who is the Chancellor's Professor of Materials Science and Engineering at University of California, Berkeley. He is notable for his pioneering research in high-throughput computational materials design, and in the development of novel lithium-ion battery technologies.

Abstract: Novel materials design is a critical capability to address several urgent societal problems. But materials development is difficult and time consuming due to the lack of quantitative information on the properties, synthesis and behavior of novel materials. Ab-initio computing, whereby the basic properties of compounds are predicted by solving the basic equations of quantum mechanics, have become remarkably powerful and widespread in the field of materials research. New density functionals have increased the accuracy of energy-based predictions to the level needed for predicting crystal structure stability, and chemical reactivity. I will show how this has led to many examples of novel computer-designed compounds which have been successfully synthesized in the laboratory. More recently, the confluence of ab-initio methods, high- throughput computing, and data science has created the ability to computationally explore the properties of multiple thousands of compounds and use them for compound searching or as input to machine learning models. As one example of this, the Materials Project (www.materialsproject.com), has delivered computed data to the community on an unparalleled scale.

With computational property design becoming faster and more accurate, the field is becoming increasingly limited by the time required needed to synthesize new materials in a predictive and controlled manner. In particular, an understanding of which compounds can be formed and under which condition they can be made would enhance the focus on computational materials design towards feasible, synthesizable materials I will discuss the scientific ideas that can lead to a predictive theory of synthesis, and give several examples where the synthesis path for metastable compounds can be predicted.
These videos are reproduced courtesy of the Materials Science and Engineering Department of Case Western Reserve University.

http://engineering.case.edu/materials-science-and-engineering
http://www.phase-trans.msm.cam.ac.uk