Accelerating Materials Discovery with Data-Driven Atomistic Computational Tools

Time: Wednesday, October 11, 2017 - 2:30pm - 3:30pm
Type: Seminar Series
Presenter: Prof. Chris Wolverton; Dept. of Materials Science and Engineering. Northwestern University
Room/Office: Room 107
Mason Lab
9 Hillhouse Avenue
New Haven, CT 06511
United States

Department of Mechanical Engineering & Materials Science Seminar

Professor Chris Wolverton
Dept. of Materials Science and Engineering
Northwestern University

"Accelerating Materials Discovery with Data-Driven Atomistic Computational Tools"

Many of the key technological problems associated with alternative energies (e.g., thermoelectrics, advanced batteries, hydrogen storage, etc.) may be traced back to the lack of suitable materials. Both the materials discovery and materials development processes may be greatly aided by the use of computational methods, particular those atomistic methods based on density functional theory (DFT). Here, we present an overview of our recent work utilizing high-throughput computation and data mining approaches to accelerate materials discovery, specifically highlighting several new approaches. We describe our high-throughput DFT database, the Open Quantum Materials Database (OQMD), which contains over 450,000 DFT calculations and is freely available for public use at We show how this type of large database can be used to effectively screen for new materials with desired properties and show examples of this screening approach for batteries, thermoelectrics, structural metals, etc. We also describe a machine learning approach to construct a materials screening model based on an extensive set of thousands of DFT calculations. The resulting model, which has "learned" rules of chemistry from these many examples, can predict the stability of arbitrary compositions without requiring any a priori knowledge of crystal structure, at about six orders of magnitude lower computational expense than the original QM tools. We use this model to scan—in a matter of minutes—roughly 1.6 million candidate compositions for novel ternary compounds (AxByCz), and predict roughly 4,500 new stable materials.

Wednesday, October 11, 2017
2:30 – 3:30 pm
Location – Mason 107

Host: Professor Jan Schorers

Refreshments served at 2:15 pm