|About this Abstract
||2017 TMS Annual Meeting & Exhibition
||Computational Approaches to Materials for Energy Applications
||Structure Prediction in Novel Energy Materials Design
||Maximilian Amsler, Chris Wolverton
|On-Site Speaker (Planned)
Recently, novel approaches in computational materials science have led to significant advances in materials design, including high-throughput calculations, data-mining and machine learning. Another increasingly popular technique is ab-initio structure prediction, such as the Minima Hopping Method, which implements a highly efficient global geometry optimization algorithm to identify thermodynamically stable and metastable compounds. I will illustrate how this method can be used to tackle materials design challenges from different perspectives, supported by examples of its recent, successful application.