||Advances in theoretical understanding, algorithms, and computational power are enabling computational tools to play an increasing role in materials discovery, development, and optimization . Recently application of data mining techniques, genetic algorithms, machine learning approaches, and predictive empirical potentials demonstrate the “virtual synthesis” of novel materials, with their properties being predicted on a computer before ever being synthesized in a laboratory. This symposium will cover recent methodological developments and applications at the frontier of computational materials science and materials informatics, ranging from quantum-level prediction to macro-scale property optimization. The goal is to cover basic research topics in an interdisciplinary approach, which connects theory and experiment, with a view towards materials applications. Of particular interest is computational and theoretical work that features a strong connection to experiment.
- Application of materials informatics approaches such as data mining, genetic algorithms, cluster expansions, and machine-learning for structures, properties, and processing
- Innovations that improve accuracy and efficiency of computational materials design
- Computational discovery and design of novel materials, such as 2D materials and materials for energy technologies
- Semi-empirical models of interatomic interaction