Applications of the ASE database: Efficient calculational workflows and data sharing

Data-driven approaches combined with electronic structure calculations have a huge potential to guide the discovery of new materials. However, this paradigm relies on the development of sophisticated tools and software for storing, sharing and generating calculational results. Here, the ASE database provides a solid foundation for storing and sharing atomic structures and calculational results. In this talk I will discuss recent upgrades to the ASE database, and give examples of how it can be used to support automated calculational workflows, and machine learning driven discoveries. Also, I will demonstrate how the ASE database can be used for web-server implementations, as used on the open database platforms Catalysis-Hub [1] and the Computational Materials Repository [2]. Finally I will discuss some challenges and possible extensions to the current ASE database implementation.

References:

1. K. T. Winther, M. J. Hoffmann, J. R. Boes, O. Mamun, M. Bajdich, and T. Bligaard, Scientific Data 6, Article number: 75 (2019)
2. https://cmr.fysik.dtu.dk/