A HANDS-ON COURSE ON TOOLS FOR NOVEL-MATERIALS DISCOVERY SEPTEMBER 24-27, 2018
Luca Ghiringhelli (Fritz Haber Institute of the Max Planck Society)
Markus Rampp (MPCDF)
Matthias Scheffler (Fritz-Haber-Institut der Max-Planck-Gesellschaft)
Angelo Ziletti (Fritz Haber Institute of the Max Planck Society (FHI), Berlin )
Big data, machine learning and artificial intelligence are revolutionizing numerous fields, and materials science is no exception. In this timely moment, NOMAD summer will introduce novice and advanced researchers (in academia and industry) to data-driven computational methods but also practical - and readily usable - tools for novel materials discovery developed within the Novel Materials Discovery (NOMAD) Centre of Excellence.
An enormous amount of materials data, with millions of CPU hours spent every day in HPC centers worldwide, are already stored in data repositories. These data represents an invaluable resource. But how to extract knowledge from it?
The NOMAD Center of Excellence (https://NOMAD-CoE.eu) develops tools to obtain insight into physical processes in materials. Converting inputs and outputs produced by many different computer codes into a common format ensures that they can be compared to each other. This makes data ready for the next steps, that are urgently needed in academia and industry and that are the focus of this Summer School: making Big Data of materials comprehensible to the outside world.
In particular, this school will introduce both novice and advanced researchers in academia and industry to methods and practical tools to:
1. upload, share, and download materials science data using the NOMAD Repository and Archive;
2. visualize physical processes and complex relationships between materials properties with Advanced Graphics;
3. search and retrieve the vast amount of computed materials properties using the NOMAD Encyclopedia;
4. identify correlations and structure in big data of materials, towards the final goal of predicting novel materials with tailored properties with NOMAD Analytics-Toolkit.
The school will feature 7 sessions on the different topics listed below. Each session will be comprised of talks (45 min) by the invited speakers introducing the topics and hands on sessions guided by tutors from the NOMAD team. In the attached program the topical sessions including the team presenting each topic (speakers and tutors) are detailed. Additionally, we will include keynote talks by international researchers on the forefront of data-driven materials science to speak on relevant timely topics.
Workshop information provided by CECAM
Besides focusing the summer school on the tools developed within the NOMAD CoE, we will include also external researchers on the forefront of data-driven materials science.
Selected topics are
- Exploratory Data Analysis and Causal Inference (J. Vreeken)
- Data-driven Rational Materials Design (R. Ramprasad)
- High-throughput Calculations (G. Ceder)
- Dimensionality reduction for Big-Data analytics (M. Ceriotti)