WEB180926 - Data-Centric Science for Materials Innovation
With the development of high-speed computers, networks, and huge storage, researchers can utilize a large volume and wide variety of materials data generated by experimental facilities and computations. The emergence of these big data and advanced analytical techniques has opened unprecedented opportunities for materials research. The September, 2018 issue of MRS Bulletin will focus on the numerous efforts in developing and utilizing databases of electronic structure calculations and their impact on addressing different classes of problems in materials science.
The talks in this webinar will complement the MRS Bulletin issue, and an interactive Q&A will be held with each of the speakers following their talks.
Talk Presentations:
- Harnessing the Materials Project for machine learning and accelerated discovery
Shyam Dwaraknath, Lawrence Berkeley National Laboratory - NOMAD: The FAIR concept for big data-driven materials science
Claudia Draxl, Fritz-Haber-Institut - Accelerating the adoption of materials informatics
Muratahan Aykol, Toyota Research Institute
Talk Presentations:
- Harnessing the Materials Project for machine learning and accelerated discovery
Shyam Dwaraknath, Lawrence Berkeley National Laboratory
Talk begins at 10:42
- NOMAD: The FAIR concept for big data-driven materials science
Claudia Draxl, Fritz-Haber-Institut
Talk begins at 42:01
- Accelerating the adoption of materials informatics
Muratahan Aykol, Toyota Research Institute
Talk begins at 1:00:16
