The MachQu project will develop new probabilistic programming and active machine learning methods, and apply these to a currently very active topic in materials physics. It utilizes state-of-the art machine learning methods to develop new efficient quantum mechanics- based simulation tools of atomic migration processes in materials in the extreme conditions of fusion reactors and particle accelerators. The results of the materials simulations can be used for knowledge-based design of complex alloyed materials that can withstand extreme conditions.
|Effective start/end date||01/01/2018 → 31/12/2019|
- 113 Computer and information sciences
- 216 Materials engineering
- 114 Physical sciences