Design of materials for nuclear energy applications: First-principles calculations and artificial intelligence methods

The review contains a description of modern methods and results of designing new materials for nuclear energy applications. The first part presented in this review contains a description of ab initio methods for calculating of materials properties. It describes rigorous and approximate quantum methods (density functional method) for the predicting the properties of materials employing modern supercomputers, and popular software packages for numerical simulation, as well as databases of first-principles calculations that exist internationally. With the accumulation of a large number of laborious quantum calculations, artificial intelligence methods are becoming more and more effective. In particular, machine learning methods are considered, and results of their use for the design of materials are presented in the review. The results of quantum mechanics modeling of binary alloys of iron, chromium and nickel are presented. The second part of the review will be devoted to quantum modeling of liquid and plasma states of matter in reactors, as well as experimental studies of materials for nuclear power. The third part of the review will be devoted to non-equilibrium plasma formed in reactors as a result of secondary processes during stopping of fast particles.