Hydride-induced embrittlement of metals
Abstract
The purpose of the present project is to investigate the impact of hydride formation on the mechanical properties yttrium (Y) hydrides by means of large-scale atomistic modelling. This aims to investigate the mechanical properties additively materials containing dispersed yttrium hydride precipitates, which are efficient high-density moderators and necessary for commercial realization of microreactor technology.
There are two main objectives. First we aim to model the impact of hydrides on the mobility of dislocations, to predict the increased drag and its influence on the plastic properties and hardening. Possible approaches that can be used to quantify the degree of hardening and to upscale the information to a continuum level include the analytical Friedel Kroupa Hirsch (FKH) and Bacon Kocks Scattergood (BKS) models. They describe the critical (i.e. Peierls) stress required to enable dislocation glide past the obstacles. This information will be used in Discrete Dislocation Dynamics simulations to quantify the hardening on a microscopic length scale. To this end we will need to fit new interatomic potentials for the Y-H systems, which will be trained using DFT data generated herein. In this initial stage we aim to produce semi-empirical angular-dependent potentials (ADP), but our ambition is to initiate the procedure to fit machine-learning potentials based on the atomic-cluster expansion (ACE) formalism. For this part of the project we collaborate with partners at ICAMS at Ruhr University, Bochum. This latter part requires significant amounts of DFT-data generation, based both on ab initio molecular dynamics (AIMD) and conventional self-consistent modelling.
For the second part of the project we will collaborate with partners at Oak Ridge, and Los Alamos National Labs to produce thermal neutron scattering scattering laws for hydride moderated reactor materials (Y hydrides). To this end, we will contribute with ab initio phonon data typically derived from density functional theory modelling. By using AIMD in conjunction with velocity-autocorrelation analysis and the stochastic temperature-dependent effective potential (s-TDEP) method, we anticipate to produce well-described hydrogen phonon densities of states.
