Abstract
As the need for energy transition increases, the quest for cleaner alternative sources is all time high. Hydrogen has the potential to lead this transition owing to its clean and sustainable make-up. Nonetheless, one of the major challenges to hydrogen powered economy stems from the detrimental hydrogen-defect interaction in steels, ultimately leading to embrittlement. In the past century, several different embrittlement mechanisms have been proposed following experimental and numerical investigations at different time and length scale[1]. Yet, a thorough understanding of the operating conditions of these mechanisms, specifically the role of hydrogen-defect dynamics and the quantification of local hydrogen concentration is still lacking.
The primary focus of the present work is on investigating the nano/micro-scale interaction of hydrogen with lattice defects in iron, specifically the dislocations and how their interaction influences the macroscopic mechanical behaviour. For accurately predicting the hydrogen-lattice defect interaction, DFT calculations are performed. The energetics of hydrogen at different defects is investigated and discussed with the
existing literature studies. Additionally, based on this existing DFT database, a new DFT accurate machine learning (GAP[2]) based Fe-H potential is developed. To further obtain novel insights on the influence of hydrogen on the mobility of bcc edge dislocations, molecular dynamic simulations are performed using the developed GAP Fe-H potential and empirical EAM potential[3]. The critical shear stress for the glide of an edge dislocation in presence of hydrogen is computed and discussed as a function of the hydrogen concentration.