Fe-TiC-H machine learning interatomic potential for predicting hydrogen segregation and diffusion in TiC/Fe

Abstract

Carbide particles act as effective hydrogen traps that can mitigate hydrogen embrittlement in steels, with their trapping efficacy governed by the binding energy of hydrogen at atomic-scale sites within the carbide and at the carbide/matrix interface. Within the carbide, carbon vacancies are established trap sites, while at the carbide/matrix interface, multiple distinct trap sites may form depending upon the interface character. State-of-the-art experimental methods cannot attribute binding energies to individual sites unambiguously, particularly at the carbide/matrix interface, where distinct trap sites may exhibit similar binding energies. Density functional theory (DFT) calculations have partially addressed this limitation, but their computational cost prohibits accurate treatment of semicoherent and incoherent interfaces, for which hydrogen binding energies remain poorly characterised. In this work, we develop a DFT-accurate machine-learning Fe–TiC–H interatomic potential that enables simulations of hydrogen energetics and kinetics at various TiC/Fe interfaces in the Baker–Nutting orientation. Predictions of structural, dynamic and energetic properties of both bulk phases (i.e., bcc Fe and rocksalt TiC) and the coherent interface with and without hydrogen are in good agreement with DFT. We apply the potential to examine the atomic structure and hydrogen trapping at semicoherent and incoherent interfaces. We find that the binding energy of hydrogen at misfit dislocations is similar to that at coherent interfaces, with a difference of no more than 0.1 eV. However, the misfit strain field reduces carbon vacancy formation energies at the interface, where hydrogen can be trapped with similar binding energies as that in a bulk C vacancy (approximately –1 eV). Lower vacancy formation energies are also found at the incoherent interface, where hydrogen binding energies span a broader range, depending sensitively on the local atomic environment. Overall, the results enable interpretation of experimental observations of hydrogen segregation around semicoherent and incoherent TiC interfaces.