Abstract
To understand the physics of hydrogen embrittlement at the atomic scale, a general-purpose neural network interatomic potential (NNIP) for the $\ensuremath{\alpha}$-iron and hydrogen binary system is presented. It is trained using an extensive reference database produced by density functional theory (DFT) calculations. The NNIP can properly describe the interactions of hydrogen with various defects in $\ensuremath{\alpha}$-iron, such as vacancies, surfaces, grain boundaries, and dislocations; in addition to the basic properties of $\ensuremath{\alpha}$-iron itself, the NNIP also handles the defect properties in $\ensuremath{\alpha}$-iron, hydrogen behavior in $\ensuremath{\alpha}$-iron, and hydrogen-hydrogen interactions in $\ensuremath{\alpha}$-iron and in vacuum, including the hydrogen molecule formation and dissociation at the $\ensuremath{\alpha}$-iron surface. These are superb challenges for the existing empirical interatomic potentials, like the embedded-atom method based potentials, for the $\ensuremath{\alpha}$-iron and hydrogen binary system. In this study, the NNIP was applied to several key phenomena necessary for understanding hydrogen embrittlement, such as hydrogen charging and discharging to $\ensuremath{\alpha}$-iron, hydrogen transportation in defective $\ensuremath{\alpha}$-iron, hydrogen trapping and desorption at the defects, and hydrogen-assisted cracking at the grain boundary. Unlike the existing interatomic potentials, the NNIP simulations quantitatively described the atomistic details of hydrogen behavior in the defective $\ensuremath{\alpha}$-iron system with DFT accuracy.
Highlights
The hydrogen-induced mechanical performance degradation of metals and all phenomena associated with its deleterious effects are known as hydrogen embrittlement (HE) [1,2], which is a prominent problem in current societal and technological requirements [3]
The network interatomic potential (NNIP) quality is estimated by the root-mean-squared error (RMSE) of energies (E ) and forces (F ) primarily used to guide the optimization of adjustable parameters: RMSE(E ) =
Combining the grand canonical Monte Carlo (GCMC) method [109] with molecular dynamics (MD) simulations, we studied the radial distribution function of hydrogen volume density around various defects
Summary
The hydrogen-induced mechanical performance degradation of metals and all phenomena associated with its deleterious effects are known as hydrogen embrittlement (HE) [1,2], which is a prominent problem in current societal and technological requirements [3]. Iron and its alloys are the most widely used structural materials in various industries due to their excellent mechanical properties and low cost. The development of iron alloys with HE resistance requires a deep understanding of the interaction between hydrogen and the defects in the iron alloy’s matrix [4]. Experimental examination of the role played by hydrogen in metals is extremely challenging owing to its high diffusivity, low solubility, and small size [5]. Computer simulations at the atomic level can provide insightful information. Electronic structure calculations, such as density functional theory (DFT), supply the most accurate potential
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