Development of a machine learning potential for the study of crack propagation in titanium

LJ Shen and Y Wang and WS Lai, INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING, 194, 104514 (2021).

DOI: 10.1016/j.ijpvp.2021.104514

In this paper, a machine learning potential of titanium in the form of moment tensor potential (MTP) is constructed to study the crack propagation behavior of titanium with a pre-crack via molecular dynamics (MD) simulations. The MTP of titanium is obtained by learning the results of the first-principles calculation for various configurations, and is verified to rationally describe the statistic and dynamic property of titanium. Using MTP, MD simulations of a pre-crack on 10 (1) over bar0 and 0001 planes upon loading are performed. The results show that generation of twinning occurs in the 10 (1) over bar0 plane, while generation of partial dislocation occurs in the 0001 plane. MD simulations of a preset microcrack using traditional potential function are also presented and compared with those with MTP.

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