Revealing the dynamic responses of Pb under shock loading based on DFT-accuracy machine learning potential
This work provides theoretical insights into shock-induced phenomena in lead, a model material, but is incremental as it applies an existing machine learning method to new data on Pb-Sn alloys.
The study tackled the challenge of understanding dynamic mechanical behavior in lead under shock loading by using a DFT-accuracy machine learning potential for Pb-Sn alloys, revealing that shock along [001] orientation causes fast, reversible phase transitions without twinning, while [011] orientation leads to slow, irreversible deformation with localized phase transitions.
Lead (Pb) is a typical low-melting-point ductile metal and serves as an important model material in the study of dynamic responses. Under shock-wave loading, its dynamic mechanical behavior comprises two key phenomena: plastic deformation and shock induced phase transitions. The underlying mechanisms of these processes are still poorly understood. Revealing these mechanisms remains challenging for experimental approaches. Non-equilibrium molecular dynamics (NEMD) simulations are an alternative theoretical tool for studying dynamic responses, as they capture atomic-scale mechanisms such as defect evolution and deformation pathways. However, due to the limited accuracy of empirical interatomic potentials, the reliability of previous NEMD studies is questioned. Using our newly developed machine learning potential for Pb-Sn alloys, we revisited the microstructure evolution in response to shock loading under various shock orientations. The results reveal that shock loading along the [001] orientation of Pb exhibits a fast, reversible, and massive phase transition and stacking fault evolution. The behavior of Pb differs from previous studies by the absence of twinning during plastic deformation. Loading along the [011] orientation leads to slow, irreversible plastic deformation, and a localized FCC-BCC phase transition in the Pitsch orientation relationship. This study provides crucial theoretical insights into the dynamic mechanical response of Pb, offering a theoretical input for understanding the microstructure-performance relationship under extreme conditions.