Discover the SciOpen Platform and Achieve Your Research Goals with Ease.
Search articles, authors, keywords, DOl and etc.
Boron carbide, a typical lightweight and high-strength ceramic material, has broad application prospects in national defense, military, and aerospace. However, the nanoscale amorphous shear band, which mainly arises from the destruction of icosahedra, is easily formed in boron carbide under impact, thereby causing its catastrophic shear failure. Since the formation of amorphous shear band of boron carbide significantly depends on its microstructures, molecular dynamics simulations have become a key approach to reveal the microstructural evolutions and mechanisms. However, due to the insufficient accuracy of classical atomistic potentials, classical molecular dynamics simulations face significant challenges in simulating complex material systems, such as boron carbide. In recent years, the development of machine learning methods has provided a new research paradigm for the development of atomic potentials. Among numerous machine-learning atomistic potentials, the deep potential (DP) model, which is based on deep neural networks, is particularly widely applied. This DP model can not only maintain the accuracy comparable to that of ab initio simulations, but also exhibits the efficiency comparable to that of classical molecular dynamics simulations. Thus, the DP model has become an effective strategy to examine complex material systems. In the present study, we systematically examine the research of the DP method on boron carbide ceramics. Firstly, the theoretical framework, development process of the DP model, and the construction and validation of the DP model for boron carbide are summarized. Subsequently, the mechanical responses and the localized amorphization mechanisms of boron carbide are revealed using deep potential molecular dynamics simulations. Then, some strategies are proposed to enhance the ductility of boron carbide, including microalloying, stoichiometry regulation, grain boundary engineering, and defect control. Finally, the application prospects of the DP model in the research of complex material systems, such as boron carbide, are explored.
This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc/4.0/)
Comments on this article