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Deformation and phase transformation of dual-phase Ti under tension and compression process
Thi-Thuy Binh Ngo1, Van-Thuc Nguyen2, Te-Hua Fang3
1Department of Mechanical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, 807, Taiwan.
Context:
This study utilizes molecular dynamics (MD) simulation to investigate polycrystalline dual-phase titanium (DP Ti) deformation behavior and phase transformation under tensile and compressive loading. The analysis focuses on the influence of hexagonal close-packed (HCP) phase fraction, strain rate, and temperature on the mechanical properties and microstructural evolution. The results indicate that increasing the HCP phase fraction enhances the elastic modulus (36.5%), yield strength, and strain hardening while maintaining acceptable ductility. The optimal mechanical performance is achieved at 75.4% HCP phase fraction. Strain rate has significantly influenced mechanical response, with higher rates promoting increased yield strength, elastic modulus, dislocation activity, and phase transformations to body-centered cubic (BCC) and amorphous phases. In contrast, raising the temperature from 300 to 900 K results in thermal softening, reduced strength, and diminished dislocation activity, alongside pronounced HCP-to-BCC phase transformation. Interphase boundaries are critical in shaping the deformation mechanisms, influencing dislocation evolution and strain hardening. During deformation, Shockley, Hirth, and other partial dislocations appear. These findings offer valuable insights into the deformation mechanisms and phase behavior of DP Ti, emphasizing its potential for applications requiring a balance between strength and ductility.
Methods:
The simulations utilized the open-source software LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) for modeling atomic-scale interactions. Visualization of the evolving atomic structures was performed using OVITO (Open Visualization Tool). To analyze microstructural changes, the Dislocation Extraction Algorithm (DXA) and Common Neighbor Analysis (CNA) methods were employed.
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