Achieving DFT accuracy in short range ordering and stacking fault energy using moment tensor potential for CoCrFeNi and CoCrNi
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| Format: | Preprint |
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2025
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| _version_ | 1866912585879650304 |
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| author | Nitol, Mashroor S. Tamm, Artur Mubassira, Subah Xu, Shuozhi Fensin, Saryu J. |
| author_facet | Nitol, Mashroor S. Tamm, Artur Mubassira, Subah Xu, Shuozhi Fensin, Saryu J. |
| contents | Medium-entropy alloys (MEAs) such as CoCrFeNi and CoCrNi are promising structural materials owing to their outstanding mechanical and thermal properties, which arise from complex chemical disorder and atomic-scale interactions. Although density functional theory (DFT) has provided fundamental insights into these systems, its high computational cost limits exploration of large-scale phenomena. Classical interatomic potentials have been used to address this gap but often lack the fidelity needed to capture many-body interactions and chemical short-range ordering (CSRO) effects. In this work, we developed a machine-learned Moment Tensor Potential (MTP) to bridge accuracy and efficiency. The MTP was trained on a comprehensive DFT database spanning unary to quaternary configurations and reproduces energies, forces, and stresses with near-DFT accuracy across diverse structural and chemical environments. It accurately predicts elastic properties and recovers compositional trends in bulk and shear moduli in agreement with DFT. Hybrid Monte Carlo/molecular dynamics simulations capture CSRO, reproducing key DFT-reported features including Cr-Cr and Fe-Fe repulsion and Ni-Cr ordering. Stacking fault energetics were modeled, yielding ISF energies near 54 mJ/m2 for CoCrNi and 36 mJ/m2 for CoCrFeNi, consistent with DFT predictions. Local chemical environment effects on stacking faults were also resolved: Co-rich planes reduce, whereas Cr- or Fe-rich planes increase, the stacking fault energy. By enabling large-scale, high-fidelity simulations at a fraction of DFT's cost, the developed MTP provides a robust framework for predictive modeling of thermodynamic stability, defect behavior, and mechanical response of FCC MEAs. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2509_11231 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Achieving DFT accuracy in short range ordering and stacking fault energy using moment tensor potential for CoCrFeNi and CoCrNi Nitol, Mashroor S. Tamm, Artur Mubassira, Subah Xu, Shuozhi Fensin, Saryu J. Materials Science Mesoscale and Nanoscale Physics Medium-entropy alloys (MEAs) such as CoCrFeNi and CoCrNi are promising structural materials owing to their outstanding mechanical and thermal properties, which arise from complex chemical disorder and atomic-scale interactions. Although density functional theory (DFT) has provided fundamental insights into these systems, its high computational cost limits exploration of large-scale phenomena. Classical interatomic potentials have been used to address this gap but often lack the fidelity needed to capture many-body interactions and chemical short-range ordering (CSRO) effects. In this work, we developed a machine-learned Moment Tensor Potential (MTP) to bridge accuracy and efficiency. The MTP was trained on a comprehensive DFT database spanning unary to quaternary configurations and reproduces energies, forces, and stresses with near-DFT accuracy across diverse structural and chemical environments. It accurately predicts elastic properties and recovers compositional trends in bulk and shear moduli in agreement with DFT. Hybrid Monte Carlo/molecular dynamics simulations capture CSRO, reproducing key DFT-reported features including Cr-Cr and Fe-Fe repulsion and Ni-Cr ordering. Stacking fault energetics were modeled, yielding ISF energies near 54 mJ/m2 for CoCrNi and 36 mJ/m2 for CoCrFeNi, consistent with DFT predictions. Local chemical environment effects on stacking faults were also resolved: Co-rich planes reduce, whereas Cr- or Fe-rich planes increase, the stacking fault energy. By enabling large-scale, high-fidelity simulations at a fraction of DFT's cost, the developed MTP provides a robust framework for predictive modeling of thermodynamic stability, defect behavior, and mechanical response of FCC MEAs. |
| title | Achieving DFT accuracy in short range ordering and stacking fault energy using moment tensor potential for CoCrFeNi and CoCrNi |
| topic | Materials Science Mesoscale and Nanoscale Physics |
| url | https://arxiv.org/abs/2509.11231 |