Incipience of Plastic Flow in Aluminum with Nanopores: Molecular Dynamics and Machine-Learning-Based Description
Abstract
:1. Introduction
2. Materials and Methods
2.1. Molecular Dynamics Simulations
2.2. Processing of MD Data and Approximation by Artificial Neural Network
2.3. Density Functional Theory Calculations
2.4. Plasticity and Fracture Model
3. Results
3.1. Dislocation Nucleation in Nanoporous Aluminum
3.2. Verification of Plasticity and Fracture Model and Identification of Parameters
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Parameter | Value |
---|---|
1 J/m2 | |
0.8 eV/b | |
0.5 | |
0.1 | |
200 |
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Mayer, A.E.; Mayer, P.N.; Lekanov, M.V.; Panchenko, B.A. Incipience of Plastic Flow in Aluminum with Nanopores: Molecular Dynamics and Machine-Learning-Based Description. Metals 2022, 12, 2158. https://doi.org/10.3390/met12122158
Mayer AE, Mayer PN, Lekanov MV, Panchenko BA. Incipience of Plastic Flow in Aluminum with Nanopores: Molecular Dynamics and Machine-Learning-Based Description. Metals. 2022; 12(12):2158. https://doi.org/10.3390/met12122158
Chicago/Turabian StyleMayer, Alexander E., Polina N. Mayer, Mikhail V. Lekanov, and Boris A. Panchenko. 2022. "Incipience of Plastic Flow in Aluminum with Nanopores: Molecular Dynamics and Machine-Learning-Based Description" Metals 12, no. 12: 2158. https://doi.org/10.3390/met12122158