Report
Development of Interatomic Potential for Al-Tb Alloy by Deep Neural Network Learning Method
| العنوان: | Development of Interatomic Potential for Al-Tb Alloy by Deep Neural Network Learning Method |
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| المؤلفون: | Tang, L., Yang, Z. J., Wen, T. Q., Ho, K. M., Kramer, M. J., Wang, C. Z. |
| سنة النشر: | 2020 |
| المجموعة: | Condensed Matter Physics (Other) |
| مصطلحات موضوعية: | Condensed Matter - Materials Science, Condensed Matter - Disordered Systems and Neural Networks, Physics - Computational Physics |
| الوصف: | An interatomic potential for Al-Tb alloy around the composition of Al90Tb10 was developed using the deep neural network (DNN) learning method. The atomic configurations and the corresponding total potential energies and forces on each atom obtained from ab initio molecular dynamics (AIMD) simulations are collected to train a DNN model to construct the interatomic potential for Al-Tb alloy. We show the obtained DNN model can well reproduce the energies and forces calculated by AIMD. Molecular dynamics (MD) simulations using the DNN interatomic potential also accurately describe the structural properties of Al90Tb10 liquid, such as the partial pair correlation functions (PPCFs) and the bond angle distributions, in comparison with the results from AIMD. Furthermore, the developed DNN interatomic potential predicts the formation energies of crystalline phases of Al-Tb system with the accuracy comparable to ab initio calculations. The structure factor of Al90Tb10 metallic glass obtained by MD simulation using the developed DNN interatomic potential is also in good agreement with the experimental X-ray diffraction data. |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1039/D0CP01689F |
| URL الوصول: | http://arxiv.org/abs/2001.06762 |
| رقم الانضمام: | edsarx.2001.06762 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1039/D0CP01689F |
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