This project primarily focuses on research related to 'Numerical evaluation of the effect of the twist angle on phonon hydrodynamics in twisted bilayer graphene'. It includes input and output files associated with the machine-learned potential functions, as well as animation files of the structures in the training set. Below is a summary of the document's contents along with a brief introduction:
| File name | Brief description |
|---|---|
| 1.mp4 | front view of training set animation display |
| 2.mp4 | side view of training set animation display |
| nep.in | NEP Input parameters |
| nep.txt | NEP potential parameters |
| train.xyz | training data for the construction |
| energy_train.out | target and predicted energies for training data set |
| force_train.out | target and predicted forces for training data set |
| virial_train.out | target and predicted virials for training data set |
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- NEP refers to Neuroevolution Potential. For more information, please visit https://gpumd.org.
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- If you use the data from this project please refer to my article 'Numerical evaluation of the effect of the twist angle on phonon hydrodynamics in twisted bilayer graphene;DOI: 10.1103/PhysRevB.110.245305'. Email: shiqian@ynu.edu.cn、 wnren@kust.edu.cn、crkedu6@gmail.com and yangdi0620@126.com.