fig1
![Taking materials dynamics to new extremes using machine learning interatomic potentials](https://image.oaes.cc/d8e9f3d3-419e-442f-b38a-1f98bd5ff6b7/4486.fig.1.jpg)
Figure 1. The strategy of machine learning interatomic potential development. The main processes include data generation, feature representation, ML regression, and model evaluation. Active learning is used to update and optimize the performance of the best potential at any instant. DFT: Density functional theory; ML: machine learning.