Unlocking Atomistic Simulation Potential: Tutorial on DeePMD-kit for Accurate Machine-Trained Models

Explore the cutting-edge world of machine-trained potentials for atomistic simulations in this comprehensive tutorial on DeePMD-kit. Delve into the power of deep neural networks and Gaussian processes, which offer near-quantum mechanical accuracy at a fraction of the computational cost. Learn how these advancements are expanding the horizons of AIMD simulations, enabling systematic exploration of bulk thermodynamic properties, dynamic behavior, and transport properties previously out of reach. Focus on the highly successful DeePMD software developed by Car and colleagues, along with the DPGEN software for dataset preparation and model training. Gain practical insights into implementing these powerful tools through a pedagogical overview, equipping you with the knowledge to leverage machine-trained potentials in your own atomistic simulations. Discover how to unlock new possibilities in materials science and computational chemistry with this essential tutorial on DeePMD-kit and machine-trained models.