forces on atoms, and stresses on unit cells for a sufficiently large number of reference configurations. The necessary reference structures were generated employing the on-the-fly machine-learning force field methodology implemented in VASP56,59, whose conceptual approach has been outlined in the previ...
forces on atoms, and stresses on unit cells for a sufficiently large number of reference configurations. The necessary reference structures were generated employing the on-the-fly machine-learning force field methodology implemented in VASP56,59, whose conceptual approach has been outlined in the previ...
We present a method combining first-principles calculations and machine learning to predict the redox potentials of half-cell reactions on the absolute scale. By applying machine learning force fields for thermodynamic integration from the oxidized to the reduced state, we achieve efficient statistical s...
Ab-initio simulations of materials using VASP: density-functional theory and beyond. J. Comput. Chem. 29, 2044–2078 (2008). Article Google Scholar Lu, Z. Computational discovery of energy materials in the era of big data and machine learning: a critical review. Mater. Rep. Energy 1, ...
The combination worked, yielding force fields for 54 elements in a fraction of the time it once would have taken to find parameters for just one element and proving that reinforcement learning can be a useful tool in continuous action spaces. ...
The MACE-MP models are trained on MPTrj raw DFT energies from VASP outputs, and are not directly comparable to the MP's DFT energies or CHGNet's energies, which have been applied MP2020Compatibility corrections for some transition metal oxides, fluorides (GGA/GGA+U mixing corrections), and ...
The bond angles in the TM@WSn2N4 structure were examined using machine-learning methods, revealing their significant impact on HER catalytic activity. Section snippets DFT calculations Vienna Atomic Number Simulation Package (VASP) was used to calculate density functional theory [28]. The exchange ...
In Section 4, "Other Applications of Machine Learning in Battery Technology," the paper delves into the prediction of Remaining Useful Life (RUL) and State of Health (SOH), illustrating the broad spectrum of applications within this field. The paper culminates in Section 5, providing a ...
Projects that focus on providing data structures used in atomistic machine learning.dpdata (🥇24 · ⭐ 190) - Manipulating multiple atomic simulation data formats, including DeePMD-kit, VASP, LAMMPS, ABACUS, etc. LGPL-3.0 GitHub (👨💻 60 · 🔀 120 · 📦 120 · 📋 93 - ...
We conduct a comparative study of different ML-based interatomic potential schemes, including VASP, MACE, and CHGNet, utilizing various training strategies such as on-the-fly learning, pre-trained universal models, and fine-tuning. By considering different temperatures and concentration regimes, we ...