Collinear-spin machine learned interatomic potential for ${\mathrm{Fe}}_{7}{\mathrm{Cr}}_{2}\mathrm{Ni}$ alloy We have developed a machine learned interatomic potential for the prototypical austenitic steel ${\mathrm{Fe}}_{7}{\mathrm{Cr}}_{2}\mathrm{Ni}$, using the Gaussian approximation potential (GAP) framew...

More recently, I have been using #MachineLearning tools to develop #InteratomicPotentials:

doi.org/10.1103/Phys...

This work developed an MLIP for the prototypical austenitic #StainlessSteel, Fe-Cr-Ni. Potentials such as this will help to accelerate future simulations 🚀

Join us today at #NeurIPS2024 for our poster presentation:

Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing

🗓️ When: Wed, Dec 11, 11 a.m. – 2 p.m. PST
📍 Where: East Exhibit Hall A-C, Poster #4107

#MachineLearning #InteratomicPotentials #Equivariance #GraphNeuralNetworks