A fine-tuned MACE-based machine learning potential trained via active learning on near-ground-state DFT data enables direct large-scale MD prediction of lithium self-diffusion coefficients in NMC811.
P.; Simm, G.; Ortner, C.; Csanyi, G
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Direct Simulation of LiNi0.8Mn0.1Co0.1O2 Transport Properties Using an Efficient and Accurate Machine Learning Potential
A fine-tuned MACE-based machine learning potential trained via active learning on near-ground-state DFT data enables direct large-scale MD prediction of lithium self-diffusion coefficients in NMC811.