Fig. 2: Performance evaluation of SuperSalt using the training and test datasets.
From: SuperSalt: equivariant neural network force fields for multicomponent molten salts system
Parity plots for energy and force, comparing density functional theory (DFT) reference data with SuperSalt potential predictions, are shown for a the training dataset, b the validation dataset, c Test_1 containing the 3300-ternary dataset, and d Test_2 containing the 800-multicomponent dataset. The corresponding force root mean square error (RMSE) per element for each dataset is presented as histograms in the third column. The testing errors in atomic forces for the four databases in the right panels largely follow a Gaussian distribution and are concentrated in the range of −25 to 25 meV/Å.
