Fig. 7
From: Machine-learning the configurational energy of multicomponent crystalline solids
Formation energies predicted with a least squares regression and b neural network potential for lithium-vacancy orderings on the tetrahedral and octahedral sites of spinel TiS2. Local features around each site are generated from only pair correlations for the neural network, while the least squares model uses the average correlations for the same clusters. The figure shows DFT calculated formation energies as circles, while the predictions from the model are shown as green crosses. Configurations on the DFT convex hull are shown as orange circles and the configurations on the predicted convex hull are shown as orange crosses. The figure on top shows the full composition range, while the figure below spans a smaller composition range up to \(x = \frac{2}{3}\)
