  Here, we present an EfficientNet-B0-based model to directly predict multiple
properties of lithium manganese nickel oxides (LMNO) using their crystal
structure images. The model is supposed to predict the energy above the convex
hull, bandgap energy, crystal systems, and crystal space groups of LMNOs. In
the last layer of the model, a linear function is used to predict the bandgap
energy and energy above the convex hull, while a SoftMax function is used to
classify the crystal systems and crystal space groups. In the test set, the
percentages of coefficient of determination (R2) scores are 97.73% and 96.50%
for the bandgap energy and energy above the convex hull predictions,
respectively, while the percentages of accuracy are 99.45% and 99.27% for the
crystal system and crystal space group classifications, respectively. The class
saliency maps explain that the model pays more attention to the shape of the
crystal lattices and gradients around the lattice region occupied by the larger
ions. This work provides new insight into using an intelligent model to
directly relate the crystal structures of LMNO materials with their properties.
