Gap Prediction in Hybrid Graphene-Hexagonal Boron Nitride Nanoflakes Using Artificial Neural Networks

Figure 3

Predicted ANN gap vs. reference DFT gap, for typical fully connected networks with three layers: (a) Method 1 (166/100/1 neurons) and (b) Method 2 (20/100/1 neurons). The results corresponding to the training and test sets are represented in blue and red colors, respectively. The coefficient of determination is calculated for both training and test examples. The inset contains log-log plots showing a detailed view over the small gap energy range.

(a)

(b)