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

Figure 2

The reference DFT gap vs. the BN fraction . Depending on the position and shape of the BN rectangular domain, different gap values are obtained at the same . A fit with a second degree polynomial function shows the statistical increase of with (). The inset shows a histogram of the DFT gap values, focusing on the small energy gaps.