The promolecule density is a three-dimensional (3D) quantity and thus cannot be utilized in a traditional CNN. The CNNs are typically used for two dimensional (2D) images; in that regard, for an application, we have first to convert the three dimensional promolecule density to a 2D quantity. We can achieve this by projecting the 3D density to 2D planes, namely the xy, yz and zx planes. Via this 2D projection we obtain three projected datapoints from a single 3D datapoint. This 2D projection thus leads to a data augmentation (artificial increase of the dataset size) and minimizes loss of information. The dataset required for our model is mainly sourced from the current literature (including reviews on nanoclusters) 27a and we further carry out calculations to ascertain as to whether the reported structures are truly global minimum.