We next compare the SC trained NN and compare its performance with energetics and forces computed with DFT. While the SC model is expected to deviate from the DFT energies for certain situations, it is important to quantify the extent of error of the SC trained NN against a DFT test set. To accomplish this, we further test these networks with the validation set of 2000 -3000 structures whose energies were calculated with DFT to probe into how well a network trained with only radial symmetric functions will perform with respect to DFT. We find that the NN fails catastrophically in both energy as well as force calculations (Fig. ) -the MAE for most elements are » 0.5 eV. The corresponding MAE in force predictions shown in Fig. (b) are also quite high for most elements (» 1 eV/Å). This provides hints to the inadequacies of an SC EAM type of potential (spherically symmetric), which accounts for only the radial symmetry operations, in describing the energetic as well as dynamics of systems. At the nanoscale, as surface effects begin to dominate, it becomes imperative to include contributions from angular i.e. 3-body interactions as well.