Table : Summary of the force fields collected from literature to predict nanocluster energies and forces. The references for each force field is mentioned in the square brackets. [13] Element Functional Form Ag eam/fs [14], eam/alloy [15], sutton chen [16] Al eam/fs [17], meam [18], sutton chen [16], adp [19] Au eam/fs [14], eam/alloy [4], adp [20], sutton chen [ The ANN Forcefield models are validated against a set of 30000 structures for each element created using nested sampling, with energies calculated using SC-EAM. Both Force as well as energy calculations are conducted and the correlation plots for the optimised final NN from activelearning are shown in this section. The training sets for these networks are used in the next phase to retrain the NN using DFT The NN trained using SC-EAM is validated against a validation structure set calculated using DFT to serve as a benchmark for the ANN retrained using DFT. The lack of angular components in the fingerprints used for these networks makes it difficult for them to accurately capture the energy and force data calculated using DFT. The Retrained ANN Forcefield models are validated against a set of 1600-2000 Structures whose energy and forces were calculated using VASP. The mean absolute errors for energies(in meV/atom) and forces (in meV/Å) are included in the legend of the plot. Each plot has four panels; top row containing energy and Force plots for the training, while the bottom row covering energy and Force plots for the test data.