FIG. 1: AL4GAP Workflow for active leaning over a combinatorial composition map of molten salt mixtures. The compositions space is explored and sampled concurrently by providing dedicated compute resource for each composition. method generates the necessary forcefield files needed for performing the LAMMPS simulation. The 'ffparam' can take two possible arguments namely 'TF' (i.e., rigid ion model) or 'OPLS' (Optimized Potentials for Liquid Simulations ) keywords. Our prior publications for molten LiCl and LiCl-KCl used the rigid ion based sampling which invoked the 'TF' keyword to perform RIM based sampling and the corresponding parametrization available in our GitHub only supports monovalent mixing of up to two salts . The RIM model generator classes used in prior studies are found in the GitHub repository as 'moltensalt_tosifumi_gen.py' and 'tosi_fumi_params.py'. The 'OPLS' class was added to expand the number of chemical species in the composition space to support multiply charged cationic salt mixtures and is the new default argument. The 'setup_input' will internally invoke a Python class named 'moltensalt_gen' that contains all the coordinate generation and force field parameters for OPLS. A target "number of atom parameter ('set_target_number_of_atoms'), which is fixed at 64 atoms with a shortest distance cutoff of 2 Å('min_dist'), is used to arrive at the most plausible charge neutral atoms packing. The AL4GAP workflow through the OPLS sampler currently support 9 cations (Li, Na, K, Rb, Cs, Mg, Ca, Sr, and Ba), 4 anions (F, Cl, Br and I) and two heavy species (Nd and Th).