“…One direction that can offer a solution to this problem is the use of an “inverse” modeling approach, such as Reverse Monte Carlo (RMC), − regularization method, − and one enabled by the application of supervised machine learning methods. , Recently, a method of extracting the pair distribution function ( g ρ ( r )) around an X-ray absorbing atom from an EXAFS spectrum was developed. , However, the theoretical training set for the artificial neural network (NN) that maps EXAFS on g ρ ( r ) was constructed using MD-EXAFS; hence, the resultant g ρ ( r ) function extracted using the neural network approach was model-dependent. A recently developed follow-up method, utilizing an “objective” training approach, was shown to provide reliable results for Ni complexes in molten salt mixtures, and thus is a good starting point for extending this method to the molten actinide salt research.…”