Rajni Chahal Postdoctoral Research Associate Contact CHAHALR@ORNL.GOV All Publications Transferable Deep Learning Potential Reveals Intermediate-Range Ordering Effects in LiF–NaF–ZrF4 Molten Salt Inverse mapping of properties to composition through generative modeling for designing molten salts Designing Physicochemically-Ordered Interphases for High-Performance Composites Liquid–Vapor Phase Equilibrium in Molten Aluminum Chloride (AlCl3) Enabled by Machine Learning Interatomic Potentials... Ab initio simulated Van Hove correlation function for time-resolved local dynamics in molten MgCl2... Deep-Learning Interatomic Potential Connects Molecular Structural Ordering to the Macroscale Properties of Polyacrylonitrile... Chemistry Informed Machine Learning-Based Heat Capacity Prediction of Solid Mixed Oxides Tracing mechanistic pathways and reaction kinetics toward equilibrium in reactive molten salts High-Throughput Prediction of Molten Salt Mixture Density with Supervised Machine Learning Multiobjective Hyperparameter Optimization for Deep Learning Interatomic Potential Training Using NSGA-II Key Links Curriculum Vitae Organizations Physical Sciences Directorate Chemical Sciences Division Separations and Polymer Chemistry Section Chemical Separations Group
