Nikhil V S Avula
(Jawaharlal Nehru Centre for Advanced Scientific Research, India)

Modeling aqueous electrolytes has been challenging, despite the tremendous progress in the field. One phenomenon that is particularly difficult to capture is the “anomalous diffusion” of water in salt solutions. The diffusivity of water in aqueous cesium iodide solutions is larger than that in neat liquid water and vice versa for sodium chloride solutions. Such peculiar ion-specific behavior, called anomalous diffusion, is not reproduced in typical force field based molecular dynamics (MD) simulations due to inadequate treatment of ion-water interactions. In this talk, I shall demonstrate that machine learned atomic potentials (MLPs) trained on quantum density functional theory (DFT) data can reproduce the experimentally determined thermodynamic, structural, dynamical, and transport properties, including their varied trends in water diffusivities across salt concentration. Further, MLPs reveal that - while both ions in CsI solutions contribute to the faster diffusion of water molecules, the competition between the heavy retardation by Na ions and the slight acceleration by Cl ions in NaCl solutions reduces their water diffusivity. In the end, I shall briefly discuss our recent attempts to develop a universal MLP that can model all alkali-halide aqueous solutions at DFT accuracy.
 

Zoom registration link :
https://zoom.us/meeting/register/tJcqduyopjkrE9He-usl-16oLlY5Iz1Vl7W0