Project summary:

The research project aims to develop a comprehensive computational model to study the dynamic behavior of solvated ions in supercapacitors during charge and discharge processes. The key innovation lies in the integration of a hybrid Monte Carlo (MC) and Molecular Dynamics (MD) approach (Rud et al., 2022), allowing for efficient and accurate simulations of the solvation shell around ions and corresponding hydrodynamics. The project focuses on addressing the limitations of full atomistic simulations by employing MC to selectively account for the relevant solvation shell made of water molecules around ions. Instead of accounting for all the water dipole particles, the model will consider only the ones that affect the electrostatic energy due to dipole—ion interactions. The computational method will combine the MC part, at which the water dipoles are inserted (or deleted) providing a relevant configuration of an ion solvation shell, and the MD part which will account for the mechanical movement of the system particles, including the frictional forces capturing the hydrodynamics of ions.The research will investigate the implications of this hybrid approach on ion transport, ion concentration profiles, and the overall electrochemical performance of supercapacitors in charging and discharging processes. Validation of the developed model will be conducted through comparison with experimental data and other theoretical predictions, and full atomistic simulations (Lee and Rasaiah, 1994) ensuring the accuracy and reliability of the simulation results. The project's outcomes are expected to shed light on the hydrodynamic properties of solvated ions in supercapacitors, offering valuable insights for optimizing device performance and guiding the design of advanced energy storage systems. This innovative research contributes to the broader field of computational chemistry and materials science, providing a powerful tool for studying complex electrochemical systems and facilitating the development of more efficient and sustainable energy storage technologies.

Profile of an ideal candidate: MSc or equivalent degree in Chemistry, Physics, or a related field (required), working communication skills in English, background in statistical mechanics, molecular simulations, computer programming, and Linux operating system.

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