Investigating the governing physico-chemical interactions in vanadium redox flow batteries using multiscale molecular modelling
Date of Issue2017-12-27
Interdisciplinary Graduate School (IGS)
Vanadium Redox Flow Batteries (VRFB) can be integrated with renewable energy technologies like solar or wind energy to overcome the energy storage problems. The stored energy can then be used, as and when required. The energy storage capacity of VRFB depends on the volume of the electrolyte and the solubility of vanadium ions in the electrolyte; whereas its power depends on the electrode surface area and cell stack. Thus, the main advantage of using a redox flow battery over any other rechargeable battery system is that the energy storage capacity can be increased to any extent by increasing the size of the electrolyte storage tanks. To commercialize VRFB, efforts are being made to reduce the size of the electrolyte storage tanks by increasing the solubility of vanadium ions in these electrolytes and also by improving the thermal stability of the electrolyte. The most common approach taken to enhance the solubility and stability is to modify the electrolyte using additives. However, fundamental insights into the physico-chemical interactions between vanadium ions and the electrolyte system that govern the solubility and stability of the ions are lacking and hence systematic screening and selection of additives is not feasible. The aim of this thesis is to fill this knowledge gap by investigating the local solvation structure and governing interactions of vanadium ions in the conventional electrolyte and modifications in them in the presence of additives. To achieve this, molecular modelling is used as a tool. Physical interactions are modelled using classical force field based molecular dynamics (MD) and chemical reactions are studied using density functional theory (DFT). Force field based MD simulations are coupled with metadynamics to simulate the rare events and reconstruct the free energy surface. Vanadium being a transition metal with multiple oxidation states, force field for vanadium was not available. Hence, force field parameters for vanadium ions are fitted by benchmarking ab initio MD computed radial distribution functions (RDF) and solvation structures obtained by Extended X-ray absorption fine structure (EXAFS). Simulations are then performed to investigate the role of organic and inorganic additives in stabilizing the vanadium ions. The main findings from this work are: a) New force-field parameters for vanadium ions are proposed, which can be used to perform large scale classical MD simulations of systems containing vanadium ions. b) It is kinetically feasible for the additive counterions chloride and dihydrogen phosphate to enter the first solvation shell of vanadium ions and these are also thermodynamically stable in the first solvation shell. Thus, the additive counterions are capable of changing the solvation structure of vanadium ions and they can also form an ion-pair complex, resulting in modification in vanadium ion solubility. On the other hand, bisulphate and sulphate ions, present in the conventional electrolyte are not as stable in vanadium’s first solvation shell and hence cannot modify vanadium’s water solvation, leading to its precipitation as V2O5 at high temperatures. c) This is the first time it is revealed how cations in the additives are equally important and how they play a role in altering the stability of vanadium ions. d) DFT calculations performed to get mechanistic insights and feasibility of oxidation of glucose (as an additive) by VO2+ ions reveal that it is not feasible kinetically for glucose to form gluconic acid in the presence of VO2+ ions and it would form arabinose and formic acid. As VO2+ ions can oxidize glucose, the improved stability of the VRFB electrolyte is a result of change in SOC of the positive electrolyte. In summary, this thesis elucidates the governing principle behind the stabilization of vanadium ions by organic and inorganic additives. Also, a computationally inexpensive modeling tool is developed to select and screen potential additives.