Electrolytes are an important component of electrochemical energy storage systems and their optimization is critical for emerging beyond lithium ion technologies. Here, an integrated computational-experimental approach is used to rank-order and aid the selection of suitable electrolytes for a Na-ion battery. We present an in silico strategy based on both thermodynamic and kinetic descriptors derived from molecular dynamics simulations to rationally arrive at optimal electrolytes for Na-ion batteries. We benchmarked various electrolytes (pure and binary mixtures of cyclic and acyclic carbonates with NaClO4 salt) to identify appropriate formulations with the overarching goal of simultaneously enhancing cell performance while meeting safety norms. Fundamental insights from computationally derived thermodynamic and kinetic data considerations coupled with atomistic-level description of the solvation dynamics is used to rank order the various electrolytes. Thermodynamic considerations based on free energy evaluation indicate EC:PC as a top electrolyte formulation under equilibrium conditions. However, kinetic descriptors which are important factors dictating the rate capability and power performance suggest EC:DMC and EC:EMC to be among the best formulations. Experimental verification of these optimized formulations was carried out by examining the electrochemical performance of various electrolytes in Na/TiO2nanotubes half cells with NaClO4 salt. Our rate capability studies confirm that EC:DMC and EC:EMC to be the best formulations. These optimized formulations have low-rate specific capacities 120–140 mAh/g whereas the lower ranked electrolytes (EC: DEC) have capacities 95 mAh/g. The various electrolytes are also evaluated from a safety perspective. Such results suggest encouraging prospects for this approach in the a priori prediction of optimal sodium ion systems with possible screening implications for novel battery formulations
The selection of an appropriate electrolyte is an important consideration in the design of next-generation batteries. Low-cost sodium ion based batteries have assumed the role of attractive alternatives to Lithium ion batteries for dispensing and storage of energy. Here, we perform in silico based molecular dynamics simulation (MD) study on a variety of electrolytes and NaClO4 salt. We perform potential of mean force (PMF) calculations to extract the free energy of solvation for these different electrolyte-salt combinations in bulk and rank them based on the free energy predictions. The energetics of ion solvation will be used to understand the surface preference of the intercalating ion for a given electrolyte. The PMF calculations will provide insights into the solubility of the salt in the various electrolytes and will serve as a metric for choosing the most suitable electrolyte-salt combination for a given electrode. In designing new electrolytes, it is generally preferred to have high solubility of the salt. We will also determine the heats of vaporization of the various organic electrolytes and this information will be used to identify the operational range and safety aspects of the electrolyte. Electrolytes with low heat of vaporization can be considered unsafe. Additionally, the MD simulation trajectories will also be used to calculate the diffusivity of the ions in the various electrolytes. Additional transport metrics such as activation barriers to diffusion, ionic conductivity are used to refine the rank order of the electrolytes, in addition to the thermodynamics and equilibrium considerations. Determination of micro-structure suggests varying degree of coordination of sodium ion with these electrolytes commensurate with the ion solvation energetics. Suitable comparisons of computational predictions are made with experimental resutls. Collectively, this would form an apriori, in silico study informing experiments and would be a useful tool and metric for screening variety of solvent and electrode candidates in terms of their ability to be used for battery applications.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.