Microscopic origins of conductivity in molten salts unraveled by computer simulations

Abstract

Molten salts are crucial materials in energy applications, such as batteries, thermal energy storage systems or concentrated solar power plants. Still, the determination and interpretation of basic physico-chemical properties like ionic conductivity, mobilities and transference numbers cause debate. Here, we explore a method for determination of ionic electrical mobilities based on non-equilibrium computer simulations. Partial conductivities are then determined as a function of system composition and temperature from simulations of molten LiFαClβIγ (with α + β + γ = 1). High conductivity does not necessarily coincide with high Li+ mobility for molten LiFαClβIγ systems at a given temperature. In salt mixtures, the lighter anions on average drift along with Li+ towards the negative electrode when applying an electric field and only the heavier anions move towards the positive electrode. In conclusion, the microscopic origin of conductivity in molten salts is unraveled here based on accurate ionic electrical mobilities and an analysis of the local structure and kinetics of the materials.

Data‐Driven Analysis of High‐Throughput Experiments on Liquid Battery Electrolyte Formulations: Unraveling the Impact of Composition on Conductivity**

“…The remaining minor systematic deviations of the activation energies of the conductivity to the viscosity and diffusivity in Figure 4C indicate that the lowering of the conductivity as compared to the Nernst–Einstein prediction via pair formation is somewhat less pronounced for lower temperatures. The latter has been also reported for other systems [52] …”

Applying Classical, Ab Initio, and Machine-Learning Molecular Dynamics Simulations to the Liquid Electrolyte for Rechargeable Batteries

“…The lower ionic conductivity in the Li 2 S 4 electrolyte despite the higher diffusion coefficient of Li + compared to Li 2 S 6 and Li 2 S 8 electrolytes could also be explained since the formation of large clusters in the Li 2 S 4 solution leads to less effective charge carriers (Figure b). Therefore, the role of the carrier concentration apart from the diffusion coefficient is supposed to be paid attention to when studying ionic transport properties . The Nernst–Einstein equation, which gives the ideal ionic conductivity at the limit of low concentrations, is further corrected and extended to take the strong ion–ion association in electrolytes with high salt concentrations into consideration. ,,, CIPs, AGGs, and larger clusters are likely to be electrically neutral or even negative.…”

“…Therefore, the role of the carrier concentration apart from the diffusion coefficient is supposed to be paid attention to when studying ionic transport properties. 420 The Nernst−Einstein equation, which gives the ideal ionic conductivity at the limit of low concentrations, is further corrected and extended to take the strong ion−ion association in electrolytes with high salt concentrations into consideration. 301,412,421,422 CIPs, AGGs, and larger clusters are likely to be electrically neutral or even negative.…”

Structural and Transport Properties of Novel High-Transference Number Electrolytes Based on Perfluoropolyether-block-Poly(ethylene oxide) for Application in Lithium-Ion Batteries: A Molecular Dynamics Simulation Study

“…The Nernst–Einstein ionic conductivity, σ NE , is defined as the ratio of σ to σ NE . The parameter α is widely used to evaluate the effect of correlative ion motion on the ionic conductivity of an electrolyte. ,− This parameter is also considered a degree of dissociation of the salt into ions, , and mathematically, α is defined as α = lim t → ∞ nobreak0em.25em⁡ σ σ NE …”