Comparative Study of Alkali-Cation-Based (Li+, Na+, K+) Electrolytes in Acetonitrile and Alkylcarbonates

The development of a suitable functional electrolyte is urgently required for fast-charging and high-voltage alkali-ion (Li, Na, K) batteries as well as next-generation hybrids supercapacitors. Many recent works focused on an optimal selection of electrolytes for alkali-ion based systems and their electrochemical performance but the understanding of the fundamental aspect that explains their different behaviour is rare. Herein, we report a comparative study of transport properties for LiPF₆, NaPF₆, KPF₆ in acetonitrile (AN) and a binary mixture of ethylene carbonate (EC), dimethyl carbonate (DMC): (EC/DMC : 1/1, weigh) through conductivities, densities and viscosities measurements in wide temperature domain. By application of the Stokes-Einstein, Nernst-Einstein, and Jones Dole equations, the effective ionic solvated radius of cation (r_eff), the ionic dissociation coefficient (α_D) and structuring Jones Dole's parameters (A, B) for salt are calculated and discussed according to solvent or cation nature as a function of temperature. From the results, we demonstrate that better mobility of potassium can be explained by the nature of the ion-ion and ion-solvent interactions due to its polarizability. In the same time, the predominance of triple ions in the case of K⁺, is a disadvantage at high concentration.     

A Discussion of Probability Functions and Constraints from a Variational Perspective

Set-Valued and Variational Analysis - Probability constraints are a popular modelling mechanism in applications. They help to model feasible decisions when the latter are taken prior to observing...     

Hydrodynamic Limit of the Symmetric Exclusion Process on a Compact Riemannian Manifold

Journal of Statistical Physics - We consider the symmetric exclusion process on suitable random grids that approximate a compact Riemannian manifold. We prove that a class of random walks on these...     

Spectral estimates for saddle point matrices arising in weak constraint four‐dimensional variational data assimilation

We consider the large sparse symmetric linear systems of equations that arise in the solution of weak constraint four‐dimensional variational data assimilation, a method of high interest for numerical weather prediction. These systems can be written as saddle point systems with a 3 × 3 block structure but block eliminations can be performed to reduce them to saddle point systems with a 2 × 2 block structure, or further to symmetric positive definite systems. In this article, we analyse how sensitive the spectra of these matrices are to the number of observations of the underlying dynamical system. We also obtain bounds on the eigenvalues of the matrices. Numerical experiments are used to confirm the theoretical analysis and bounds.