Combining Molecular Dynamics and Experimental Methods for the Parametrization of Binary Carbonate-Based Electrolytes

Modelling the ionic transport in battery cells requires precise parametrization of the involved electrolytes. For carbonate-based electrolytes, however, the evaluation of their parameters suffers from interphase effects between the bulk electrolyte and the Li metal electrode, commonly present in the usual electrochemical polarization experiments. In this work, we combine measurements on conductivity and concentration cells with molecular dynamic simulations, avoiding these difficulties and thus, allowing for a more accurate determination of the parameters. We determine the conductivity, the transference number, the thermodynamic factor and the salt diffusion coefficient for three different electrolytes, i.e mixtures of ethylene carbonate (EC), ethyl methyl carbonate (EMC), methyl propionate (MP), dimethyl carbonate (DMC) and propylene carbonate (PC), containing LiPF$_6$ at various concentrations and temperatures. In order to validate the simulated transference numbers, we employ electrophoretic Nuclear Magnetic Resonance spectroscopy (eNMR).

💡 Research Summary

This paper presents a comprehensive and innovative methodology for accurately parameterizing the transport properties of binary carbonate-based electrolytes, which are crucial for modeling and optimizing lithium-ion battery performance. The core challenge addressed is the difficulty in obtaining reliable bulk electrolyte parameters—ionic conductivity (κ), Li+ transference number (t+), thermodynamic factor (TDF), and salt diffusion coefficient (D±)—from traditional electrochemical experiments using lithium metal electrodes, due to interfering interphasial reactions at the electrode-electrolyte interface.

To circumvent this issue, the authors synergistically combine molecular dynamics (MD) simulations with key experimental techniques. The approach consists of three pillars: 1) Experimental measurement of conductivity via electrochemical impedance spectroscopy (EIS). 2) Experimental measurement of a convoluted function a(c,T) = (1 - t+)TDF using concentration cells with Li electrodes. 3) Calculation of the Onsager transport coefficients (Lij) and subsequently κ and t+ from MD simulations based on Green-Kubo relations. The MD simulations employ a non-polarizable OPLS force field, and the effective charges of the ions are scaled using a factor optimized by benchmarking the simulated conductivity against the experimental EIS data.

The MD-derived t+ value is then used to deconvolute the experimental a(c,T) data from the concentration cells, allowing for the separate determination of t+ and TDF. Finally, D± is calculated using these values. Crucially, the transference numbers predicted by the MD simulations are independently validated using electrophoretic NMR (eNMR) measurements, a technique immune to interfacial effects, confirming the reliability of the computational approach.

The study applies this hybrid framework to three relevant electrolyte systems containing LiPF6 salt: EC:EMC (3:7 by weight), EC:DMC:PC (27:63:10 by volume), and EC:EMC:MP (2:6:2 by volume). These were chosen as a well-studied benchmark (EC:EMC), an electrolyte used in a commercial 18650 cell (EC:DMC/PC), and a low-temperature candidate proven in space missions (EC:EMC/MP). The complete set of four transport parameters is determined as a function of concentration (0.1 M to 3.0 M) and temperature (-20°C to 20°C).

A significant theoretical aspect thoroughly discussed is the reference frame dependency of transport parameters. The paper details the transformation equations required to convert parameters between the center-of-mass (COM) frame typically used in MD and the volume-fixed (VOL) frame relevant to the eNMR and concentration cell experiments, ensuring consistent comparison and integration of data from all sources.

In summary, this work establishes a robust protocol that leverages the strengths of both computational and experimental methods to disentangle and accurately determine the fundamental transport parameters of complex electrolytes, free from the artifacts of electrode interphases. The resulting dataset and methodology provide a valuable foundation for advanced battery modeling and the rational design of next-generation electrolytes.