Work

Joint Partial Least Squares Modeling of Experimental and Computational Data for Electrolyte Prescreening in Lithium–Sulfur Batteries

Year: 2025

Type: article

Abstract: Lithium–sulfur batteries have attracted great research interest due to the high theoretical capacity of sulfur of 1672 mAh g−1. However, they have various problems due to the shuttle current caused by molecular sulfur dissolving in the electrolyte. Hence, electrolyte design is a key focus when optimizing the batteries. This study investigates the relationship between cycling data and electrochemical properties measured with cyclovoltammetric measurements, shuttle current measurements, and impedance spectroscopy. Using the acquired data, a partial least squares model to screen solvent candidates in reference to these findings is introduced. This model is based on cycling data as well as density functional theory‐calculated Conductor‐like Screening Model for Real Solvents data of the solvents and (solvated) lithium–polysulfides. The usefulness of the converged method is demonstrated by using it to identify new possible electrolyte systems. A subset of ten selected electrolyte systems is evaluated experimentally and their performance is reported. One of those electrolytes, 1.4 M LiTFSI, in pimelonitrile solution and without any further additives, displays exceptional cycling stability already on the first attempt, reaching a state of health of 50% after 115 cycles and maintaining a Coulombic efficiency of close to 100% during the entire cycling procedure.

Source: ChemElectroChem

DOI: 10.1002/celc.202500256

Authors: Fritz Wortelkamp, Christian Wittekind, Lilli Busch, Simon Weidner, Ingo Krossing

Institutions: University of Freiburg, Swiss Distance University of Applied Sciences

Language: English

Topic: Advanced Battery Materials and Technologies

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: gold

Estimated APC paid: $2,750