Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/137020
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Type: Journal article
Title: Unraveling the Catalyst-Solvent Interactions in Lean-Electrolyte Sulfur Reduction Electrocatalysis for Li-S Batteries
Author: Li, H.
Rongwei, M.
Guo, Y.
Ye, C.
Kong, D.
Johannessen, B.
Jaroniec, M.
Qiao, S.
Citation: Angewandte Chemie International Edition, 2022; 61(51):1-9
Publisher: Wiley
Issue Date: 2022
ISSN: 1433-7851
1521-3773
Statement of
Responsibility: 
Huan Li, Rongwei Meng, Yong Guo, Chao Ye, Debin Kong, Bernt Johannessen, Mietek Jaroniec, and Shi-Zhang Qiao
Abstract: Efficient catalyst design is important for leanelectrolyte sulfur reduction in Li-S batteries. However, most of the reported catalysts were focused on catalystpolysulfide interactions, and generally exhibit high activity only with a large excess of electrolyte. Herein, we proposed a general rule to boost lean-electrolyte sulfur reduction by controlling the catalyst-solvent interactions. As evidenced by synchrotron-based analysis, in situ spectroscopy and theoretical computations, strong catalyst-solvent interaction greatly enhances the lean-electrolyte catalytic activity and battery stability. Benefitting from the strong interaction between solvent and cobalt catalyst, the Li-S battery achieves stable cycling with only 0.22% capacity decay per cycle with a low electrolyte/sulfur mass ratio of 4.2. The lean-electrolyte battery delivers 79% capacity retention compared with the battery with flooded electrolyte, which is the highest among the reported lean-electrolyte Li-S batteries.
Keywords: Catalyst-solvent interactions
electrocatalysis
Lean electrolyte condition
Li−S batteries
sulfur reduction reaction
Description: Published 19 December 2022
Rights: © 2022 The Authors. Angewandte Chemie International Edition published by Wiley-VCH GmbH This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
DOI: 10.1002/anie.202213863
Grant ID: http://purl.org/au-research/grants/arc/FL170100154
http://purl.org/au-research/grants/arc/DP220102596
Published version: http://dx.doi.org/10.1002/anie.202213863
Appears in Collections:Chemical Engineering publications

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