Revisiting the unified principle for single-atom electrocatalysts in the sulfur reduction reaction: from liquid to solid-state electrolytes
By
Shen, JD (Shen, Jiadong) [1] , [2] ; Liang, ZW (Liang, Ziwei) [1] ; Gu, TT (Gu, Tengteng) [1] ; Sun, ZY (Sun, Zhaoyu) [1] ; Wu, YW (Wu, Yiwen) [1] ; Liu, XQ (Liu, Xiaoqin) [2] ; Liu, JH (Liu, Junhao) [1] ; Zhang, XY (Zhang, Xiuying) [3] ; Liu, JW (Liu, Jiangwen) [1] ; Shen, L (Shen, Lei) [2] ;
(provided by Clarivate)
Source
ENERGY & ENVIRONMENTAL SCIENCE
Volume17Issue16Page6034-6045
DOI10.1039/d4ee01885k
Published
AUG 13 2024
Early Access
JUL 2024
Indexed
2024-07-28
Document Type
Article
Abstract
The conversion of lithium-polysulfides (LPSs) through the sulfur reduction reaction (SRR) is a crucial process for improving the electrochemical performance of lithium-sulfur (Li-S) batteries. However, the microscopic mechanism of the SRR remains unclear, affecting catalyst design for Li-S batteries. By applying artificial intelligence (AI), we have developed a unified mechanistic model for the SRR on metal-nitrogen-doped carbon (TMNC, TM = 3d/4d/5d transition metals) catalysts. This model reveals the SRR catalytic activity's physical essence in TMNCs, rooted in wavefunction overlap between transition metals and non-metal atoms. This is supported by physical models and experiments. Using this insight, we have anchored FeNCs (and Fe3C for comparison) onto carbon fibers for the sulfur cathode/lithium anode, enhancing lithium metal's cyclic life to over 10 000 hours. The solid-state Li-S full cell demonstrates an energy density of similar to 400 W h kg-1 with consistent cyclic performance. Our AI-enhanced mechanistic understanding of the SRR guides the development of superior SRR catalysts and high-performance Li-S batteries.
A new descriptor (lambda) for lithium polysulfides (LPSs) conversion involving d-p coupling on catalyst surfaces. Our model, validated by DFT calculations and machine-learning algorithms, explains LPSs dynamics and improves Li-S battery performance.
Author Information
Corresponding Address
Liu, Jun
(corresponding author)
South China Univ Technol, Sch Mat Sci & Engn, Guangdong Prov Key Lab Adv Energy Storage Mat, Guangzhou 510641, Guangdong, Peoples R China
Affiliation
South China University of Technology
South China University of Technology School of Materials Science and Engineering
South China University of Technology Guangdong Provincial Key Laboratory of Advanced Energy Storage Materials
Corresponding Address
Shen, Lei
(corresponding author)
Natl Univ Singapore, Dept Mech Engn, Singapore 117575, Singapore
E-mail Addresses
shenlei@nus.edu.sg
Addresses
1 South China Univ Technol, Sch Mat Sci & Engn, Guangdong Prov Key Lab Adv Energy Storage Mat, Guangzhou 510641, Guangdong, Peoples R China
2 Natl Univ Singapore, Dept Mech Engn, Singapore 117575, Singapore
3 Natl Univ Singapore, Dept Phys, 2 Sci Dr 3, Singapore 117542, Singapore
E-mail Addresses
shenlei@nus.edu.sgmsjliu@scut.edu.cn
Categories/ Classification
Research AreasChemistryEnergy & FuelsEngineeringEnvironmental Sciences & Ecology
Citation Topics
2 Chemistry
2.62 Electrochemistry
2.62.616 Lithium-Sulfur Batteries
Sustainable Development Goals
11 Sustainable Cities and Communities
Web of Science Categories
Chemistry, MultidisciplinaryEnergy & FuelsEngineering, ChemicalEnvironmental Sciences