Abstract
The sulfur reduction reaction (SRR) plays a central role in high-capacity lithium sulfur (Li-S) batteries. The SRR involves an intricate, 16-electron conversion process featuring multiple lithium polysulfide intermediates and reaction branches1,2,3. Establishing the complex reaction network is essential for rational tailoring of the SRR for improved Li-S batteries, but represents a daunting challenge4,5,6. Herein we systematically investigate the electrocatalytic SRR to decipher its network using the nitrogen, sulfur, dual-doped holey graphene framework as a model electrode to understand the role of electrocatalysts in acceleration of conversion kinetics. Combining cyclic voltammetry, in situ Raman spectroscopy and density functional theory calculations, we identify and directly profile the key intermediates (S8, Li2S8, Li2S6, Li2S4 and Li2S) at varying potentials and elucidate their conversion pathways. Li2S4 and Li2S6 were predominantly observed, in which Li2S4 represents the key electrochemical intermediate dictating the overall SRR kinetics. Li2S6, generated (consumed) through a comproportionation (disproportionation) reaction, does not directly participate in electrochemical reactions but significantly contributes to the polysulfide shuttling process. We found that the nitrogen, sulfur dual-doped holey graphene framework catalyst could help accelerate polysulfide conversion kinetics, leading to faster depletion of soluble lithium polysulfides at higher potential and hence mitigating the polysulfide shuttling effect and boosting output potential. These results highlight the electrocatalytic approach as a promising strategy for tackling the fundamental challenges regarding Li-S batteries.
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Data availability
The data that support the findings of this study are available in the main text, figures and Supplementary Information files. Source data are provided with this paper. All relevant data are available from the corresponding authors on request.
Code availability
The code used for simulated voltage-dependent concentrations and CV curves is available at https://github.com/lophocinalis/concentration_cv.
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Acknowledgements
This work is supported by the Center for Synthetic Control Across Length-scales for Advancing Rechargeables, an Energy Frontier Research Center funded by the US Department of Energy, Office of Science Basic Energy Sciences programme under award no. DE-SC0019381.
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X.D. conceived the research. X.D. and R.L. designed the experimental research. P.S. and Z. Wei designed and performed density functional theory (DFT) calculations. R.L. performed experiments and conducted data analysis, with contributions from Z. Wei, L.P., L.Z., P.W., C.W., D.Z., H.L., Z. Wang, S.T., B.D., Y.H., P.S. and X.D. A.Z. and R.S. contributed to Raman data collection. R.L. and Z. Wei wrote the original draft. X.D. and P.S. revised the manuscript. All authors discussed the results and commented on the manuscript.
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Liu, R., Wei, Z., Peng, L. et al. Establishing reaction networks in the 16-electron sulfur reduction reaction. Nature 626, 98–104 (2024). https://doi.org/10.1038/s41586-023-06918-4
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DOI: https://doi.org/10.1038/s41586-023-06918-4
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