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Solid-state batteries (SSBs) will potentially offer increased energy density and, more importantly, improved safety for next generation lithium-ion (Li-ion) batteries. One enabling technology is solid-state composite cathodes with high operating voltage and area capacity. Current composite cathode manufacturing technologies, however, suffer from large interfacial resistance and low active mass loading that with excessive amounts of polymer electrolytes and conductive additives. Here, we report a liquid-phase sintering technology that offers mixed ionic-electronic interphases and free-standing electrode architecture design, which eventually contribute to high area capacity. A small amount (~ 4 wt.%) of lithium hydroxide (LiOH) and boric acid (H3BO3) with low melting point are utilized as sintering additives that infiltrate into single-crystal Ni-rich LiNi0.8Mn0.1Co0.1 (NMC811) particles at a moderately elevated temperature (~ 350 °C) in a liquid state, which not only enable intimate physical contact but also promote the densification process. In addition, the liquid-phase additives react and transform to ionic-conductive lithium boron oxide, together with the indium tin oxide (ITO) nanoparticle coating, mixed ionic-electronic interphases of composite cathode are successfully fabricated. Furthermore, the liquid-phase sintering performed at high-temperature (~ 800 °C) also enables the fabrication of highly dense and thick composite cathodes with a novel free-standing architecture. The promising performance characteristics of such composite cathodes, for example, delivering an area capacity above 8 mAh·cm−2 within a wide voltage window up to 4.4 V, open new opportunities for SSBs with a high energy density of 500 Wh·kg−1 for safer portable electronic and electrical transport.

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Publication history
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Acknowledgements

Publication history

Received: 23 December 2021
Revised: 24 January 2022
Accepted: 15 February 2022
Published: 24 March 2022
Issue date: July 2022

Copyright

© Tsinghua University Press 2022

Acknowledgements

Acknowledgements

This research was supported by Natural Science Foundation of Jiangsu Province (No. BK20200800), the National Natural Science Foundation of China (Nos. 51902165, 12004145, 52072323, and 52122211), Natural Science Foundation of Jiangxi Province (Nos. 20192ACBL2004 and 20212BAB214032), and Nanjing Science & Technology Innovation Project for Personnel Studying Abroad. Part of the calculations were supported by the Center for Computational Science and Engineering at Southern University of Science and Technology, and high-performance computing platform of Jinggangshan University.

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