2026 roadmap on next-generation solid electrolytes for battery applications

作者：F. Strauss, Torsten Brezesinski, Saneyuki Ohno, Yi Huang, Peng Song, Xabier Martínez de Irujo-Labalde, Wolfgang G. Zeier, Jelena Popovic-Neuber, Hugo Braun, A. Remhof, Corsin Battaglia, T. Famprikis, M. Wagemaker, Ke Huang, Yan Zeng, O. Bin, Juhyoun Park, Y. Jung, Jingui Yang, Siyuan Guo, Shu-Bo Wang, Shuo Wang, E. McCalla, Benjamin Mercier, O. Korjus, P. Perrenot, C. Villevieille, Martin Wilkening, K. Wissel, Oliver Clemens · 发表于：Materials Futures · 年份：2026 · DOI：10.1088/2752-5724/ae5120 · 被引用次数：6 · 研究领域：Physics

The global transition to sustainable energy systems requires breakthroughs in electrochemical storage technologies that are not only safe but also resource efficient. Solid-state batteries (SSBs), which use superionic solid electrolytes (SEs) instead of flammable liquid electrolytes, are at the forefront of this transformation. In general, SEs promise increased safety, access to high-voltage cathode and metal anode chemistries, and new avenues for circular design and recyclability. However, to reach their full potential, intertwined challenges related to ion transport, (electro)chemical stability, manufacturing, processing, and cost must be overcome. This 2026 roadmap on next-generation SEs for battery applications outlines new directions that will contribute to research in the field of SSBs over the next decade. It provides an overview of the current state of the art in sulfide- and halide-based SEs for Li and Na systems, examines post-Li/Na chemistries (K, Mg, and others), and highlights advances in hydroborate, fully reduced (irreducible), and compositionally complex (high-entropy) electrolytes, as well as glass-ceramic electrolytes. Beyond material innovation, the paper emphasizes the critical role of redox activity in SEs, scalable processing, high-throughput synthesis, and machine learning, as well as operando analytics and nuclear magnetic resonance spectroscopy to accelerate discoveries and gain a better understanding of structure–property relationships. Finally, the ...