Baocheng Wang, Depeng Kong, Zhiao He, Jikai Liang, Yuyao Lu, Zikang Deng, Honghe Li, Mengke Wang, M. Jamal Deen, Zhiqiu Ye, Shuyao Zhou, Huayong Yang, Honghao Lyu, Jun Chen, Kaichen Xu, Geng Yang
Sehyeok Park, Myeongcho Jang, Hun‐Gi Jung, Kyung Yoon Chung, Seungho Yu
ABSTRACT All‐solid‐state lithium‐ion batteries are promising next‐generation energy‐storage systems, but interfacial instability between cathodes and solid electrolytes remains a major barrier to long‐term durability. Interfacial coatings can mitigate these reactions, yet coating…
Xiaolu Wei, Yong Li, Chenchong Wang, Lingyu Wang, Xiang Song, Keming Mao, et al.
ABSTRACT For sustainable alloy design, unified‐composition approaches offer an effective route to deliver multiple performance levels while reducing chemistry complexity. Quenching and partitioning (Q&P) steels are widely used advanced high‐strength steels, yet their grade de…
Dezhi Chen, Chao Xu, Jingyue Yu, Qi Wang, Hongze Fang, Shuo Yin, et al.
ABSTRACT A continuing challenge in aerospace materials is the search for alloys that have desired functional properties to operate at higher temperatures with lower densities. This improves aero‐engine efficiency and reduces CO 2 and other harmful emissions, aligning with aviatio…
Xinglin Zhou, Lei Huang, Yan Zhou, Xiaohui Ning
ABSTRACT Calcium‐based liquid metal batteries are promising for large‐scale energy storage due to calcium abundance and low cost, yet their practical applications are impeded by high operating temperatures, severe self‐discharge, limited coulombic efficiency, and rapid capacity f…
Aparna Chitra Sudheer, Gopinathan M. Anilkumar, Hidenori Kuroki, Yuuki Sugawara, Takeo Yamaguchi
ABSTRACT Engineering the surface structure of catalysts is critical for achieving high intrinsic activity in the oxygen reduction reaction (ORR). We report a machine‐learning (ML)‐guided materials design strategy for the synthesis of support‐free, connected nanoparticle catalysts…
Hao Meng, Jingzi Zhang, Xu Zhu, Yuelin Wang, Antai Yang, Kailong Hu, et al.
ABSTRACT Breaking through the power conversion efficiency (PCE) limits of printable mesoscopic perovskite solar cells (p‐MPSCs) with machine learning (ML) shows great potential, but has not yet been accomplished. This work establishes a reliable workflow by constructing a high‐qu…