数据驱动发展下一代镁离子固态电解质

doi:10.61558/2993-074X.3461

电化学（中英文） ›› 2024, Vol. 30 ›› Issue (7): 2415001. doi: 10.61558/2993-074X.3461

所属专题： “下一代二次电池”专题文章； “AI for Electrochemistry”专题文章

• 观点 • 上一篇

数据驱动发展下一代镁离子固态电解质

杨方令^a^,^b, 佐藤龙平^a, 程建锋^a, 木須一彰^c, 王倩^a^,^d, 贾雪^a, 折茂慎一^a^,^c, 李昊^a^,^*()

^a材料科学高等研究所（WPI-AIMR），东北大学，仙台，980-8577，日本
^b物理学院，四川大学，四川成都，610065，中国
^c金属材料研究所（IMR），东北大学，仙台，980-8577，日本
^d材料科学与工程学院，四川大学，四川成都，610064，中国

收稿日期:2024-02-16 修回日期:2024-04-24 接受日期:2024-04-24 发布日期:2024-04-26 出版日期:2024-07-28

Data-Driven Viewpoint for Developing Next-Generation Mg-Ion Solid-State Electrolytes

Fang-Ling Yang^a^,^b, Ryuhei Sato^a, Eric Jianfeng Cheng^a, Kazuaki Kisu^c, Qian Wang^a^,^d, Xue Jia^a, Shin-ichi Orimo^a^,^c, Hao Li^a^,^*()

^aAdvanced Institute for Materials Research (WPI-AIMR), Tohoku University, Sendai, 980-8577, Japan
^bCollege of Physics, Sichuan University, Chengdu, 610065, China
^cInstitute for Materials Research (IMR), Tohoku University, Sendai, 980-8577, Japan
^dCollege of Materials Science and Engineering, Sichuan University, Chengdu, 610064, China

Received:2024-02-16 Revised:2024-04-24 Accepted:2024-04-24 Online:2024-04-26 Published:2024-07-28
Contact: *Hao Li, E-mail address: li.hao.b8@tohoku.ac.jp.

摘要/Abstract

摘要：

镁（Mg）在地壳中的储量丰富且理论体积容量高，这使得其在储能领域备受关注，特别是在固态电池中，它极具发展潜力，可作为锂（Li）的替代品。然而，镁离子在固态电解质（SSE）中传导缓慢，这是阻碍镁离子固态电池发展的关键挑战之一。近年来，各种传导镁离子的SSE被广泛报道，但很难从单一的文献报告中得出关键的信息。此外，进一步阐明镁离子SSE的结构与性能关系是有必要的，这将为SSE提供更精确的设计指南。在这篇文章中，我们基于数据挖掘分析了过去四十年报道的具有高离子电导率的镁基SSE的结构特征，总结了三个优化镁离子固态电解质的策略。基于实验和理论计算技术的发展，讨论了现阶段开发镁固态电解质的机遇和挑战，论述了实验、理论计算和机器学习在开发新型高性能镁离子SSE过程中的协作过程。我们为优化和开发下一代镁离子固态电解质提供了大数据见解。

关键词: 数据挖掘, 镁离子固态电解质, 全固态电池, 镁离子传导

Abstract:

Magnesium (Mg) is a promising alternative to lithium (Li) as an anode material in solid-state batteries due to its abundance and high theoretical volumetric capacity. However, the sluggish Mg-ion conduction in the lattice of solid-state electrolytes (SSEs) is one of the key challenges that hamper the development of Mg-ion solid-state batteries. Though various Mg-ion SSEs have been reported in recent years, key insights are hard to be derived from a single literature report. Besides, the structure-performance relationships of Mg-ion SSEs need to be further unraveled to provide a more precise design guideline for SSEs. In this Viewpoint article, we analyze the structural characteristics of the Mg-based SSEs with high ionic conductivity reported in the last four decades based upon data mining - we provide big-data-derived insights into the challenges and opportunities in developing next-generation Mg-ion SSEs.

Key words: Data mining, Magnesium-ion solid-state electrolytes, All-solid-state batteries, Magnesium-ion conductivity

杨方令, 佐藤龙平, 程建锋, 木須一彰, 王倩, 贾雪, 折茂慎一, 李昊. 数据驱动发展下一代镁离子固态电解质[J]. 电化学（中英文）, 2024, 30(7): 2415001.

Fang-Ling Yang, Ryuhei Sato, Eric Jianfeng Cheng, Kazuaki Kisu, Qian Wang, Xue Jia, Shin-ichi Orimo, Hao Li. Data-Driven Viewpoint for Developing Next-Generation Mg-Ion Solid-State Electrolytes[J]. Journal of Electrochemistry, 2024, 30(7): 2415001.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://electrochem.xmu.edu.cn/CN/10.61558/2993-074X.3461

https://electrochem.xmu.edu.cn/CN/Y2024/V30/I7/2415001

数据驱动发展下一代镁离子固态电解质

Data-Driven Viewpoint for Developing Next-Generation Mg-Ion Solid-State Electrolytes

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 5

参考文献

相关文章 0

Metrics