Coordination Chemistry Reviews, Год журнала: 2025, Номер 537, С. 216705 - 216705
Опубликована: Апрель 16, 2025
Язык: Английский
Coordination Chemistry Reviews, Год журнала: 2025, Номер 537, С. 216705 - 216705
Опубликована: Апрель 16, 2025
Язык: Английский
Nano-Micro Letters, Год журнала: 2024, Номер 16(1)
Опубликована: Июль 24, 2024
Distinct from "rocking-chair" lithium-ion batteries (LIBs), the unique anionic intercalation chemistry on cathode side of dual-ion (DIBs) endows them with intrinsic advantages low cost, high voltage, and eco-friendly, which is attracting widespread attention, expected to achieve next generation large-scale energy storage applications. Although electrochemical reactions anode DIBs are similar that LIBs, in fact, match rapid insertion kinetics anions consider compatibility electrolyte system also serves as an active material, materials play a very important role, there urgent demand for rational structural design performance optimization. A review summarization previous studies will facilitate exploration optimization future. Here, we summarize development process working mechanism exhaustively categorize latest research their applications different battery systems. Moreover, design, reaction briefly discussed. Finally, fundamental challenges, potential strategies perspectives put forward. It hoped this could shed some light researchers explore more superior advanced systems further promote DIBs.
Язык: Английский
Процитировано
20Energy storage materials, Год журнала: 2025, Номер unknown, С. 104052 - 104052
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
5Materials Genome Engineering Advances, Год журнала: 2024, Номер unknown
Опубликована: Сен. 7, 2024
Abstract Metal‐organic frameworks (MOFs), renowned for structural diversity and design flexibility, exhibit potential in catalysis. However, the pursuit of higher catalytic activity through defects often compromises stability, requiring a delicate balance. Traditional trial‐and‐error method optimizing synthesis parameters within complex chemical space is inefficient. Herein, taking typical MOF UiO‐66(Ce) as an illustrative example, closed loop workflow built, which integrates machine learning (ML)‐assissted prediction, multi‐objective optimization (MOO) experimental preparation to synergistically optimize defect content thermal stability efficient hydrogenation dicyclopentadiene (DCPD). An automatic data extraction program ensures accuracy, establishing high‐quality database. ML employed explore intricate synthesis‐structure‐property correlations, enabling precise delineation pure‐phase subspace accurate predictions properties. After two iterations, MOO model identifies optimal protocols high (>40%) (>300°C). The optimized exhibits superior performance DCPD, validating precision reliability our methodology. This ML‐assisted approach offers valuable paradigm solving trade‐off riddle materials field.
Язык: Английский
Процитировано
7Energy storage materials, Год журнала: 2024, Номер 69, С. 103427 - 103427
Опубликована: Апрель 30, 2024
Язык: Английский
Процитировано
3Coordination Chemistry Reviews, Год журнала: 2025, Номер 537, С. 216705 - 216705
Опубликована: Апрель 16, 2025
Язык: Английский
Процитировано
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