Journal of Energy Storage, Год журнала: 2024, Номер 104, С. 114637 - 114637
Опубликована: Ноя. 19, 2024
Язык: Английский
Journal of Energy Storage, Год журнала: 2024, Номер 104, С. 114637 - 114637
Опубликована: Ноя. 19, 2024
Язык: Английский
Journal of Energy Storage, Год журнала: 2025, Номер 117, С. 116099 - 116099
Опубликована: Март 15, 2025
Язык: Английский
Процитировано
2Physical Chemistry Chemical Physics, Год журнала: 2025, Номер unknown
Опубликована: Янв. 1, 2025
Carbon nitride research has reached a promising point in today's endeavours with diverse applications including photocatalysis, energy storage, and sensing due to their unique electronic structural properties. Recent advances machine learning (ML) have opened new avenues for exploring optimizing the potential of these materials. This study presents comprehensive review integration ML techniques carbon an introduction CN classifications recent advancements. We discuss methodologies employed, such as supervised learning, unsupervised reinforcement predicting material properties, synthesis conditions, enhancing performance metrics. Key findings indicate that algorithms can significantly reduce experimental trial-and-error, accelerate discovery processes, provide deeper insights into structure-property relationships nitride. The synergistic effect combining traditional approaches is highlighted, showcasing studies where driven models successfully predicted novel compositions enhanced functional Future directions this field are also proposed, emphasizing need high-quality datasets, advanced models, interdisciplinary collaborations fully realize materials next-generation technologies.
Язык: Английский
Процитировано
1Langmuir, Год журнала: 2025, Номер unknown
Опубликована: Июнь 4, 2025
Potassium-ion batteries (KIBs) are gaining attention as potential next-generation energy storage devices. Nonetheless, the commercialization of KIBs has been hindered by a lack high-performance anode materials. In this study, we introduce multielement combination strategy to modulate structure and surface charge two-dimensional materials, considering competitive bonding interactions transfer between atoms. Through structural search calculations, uncover Si2BC monolayer, which exhibits three distinct types π-bonding strength. This material demonstrates excellent stability, intrinsic metallicity, superior electrochemical performance. Specifically, monolayer shows remarkably low K-ion migration barrier just 0.10 eV, theoretical capacity peaking at 1696.55 m Ah/g, an average open-circuit voltage 0.72 V, position it highly promising candidate for applications in KIBs. Notably, discover that strength π-bonds within is inversely related barriers, with stronger facilitating lower barriers optimizing ion mobility. finding provides valuable insights into role bond enhancing transport.
Язык: Английский
Процитировано
0Journal of Materials Chemistry A, Год журнала: 2024, Номер unknown
Опубликована: Янв. 1, 2024
Azulenoid kekulene-based metallic materials for high performance sodium-ion batteries.
Язык: Английский
Процитировано
2Journal of Materials Chemistry A, Год журнала: 2024, Номер 12(40), С. 27703 - 27711
Опубликована: Янв. 1, 2024
This study has employed boron carbide monolayers to reveal the key factors affecting anode performance of metal-ion batteries.
Язык: Английский
Процитировано
1Journal of Energy Storage, Год журнала: 2024, Номер 104, С. 114637 - 114637
Опубликована: Ноя. 19, 2024
Язык: Английский
Процитировано
1