Authors
Qian Li, Yanfei Zhang, Xiaotian Guo, Zhangbin Yang, Yixuan Wang, Yumeng Chen, Yiwen Liu, Haotian Yue, Shengjie Gao, Huijie Zhou, Jianfei Huang, Mohsen Shakouri, Yonggang Wang, Guoyin Zhu, Zheng Liu, Yizhou Zhang, Huan Pang
Published in
Angewandte Chemie (International ed. in English). Pages e202509741. May 23, 2025. Epub May 23, 2025.
Abstract
Nucleation and growth of metal-organic frameworks (MOFs) are critical for controlling their morphology, size, and performance. Guided by the crystal nucleation and growth theory, this study systematically explored the effects of the sequential addition of ligand trimesic acid (BTC) and manganese ions (Mn2+), ligand-to-metal ion ratio, solvent composition, and surfactants on the nucleation and growth of MnBTC. The regulatory mechanisms of the crystal morphology and internal structure were deeply revealed. Moreover, the established machine learning (ML) model can accurately predict the concentrations of -COO- and Mn2+, providing important guidance for the controlled synthesis of MOFs in the future. In practical, the electrochemical performance of MnBTC with different morphologies and sizes was evaluated for aqueous zinc-ion batteries. The reaction mechanism of MnBTC during the charge-discharge process was investigated through a series of in-situ and ex-situ characterizations, and MnBTC demonstrated excellent energy-storage performance. This study opens a new window for the precise synthesis of MOFs which show strongly controlled micro/nano structure and coordination environment based on the crystal nucleation and growth theory with the assistance of ML.
PMID:
40406804
Bibliographic data and abstract were imported from PubMed on 23 May 2025.
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