普鲁士蓝
材料科学
相变
多物理
纳米颗粒
化学物理
纳米晶
纳米技术
光谱学
热力学
电化学
物理化学
化学
物理
电极
量子力学
有限元法
作者
Guangxun Zhang,Wanchang Feng,Guangyu Du,Yong Cai Zhang,Ya Yang,Dian Xu,Tianyi Wang,Han‐Yi Chen,Huaiguo Xue,Mohsen Shakouri,Huan Pang
标识
DOI:10.1002/adma.202503814
摘要
Abstract Prussian blue analogs (PBAs) are exemplary precursors for the synthesis of a diverse array of derivatives.Yet, the intricate mechanisms underlying phase transitions in these multifaceted frameworks remain a formidable challenge. In this study, a machine learning‐guided analysis of phase transitions in a medium‐entropy PBA system is delineated, utilizing an array of descriptors that encompass crystallographic phases, structural subtleties, and fluctuations in multimetal valence states. By integrating multimodal simulations with experimental validation, a thermodynamics‐driven phase transformation model for medium‐entropy PBA is established and accurately predicted the critical synthesis parameters. A constellation of advanced techniques—including atomic force microscopy coupled with Kelvin probe force microscopy for individual nanoparticles, X‐ray absorption spectroscopy, operando ultraviolet‐visible spectroscopy, in situ X‐ray diffraction, theoretical calculations, and multiphysics simulations—substantiated that the iron oxide@NiCoZnFe‐PBA exhibits both exceptional stability and remarkable electrochemical activity. This investigation provides profound insights into the phase transition dynamics of polymetallic complexes and propels the rational design of other thermally‐induced derivatives.
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