钙钛矿(结构)
材料科学
原子间势
格子(音乐)
化学物理
纳米颗粒
镍
密度泛函理论
纳米晶
矿物学
分子动力学
能量密度
订单(交换)
多尺度建模
科技与社会
作者
Dongjae Kong,Arron R. Potter,Yuzhe Li,Kiran Hamkins,Yue Wang,Xiaolin Zheng
出处
期刊:Nano Letters
[American Chemical Society]
日期:2026-06-18
卷期号:26 (25): 8164-8172
标识
DOI:10.1021/acs.nanolett.6c01218
摘要
While high-entropy perovskite oxides have recently emerged as promising hosts for exsolution-enabled catalysts and electrodes, a systematic understanding of how high-entropy compositions influence exsolution remains limited. Here, we compare Ni exsolution in a simpler perovskite oxide, (La 0.6 Sr 0.4 ) 0.95 (Co 0.19 Fe 0.76 Ni 0.05 )O 3−δ (LSCF-5Ni), and two high-entropy perovskite oxides, (La 0.2 Sr 0.2 Ca 0.2 Nd 0.2 Y 0.2 ) 0.95 (Co 0.19 Fe 0.76 Ni 0.05 )O 3−δ (CaNdY-5Ni) and (La 0.2 Sr 0.2 Ba 0.2 Nd 0.2 Y 0.2 ) 0.95 (Co 0.19 Fe 0.76 Ni 0.05 )O 3−δ (BaNdY-5Ni). The experiment reveals that the exsolved nanoparticle number density follows the order LSCF-5Ni < CaNdY-5Ni < BaNdY-5Ni, demonstrating that high-entropy configurations can enhance exsolution. To understand this trend, we develop a Monte Carlo-based modeling framework that combines a machine-learned interatomic potential to simulate representative atomic configurations and statistically evaluate possible exsolution pathways. The results show that high-entropy configurations with greater variations in A-site cation sizes (and thus greater lattice distortions) can broaden distributions of Ni migration and reduction energies, thereby creating more thermodynamically favorable exsolution pathways.
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