纳米颗粒
金属有机骨架
催化作用
连接器
材料科学
阳离子聚合
傅里叶变换红外光谱
多相催化
吸附
化学工程
金属
纳米技术
化学
物理化学
高分子化学
有机化学
计算机科学
工程类
冶金
操作系统
作者
Cassandra L. Whitford,Casey J. Stephenson,Diego A. Gómez‐Gualdrón,Joseph T. Hupp,Omar K. Farha,Randall Q. Snurr,Peter C. Stair
标识
DOI:10.1021/acs.jpcc.7b06773
摘要
Composites of metal nanoparticles encapsulated in metal–organic frameworks (NP@MOFs) have emerged as heterogeneous catalysts for regioselective reactions. While numerous NP@MOF composite combinations have been synthesized, characterization of the nanoparticle–MOF interface and the encapsulated nanoparticle surface have yet to be determined. In this work, Pt@ZIF-8 synthesized by the controlled encapsulation method was chosen as a representative NP@MOF, and in situ characterization methods coupled with density functional theory (DFT) calculations were used to probe the nanoparticle surface. CO adsorption diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) revealed that Pt@ZIF-8 exhibits red-shifted linear- and bridge-bound CO peaks and a linear peak associated with cationic Pt. DFT calculations and 1H NMR suggest that these sites arise from the binding and electronic donation of the MOF linker, 2-methylimidazole, to the Pt surface. DRIFTS under argon reveals that linker fragments may be present on the Pt nanoparticle surface, suggesting a reaction between the nanoparticle and the MOF linker during controlled encapsulation synthesis. Finally, CO oxidation reveals via DRIFTS that the red-shifted linear CO and bridging CO sites are active sites, while the cationic Pt is not. Overall, these results show that Pt@ZIF-8 contains unique Pt surface sites and indicate that the nanoparticle–MOF interface contains a heterogeneous mixture of framework 2-methylimidazole, free-standing 2-methylimidazole, and linker fragments. These findings expose the complex nature of the nanoparticle surface in NP@MOF composites and demonstrate the importance of characterizing their surface to understand their catalytic behavior.
科研通智能强力驱动
Strongly Powered by AbleSci AI