Selective Photocatalytic C─H Oxidation Using All-Inorganic Perovskite Quantum Dots Encapsulated in UiO-Series MOFs.

IF 10.7 2区 材料科学 Q1 CHEMISTRY, PHYSICAL
Xiyu Liu, Sai Huang, Rebecca Shu Hui Khoo, Lu Huang, Wenqing Zhu, Linjun Wang
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引用次数: 0

Abstract

All-inorganic cesium lead halide (CsPbX3, X = Cl, Br, I) perovskite quantum dots (PeQDs) are successfully incorporated within the cages of zirconium-based UiO-series metal-organic frameworks (MOFs) using in situ ship-in-a-bottle method at room temperature under ambient conditions. The resulting mBPP-MOF, which includes the 4,4'-(2,2'-bipyridyl-5,5'-diyl)dibenzoic acid (H2BPP) linker, features a larger cavity size than UiO-66 and UiO-67-bpy, allowing for uniform accommodation of PeQDs within its cages. This PeQDs@MOF hybrid heterostructure enhances the separation and transfer of photogenerated charges, enabling the synthesized CsPbBr3@mBPP-MOF to demonstrate highly selective and stable performance in the photocatalytic oxidation of toluene under visible light irradiation at 395 nm. This advancement represents a potential breakthrough in organic photocatalysis due to the material's low cost, ease of processing, high efficiency, and tunable bandgap.

在室温环境条件下,采用原位瓶中船方法,成功地将全无机卤化铯铅(CsPbX3,X = Cl、Br、I)包晶量子点(PeQDs)并入锆基 UiO 系列金属有机框架(MOFs)的笼子中。与 UiO-66 和 UiO-67-bpy 相比,mBPP-MOF(包括 4,4'-(2,2'-联吡啶-5,5'-二基)二苯甲酸(H2BPP)连接体)具有更大的空腔尺寸,可以在其笼子中均匀地容纳 PeQDs。这种 PeQDs@MOF 混合异质结构增强了光生电荷的分离和转移,使合成的 CsPbBr3@mBPP-MOF 在 395 纳米可见光照射下光催化氧化甲苯时表现出高度的选择性和稳定性。由于该材料成本低、易于加工、效率高、带隙可调,因此这一进展代表了有机光催化领域的潜在突破。
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来源期刊
Small Methods
Small Methods Materials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍: Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques. With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community. The online ISSN for Small Methods is 2366-9608.
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