Thermally stable ordered mesoporous CeO2/TiO2 visible-light photocatalysts

文献信息

发布日期 2009-02-25
DOI 10.1039/B819167K
影响因子 3.676
作者

Guisheng Li, Dieqing Zhang, Jimmy C. Yu


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摘要

Thermally stable, ordered mesoporous CeO2/TiO2 (Ce/Ti molar ratio = 0.05) visible-light photocatalysts have been fabricated by the evaporation-induced self-assembly method. Introducing highly dispersed CeO2 species into the mesoporous TiO2 framework can effectively extend the response of TiO2 to the visible-light region and improve the thermal stability of the mesoporous TiO2. The products calcined at 500 °C exhibit superior photocatalytic performance in the photochemical degradation of methylene blue under visible-light irradiation. The products are characterized by using X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), Raman, photo-luminescent (PL), and ultraviolet–visible-light reflectance (UV-vis) spectroscopy. The relationship between the physicochemical property and the photocatalytic performance of the as-prepared samples is discussed.

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来源期刊

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
自引率: 10.3%
年发文量: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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