Metal-Ion Distribution and Oxygen Vacancies That Determine the Activity of Magnetically Recoverable Catalysts in Methanol Synthesis.
Troy OrackoRigel JaquishYaroslav B LosovyjDavid Gene MorganMaren PinkBarry D SteinValentin Yu DoludaOlga P TkachenkoZinaida B ShifrinaMaxim E GrigorievAlexander I SidorovEsther M SulmanLyudmila M BronsteinPublished in: ACS applied materials & interfaces (2017)
Here, we report on the development of novel Zn-, Zn-Cr-, and Zn-Cu-containing catalysts using magnetic silica (Fe3O4-SiO2) as the support. Transmission electron microscopy, powder X-ray diffraction, and X-ray photoelectron spectroscopy (XPS) showed that the iron oxide nanoparticles are located in mesoporous silica pores and the magnetite (spinel) structure remains virtually unchanged despite the incorporation of Zn and Cr. According to XPS data, the Zn and Cr species are intermixed within the magnetite structure. In the case of the Zn-Cu-containing catalysts, a separate Cu2O phase was also observed along with the spinel structure. The catalytic activity of these catalysts was tested in methanol synthesis from syngas (CO + H2). The catalytic experiments showed an improved catalytic performance of Zn- and Zn-Cr-containing magnetic silicas compared to that of the ZnO-SiO2 catalyst. The best catalytic activity was obtained for the Zn-Cr-containing magnetic catalyst prepared with 1 wt % Zn and Cr each. X-ray absorption spectroscopy demonstrated the presence of oxygen vacancies near Fe and Zn in Zn-containing, and even more in Zn-Cr-containing, magnetic silica (including oxygen vacancies near Cr ions), revealing a correlation between the catalytic properties and oxygen vacancies. The easy magnetic recovery, robust synthetic procedure, and high catalytic activity make these catalysts promising for practical applications.
Keyphrases
- heavy metals
- highly efficient
- metal organic framework
- molecularly imprinted
- magnetic resonance imaging
- machine learning
- magnetic resonance
- room temperature
- gold nanoparticles
- computed tomography
- quantum dots
- minimally invasive
- single molecule
- ionic liquid
- deep learning
- aqueous solution
- transition metal
- dual energy
- liquid chromatography
- visible light