Dataset Information

Quantitative Conversion of Methanol to Methyl Formate on Graphene-Confined Nano-Oxides.

ABSTRACT: We demonstrate the nearly quantitative conversion of methanol to methyl formate (MF) with a reliable durability on the reduced-graphene-oxide-confined VTiOx nanoparticles (rGO@VTiO). The rGO@VTiO exhibits superior low-temperature reactivity than the rGO-free VTiO, and the MF yield of 98.8% is even comparable with the noble metal catalysts. Both experiments and simulations demonstrate that the ultrathin rGO shell significantly impacts the shell/core interfacial electronic structure and the surface chemistry of the resultant catalysts, leading to remarkable reactivity in methanol to MF. rGO enhances the dispersion and loading rates of active monomeric/oligomeric VOx. In particular, the electron migration between the rGO shell and oxides core reinforces the acidity of rGO@VTiO in the absence of sulfate acidic sites. Moreover, both in situ NAP-XPS and DRIFTS investigations suggest that the lattice oxygen was involved in the oxidation of methanol and the MF was formed via the hemiacetal mechanism.

SUBMITTER: Zhang Y

PROVIDER: S-EPMC7251949 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Quantitative Conversion of Methanol to Methyl Formate on Graphene-Confined Nano-Oxides.

Zhang Yelei Y Liu Guojuan G Shi Lei L Wu Ping P Zeng Gaofeng G Zhang Chunlei C Yang Nating N Li Shenggang S Sun Yuhan Y

iScience 20200519 6

We demonstrate the nearly quantitative conversion of methanol to methyl formate (MF) with a reliable durability on the reduced-graphene-oxide-confined VTiOx nanoparticles (rGO@VTiO). The rGO@VTiO exhibits superior low-temperature reactivity than the rGO-free VTiO, and the MF yield of 98.8% is even comparable with the noble metal catalysts. Both experiments and simulations demonstrate that the ultrathin rGO shell significantly impacts the shell/core interfacial electronic structure and the surfac ...[more]

PMID: 32450511

Similar Datasets

Project description:Segmental dynamics in unentangled isotactic, syndiotactic, and atactic poly(methyl methacrylate) (i-, a-, and s-PMMA) melts confined between pristine graphene, reduced graphene oxide, RGO, or graphene oxide, GO, sheets is studied at various temperatures, well above glass transition temperature, via atomistic molecular dynamics simulations. The model RGO and GO sheets have different degrees of oxidization. The segmental dynamics is studied through the analysis of backbone torsional motions. In the vicinity of the model nanosheets (distances less than ≈2 nm), the dynamics slows down; the effect becomes significantly stronger with increasing the concentration of the surface functional groups, and hence increasing polymer/surface specific interactions. Upon decreasing temperature, the ratios of the interfacial segmental relaxation times to the respective bulk relaxation times increase, revealing the stronger temperature dependence of the interfacial segmental dynamics relative to the bulk dynamics. This heterogeneity in temperature dependence leads to the shortcoming of the time-temperature superposition principle for describing the segmental dynamics of the model confined melts. The alteration of the segmental dynamics at different distances, d, from the surfaces is described by a temperature shift, ΔTseg(d) (roughly speaking, shift of a characteristic temperature). Next, to a given nanosheet, i-PMMA has a larger value of ΔTseg than a-PMMA and s-PMMA. This trend correlates with the better interfacial packing and longer trains of i-PMMA chains. The backbone torsional autocorrelation functions are shown in the frequency domain and are qualitatively compared to the experimental dielectric loss spectra for the segmental α-relaxation in polymer nanocomposites. The εT″(f) (analogous of dielectric loss, ε″(f), for torsional motion) curves of the model confined melts are broader (toward lower frequencies) and have lower amplitudes relative to the corresponding bulk curves; however, the peak frequencies of the εT″(f) curves are only slightly affected.

Dataset Information

Quantitative Conversion of Methanol to Methyl Formate on Graphene-Confined Nano-Oxides.

Publications

Quantitative Conversion of Methanol to Methyl Formate on Graphene-Confined Nano-Oxides.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets