Analysis of the propylene epoxidation mechanism on supported gold nanoparticles
Analysis of the propylene epoxidation mechanism on supported gold nanoparticles
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负载金纳米粒子丙烯环氧化机理分析
DOI:
10.1016/j.ces.2017.09.018
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发表时间:
2017
影响因子:
4.7
通讯作者:
Lei, Yu
中科院分区:
文献类型:
--
作者:
Turner, C. Heath;Ji, Jingjing;Lu, Zheng;Lei, Yu
The direct propylene epoxidation reaction has been investigated experimentally in the past by several different groups, and gold-based catalysts tend to provide high selectivity for propylene oxide, but the conversion is relatively low. Models that can connect the atomistic catalytic details to the observed experimental data are desired, in order to identify new catalyst structures and formulations. While electronic structure calculations have been used to quantify some of the key reaction steps in the direct propylene epoxidation reaction, atomistic models for translating this information into more experimentally-relevant data are needed. Here, kinetic Monte Carlo (KMC) simulations are used to bridge this gap in the modeling hierarchy. Relevant data from previous experiments and electronic structure calculations are used to parameterize a KMC model for predicting propylene oxide production from an Au/TiO2/SiO2catalyst. The model connects the H2/O2-related reactions occurring on the Au sites with the epoxidation step on the isolated Ti surface sites. In addition, the composition in the bulk gas phase is synchronized with the dynamic reaction events occurring on the surface. The KMC model is able to adequately reproduce the experimental trends with respect to temperature and different reactant partial pressures. However, this is only achieved by considering the re-adsorption of trace amounts of the oxidant (H2O2) from the gas phase, versus merely assuming that desorbed species are immediately swept away in the gas stream.
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影响因子:
5.5
作者:
C. Qi;M. Okumura;T. Akita;M. Haruta
通讯作者:
C. Qi;M. Okumura;T. Akita;M. Haruta
影响因子:
4.4
作者:
S. Scarle;M. Sterzel;A. Eilmes;R. Munn
通讯作者:
R. Munn
DOI:
--
发表时间:
2008
期刊:
Physical review. E, Statistical, nonlinear, and soft matter physics
影响因子:
--
作者:
D. Vlachos
通讯作者:
D. Vlachos
DOI:
10.1063/1.4974261
发表时间:
2016
期刊:
The Journal of chemical physics
影响因子:
--
作者:
M. Hoffmann;Felix Engelmann;S. Matera
通讯作者:
S. Matera
影响因子:
--
作者:
J. Limtrakul;Chan Inntam;T. Truong
通讯作者:
J. Limtrakul;Chan Inntam;T. Truong