Our recent theoretical studies have screened out CuCs-doped Ag-based promising catalysts for ethylene epoxidation[ACS Catal.11,3371(2021)].The theoretical results were based on surface modeling,while in the actual rea...Our recent theoretical studies have screened out CuCs-doped Ag-based promising catalysts for ethylene epoxidation[ACS Catal.11,3371(2021)].The theoretical results were based on surface modeling,while in the actual reaction process Ag catalysts are particle shaped.In this work,we combine density functional theory(DFT),Wulff construction theory,and micro kinetic analysis to study the catalytic performance of Ag catalysts at the particle model.It demonstrates that the CuCs-doped Ag catalysts are superior to pure Ag catalysts in terms of selectivity and activity,which is further proved by experimental validation.The characterization analysis finds that both Cu and Cs dopant promote particle growth as well as particle dispersion,resulting in a grain boundary-rich Ag particle.Besides,CuCs also facilitate electrophilic atomic oxygen formation on catalyst surface,which is benefitial for ethylene oxide formation and desorption.Our work provides a case study for catalyst design by combining theory and experiment.展开更多
Various scaling relations have long been established in the field of heterogeneous catalysis,but the resultant volcano curves inherently limit the catalytic performance of catalyst candidates.On the other hand,it is s...Various scaling relations have long been established in the field of heterogeneous catalysis,but the resultant volcano curves inherently limit the catalytic performance of catalyst candidates.On the other hand,it is still very challenging to develop universal descriptors that can be used in various types of catalysts and reaction systems.For these reasons,several strategies have recently been proposed to break and rebuild scaling relations to go beyond the top of volcanoes.In this review,some previously proposed descriptors have been briefly introduced.Then,the strategies for breaking known and establishing new and more generalized scaling relations in complex catalytic systems have been summarized.Finally,the application of machine-learning techniques in identifying universal descriptors for future computational design and high-throughput screening of heterogeneous catalysts has been discussed.展开更多
基金This work is supported by PetroChina Innovation Foundation(2019D-5007-0403).
文摘Our recent theoretical studies have screened out CuCs-doped Ag-based promising catalysts for ethylene epoxidation[ACS Catal.11,3371(2021)].The theoretical results were based on surface modeling,while in the actual reaction process Ag catalysts are particle shaped.In this work,we combine density functional theory(DFT),Wulff construction theory,and micro kinetic analysis to study the catalytic performance of Ag catalysts at the particle model.It demonstrates that the CuCs-doped Ag catalysts are superior to pure Ag catalysts in terms of selectivity and activity,which is further proved by experimental validation.The characterization analysis finds that both Cu and Cs dopant promote particle growth as well as particle dispersion,resulting in a grain boundary-rich Ag particle.Besides,CuCs also facilitate electrophilic atomic oxygen formation on catalyst surface,which is benefitial for ethylene oxide formation and desorption.Our work provides a case study for catalyst design by combining theory and experiment.
基金supported by the National Natural Science Founda-tion of China(21473053,91645122,and 22073027)the Natural Science Foundation of Shanghai(20ZR1415800)the Funda-mental Research Funds for the Central Universities(222201718003).
文摘Various scaling relations have long been established in the field of heterogeneous catalysis,but the resultant volcano curves inherently limit the catalytic performance of catalyst candidates.On the other hand,it is still very challenging to develop universal descriptors that can be used in various types of catalysts and reaction systems.For these reasons,several strategies have recently been proposed to break and rebuild scaling relations to go beyond the top of volcanoes.In this review,some previously proposed descriptors have been briefly introduced.Then,the strategies for breaking known and establishing new and more generalized scaling relations in complex catalytic systems have been summarized.Finally,the application of machine-learning techniques in identifying universal descriptors for future computational design and high-throughput screening of heterogeneous catalysts has been discussed.
