A series of CeO_(2)-TiO_(2)mixed oxides supports with various Ce/Ti molar ratio were synthesized by modified coprecipitation method. The corresponding Pt loaded(0.5 wt% Pt) catalysts were prepared by electronless depo...A series of CeO_(2)-TiO_(2)mixed oxides supports with various Ce/Ti molar ratio were synthesized by modified coprecipitation method. The corresponding Pt loaded(0.5 wt% Pt) catalysts were prepared by electronless deposition method and evaluated for the deep oxidation of n-hexane as a model VOCs. The results show that the CeO_(2)and TiOxnanoparticles can highly disperse into each other and form Ce_(2)Ti_(2)O_(7)solid solution with appropriate Ce/Ti molar ratio, which significantly improves their redox ability by enhancing the interaction between CeO_(2)and TiO_(x). The dispersibility of Pt species can also be adjusted by altering the Ce/Ti molar ratio, and Pt/CeTi-2/1 catalyst with Ce/Ti molar ratio of 2:1 exhibits the best Pt dispersibility that Pt species mainly exist as Pt single atoms. The high dispersion of Pt species in the Pt/CeO_(2)-TiO_(2)catalysts would promote the catalytic activity of VOCs oxidation with low T90% values(1000 ppm, GHSV = 15,000 h^(-1)), such as for n-hexane degradation with T90% of 139℃. The characterizations reveal that the superior activity is mainly related to possessing the more Pt2+species,adsorbed oxygen species and higher low-temperature reducibility owing to the strong interaction between highly dispersed Pt species and CeO_(2)-TiO_(2)as well as the promoted migration of lattice oxygen by the formation of more Ce_(2)Ti_(2)O_(7)species. Furthermore, the Pt/CeTi-2/1 catalyst also exhibits excellent stability for chlorinated and other non-chlorinated VOCs oxidation, making it very promising for real application under various operating conditions.展开更多
Different zeolites supported Pt catalystswithmicro-mesoporous structurewere prepared by organic base tetrapropylammonium hydroxide(TPAOH)treatment and their catalytic oxidation activity for various volatile organic co...Different zeolites supported Pt catalystswithmicro-mesoporous structurewere prepared by organic base tetrapropylammonium hydroxide(TPAOH)treatment and their catalytic oxidation activity for various volatile organic compounds(VOCs)were evaluated.The results reveal that the synergistic effect between Pt nanoparticles and surface acid sites plays an important role in VOCs low-temperature removal.The small size and high dispersion of Pt nanoparticles on the surface of the zeolites would promote the catalytic oxidation of aromatics and alkanes over the Pt/zeolite catalysts,while strong acidity and abundant acid sites of catalysts are in favour of the oxidation of the VOCs containingNandOheteroatoms.In addition,it was found that Pt/ZSM-5 catalyst exhibits the highest oxidation activity for various VOCs low-temperature removal amongst all the catalysts due to the balance of both Pt dispersion and abundant acid sites in the catalyst.This comprehensive consideration should be very helpful when designing and preparing novel catalysts for the low-temperature removal of VOCs.展开更多
Practical experience has demonstrated that single objective functions, no matter how carefully chosen, prove to be inadequate in providing proper measurements for all of the characteristics of the observed data. One s...Practical experience has demonstrated that single objective functions, no matter how carefully chosen, prove to be inadequate in providing proper measurements for all of the characteristics of the observed data. One strategy to circumvent this problem is to define multiple fitting criteria that measure different aspects of system behavior, and to use multi-criteria optimization to identify non-dominated optimal solutions. Unfortunately, these analyses require running original simulation models thousands of times. As such, they demand prohibitively large computational budgets. As a result, surrogate models have been used in combination with a variety of multi- objective optimization algorithms to approximate the true Pareto-front within limited evaluations for the original model. In this study, multi-objective optimization based on surrogate modeling （multivariate adaptive regression splines, MARS） for a conceptual rainfall-runoff model （Xin＇anjiang model, XAJ） was proposed. Taking the Yanduhe basin of Three Gorges in the upper stream of the Yangtze River in China as a case study, three evaluation criteria were selected to quantify the goodness-of-fit of observations against calculated values from the simulation model. The three criteria chosen were the Nash-Sutcliffe efficiency coefficient, the relative error of peak flow, and runoff volume （REPF and RERV）. The efficacy of this method is demonstrated on the calibration of the XAJ model. Compared to the single objective optimization results, it was indicated that the multi-objective optimization method can infer the most probable parameter set. The results also demonstrate that the use of surrogate-modeling enables optimization that is much more efficient; and the total computational cost is reduced by about 92.5%, compared to optimization without using surrogate model- ing. The results obtained with the proposed method support the feasibility of applying parameter optimization to computationally intensive simulation models, via reducing the number of simulation runs required in the numerical model considerably.展开更多
基金supported by a grant from the National Key Research and Development Program of China (2016YFC0204300)the National Nature Science Foundation of China (21477109)。
文摘A series of CeO_(2)-TiO_(2)mixed oxides supports with various Ce/Ti molar ratio were synthesized by modified coprecipitation method. The corresponding Pt loaded(0.5 wt% Pt) catalysts were prepared by electronless deposition method and evaluated for the deep oxidation of n-hexane as a model VOCs. The results show that the CeO_(2)and TiOxnanoparticles can highly disperse into each other and form Ce_(2)Ti_(2)O_(7)solid solution with appropriate Ce/Ti molar ratio, which significantly improves their redox ability by enhancing the interaction between CeO_(2)and TiO_(x). The dispersibility of Pt species can also be adjusted by altering the Ce/Ti molar ratio, and Pt/CeTi-2/1 catalyst with Ce/Ti molar ratio of 2:1 exhibits the best Pt dispersibility that Pt species mainly exist as Pt single atoms. The high dispersion of Pt species in the Pt/CeO_(2)-TiO_(2)catalysts would promote the catalytic activity of VOCs oxidation with low T90% values(1000 ppm, GHSV = 15,000 h^(-1)), such as for n-hexane degradation with T90% of 139℃. The characterizations reveal that the superior activity is mainly related to possessing the more Pt2+species,adsorbed oxygen species and higher low-temperature reducibility owing to the strong interaction between highly dispersed Pt species and CeO_(2)-TiO_(2)as well as the promoted migration of lattice oxygen by the formation of more Ce_(2)Ti_(2)O_(7)species. Furthermore, the Pt/CeTi-2/1 catalyst also exhibits excellent stability for chlorinated and other non-chlorinated VOCs oxidation, making it very promising for real application under various operating conditions.
基金supported by a grant from the National Key Research and Development Program of China (No. 2016YFC0204300)the Nature Science Foundation of China (No. 21477109)
文摘Different zeolites supported Pt catalystswithmicro-mesoporous structurewere prepared by organic base tetrapropylammonium hydroxide(TPAOH)treatment and their catalytic oxidation activity for various volatile organic compounds(VOCs)were evaluated.The results reveal that the synergistic effect between Pt nanoparticles and surface acid sites plays an important role in VOCs low-temperature removal.The small size and high dispersion of Pt nanoparticles on the surface of the zeolites would promote the catalytic oxidation of aromatics and alkanes over the Pt/zeolite catalysts,while strong acidity and abundant acid sites of catalysts are in favour of the oxidation of the VOCs containingNandOheteroatoms.In addition,it was found that Pt/ZSM-5 catalyst exhibits the highest oxidation activity for various VOCs low-temperature removal amongst all the catalysts due to the balance of both Pt dispersion and abundant acid sites in the catalyst.This comprehensive consideration should be very helpful when designing and preparing novel catalysts for the low-temperature removal of VOCs.
基金Acknowledgements The work was supported by the National Basic Research Program of China （No. 2010CB951103）, the National Natural Science Foundation of China （Grant Nos. 41330854, 41371063 and 51309155） and the National Science ＆ Technology Pillar Program during the 12th Five-year Plan Period （2012BAC21B01 and 2012BAC19B03）. We are also thankful to anonymous reviewers and editors for their helpful comments and suggestions.
文摘Practical experience has demonstrated that single objective functions, no matter how carefully chosen, prove to be inadequate in providing proper measurements for all of the characteristics of the observed data. One strategy to circumvent this problem is to define multiple fitting criteria that measure different aspects of system behavior, and to use multi-criteria optimization to identify non-dominated optimal solutions. Unfortunately, these analyses require running original simulation models thousands of times. As such, they demand prohibitively large computational budgets. As a result, surrogate models have been used in combination with a variety of multi- objective optimization algorithms to approximate the true Pareto-front within limited evaluations for the original model. In this study, multi-objective optimization based on surrogate modeling （multivariate adaptive regression splines, MARS） for a conceptual rainfall-runoff model （Xin＇anjiang model, XAJ） was proposed. Taking the Yanduhe basin of Three Gorges in the upper stream of the Yangtze River in China as a case study, three evaluation criteria were selected to quantify the goodness-of-fit of observations against calculated values from the simulation model. The three criteria chosen were the Nash-Sutcliffe efficiency coefficient, the relative error of peak flow, and runoff volume （REPF and RERV）. The efficacy of this method is demonstrated on the calibration of the XAJ model. Compared to the single objective optimization results, it was indicated that the multi-objective optimization method can infer the most probable parameter set. The results also demonstrate that the use of surrogate-modeling enables optimization that is much more efficient; and the total computational cost is reduced by about 92.5%, compared to optimization without using surrogate model- ing. The results obtained with the proposed method support the feasibility of applying parameter optimization to computationally intensive simulation models, via reducing the number of simulation runs required in the numerical model considerably.
