Catalytic reduction of nitrate over bimetallic catalysts has emerged as a technology for sustainable treatment of nitrate-containing groundwater.However,the structure of bimetallic has been much less investigated for ...Catalytic reduction of nitrate over bimetallic catalysts has emerged as a technology for sustainable treatment of nitrate-containing groundwater.However,the structure of bimetallic has been much less investigated for catalyst optimization.Herein,two main types of Pd-Cu bimetallic nanocrystal structures,heterostructure and intermetallic,were prepared and characterized using high-resolution transmission electron microscopy(HRTEM),X-ray diffraction(XRD),and X-ray photoelectron spectroscopy(XPS).The results show that two individual Pd and Cu nanocrystals with a mixed interface exist in the heterostructure nanocrystals,while Pd and Cu atoms are uniformly distributed across the intermetallic Pd-Cu nanocrystals.The catalytic nitrate reduction experiments were carried out in a semibatch reactor under constant hydrogen flow.The nitrate conversion rate of the heterostructure Pd-Cu nanocrystals supported onα-Al_(2)O_(3),γ-Al_(2)O_(3),SBA-15,and XC-72R exhibited 3.82-,6.76-,4.28-,2.44-fold enhancements relative to the intermetallic nanocrystals,and the nitrogen and nitrite were the main products for the heterostructure and intermetallic Pd-Cu nanocrystals,respectively.This indicates that the catalytic nitrate reduction over Pd-Cu catalyst is sensitive to the bimetallic structures of the catalysts,and heterostructure bimetallic nanocrystals exhibit better catalytic performances on both the activity and selectivity,which may provide new insights into the design and optimization of catalysts to improve catalytic activity and selectivity for nitrate reduction in water.展开更多
Accurate and reliable groundwater contaminant source characterization with limited contaminant concentration monitoring measurement data remains a challenging problem. This study presents an illustrative application o...Accurate and reliable groundwater contaminant source characterization with limited contaminant concentration monitoring measurement data remains a challenging problem. This study presents an illustrative application of developed methodologies to a real-life contaminated aquifer. The source characterization and optimal monitoring network design methodologies are used sequentially for a contaminated aquifer site located in New South Wales, Australia. Performance of the integrated optimal source characterization methodology combining linked simulation-optimization, fractal singularity mapping technique (FSMT) and Pareto optimal solutions is evaluated. This study presents an integrated application of optimal source characterization with spatiotemporal concentration measurement data obtained from sequentially designed monitoring networks. The proposed sequential source characterization and monitoring network design methodology shows efficiency in identifying the unknown source characteristics. The designed monitoring network achieves comparable efficiency and accuracy utilizing much smaller number of monitoring locations as compared to a more ideal scenario where concentration measurements from a very large number of widespread monitoring wells are available. The proposed methodology is potentially useful for efficient characterization of unknown contaminant sources in a complex contaminated aquifer site, where very little initial concentration measurement data are available. The illustrative application of the methodology to a real-life contaminated aquifer site demonstrates the capability and efficiency of the proposed methodology.展开更多
基金support from the National Natural Science Foundation of China(Nos.52370100,52000146,and 51978098)China Postdoctoral Science Foundation(No.2020M673351).
文摘Catalytic reduction of nitrate over bimetallic catalysts has emerged as a technology for sustainable treatment of nitrate-containing groundwater.However,the structure of bimetallic has been much less investigated for catalyst optimization.Herein,two main types of Pd-Cu bimetallic nanocrystal structures,heterostructure and intermetallic,were prepared and characterized using high-resolution transmission electron microscopy(HRTEM),X-ray diffraction(XRD),and X-ray photoelectron spectroscopy(XPS).The results show that two individual Pd and Cu nanocrystals with a mixed interface exist in the heterostructure nanocrystals,while Pd and Cu atoms are uniformly distributed across the intermetallic Pd-Cu nanocrystals.The catalytic nitrate reduction experiments were carried out in a semibatch reactor under constant hydrogen flow.The nitrate conversion rate of the heterostructure Pd-Cu nanocrystals supported onα-Al_(2)O_(3),γ-Al_(2)O_(3),SBA-15,and XC-72R exhibited 3.82-,6.76-,4.28-,2.44-fold enhancements relative to the intermetallic nanocrystals,and the nitrogen and nitrite were the main products for the heterostructure and intermetallic Pd-Cu nanocrystals,respectively.This indicates that the catalytic nitrate reduction over Pd-Cu catalyst is sensitive to the bimetallic structures of the catalysts,and heterostructure bimetallic nanocrystals exhibit better catalytic performances on both the activity and selectivity,which may provide new insights into the design and optimization of catalysts to improve catalytic activity and selectivity for nitrate reduction in water.
文摘Accurate and reliable groundwater contaminant source characterization with limited contaminant concentration monitoring measurement data remains a challenging problem. This study presents an illustrative application of developed methodologies to a real-life contaminated aquifer. The source characterization and optimal monitoring network design methodologies are used sequentially for a contaminated aquifer site located in New South Wales, Australia. Performance of the integrated optimal source characterization methodology combining linked simulation-optimization, fractal singularity mapping technique (FSMT) and Pareto optimal solutions is evaluated. This study presents an integrated application of optimal source characterization with spatiotemporal concentration measurement data obtained from sequentially designed monitoring networks. The proposed sequential source characterization and monitoring network design methodology shows efficiency in identifying the unknown source characteristics. The designed monitoring network achieves comparable efficiency and accuracy utilizing much smaller number of monitoring locations as compared to a more ideal scenario where concentration measurements from a very large number of widespread monitoring wells are available. The proposed methodology is potentially useful for efficient characterization of unknown contaminant sources in a complex contaminated aquifer site, where very little initial concentration measurement data are available. The illustrative application of the methodology to a real-life contaminated aquifer site demonstrates the capability and efficiency of the proposed methodology.
