Development of high-performance hydroxide-conductive membranes is a focus research subject owing to promising applications in electrochemical reduction of CO_(2)(eCO_(2)RR).However,few satisfactory membranes have been...Development of high-performance hydroxide-conductive membranes is a focus research subject owing to promising applications in electrochemical reduction of CO_(2)(eCO_(2)RR).However,few satisfactory membranes have been developed to maximize the performance of CO_(2) electrolyzers,despite its role as the core in regulating ion transport and preventing product crossover or fuel loss.Herein,we report the synthesis of alkaline anion-exchange membranes fabricated by poly(vinyl-alcohol)(PVA)and poly[(3-methyl-1-vinylimidazoliummethylsulfate)-co-(1-vinylpyrrolidone)](PQ44)for use in CO_(2) electrolysis.Owing to the unique imidazolium ring structure coupled with a three-dimensional semiinterpenetrating porous internal architecture,the PVA/PQ44-OH-membranes provide a high hydroxide conductivity(21.47 mS cm^(-1)),preferable mechanical property and thermal stability.In particular,the eCO_(2)RR used PVA/PQ44-OH^(-) as electrolyte membrane realized a charming Faradaic efficiency(88%)and partial current density(29 mA cm^(-2))at0.96 VRHE and,delivered the excellent durability over 20 h electrolysis in 0.5 mol L^(-1) KHCO_(3) electrolyte.Notably,it can even enable an ultrahigh current density beyond 100 mA cm^(-2) at^(-1).11 VRHE when the electrolyte was KOH instead,and produced the FEHCOOof 85%at a low potential of0.81 VRHE,superior to both commercial alkaline A201 and acidic Nafion117 membrane.展开更多
The indicator system is the foundation and emphasis in the effectiveness evaluation of system of systems(SoS). In the past, indicator systems were founded based on qualitative methods, and every indicator was mainly d...The indicator system is the foundation and emphasis in the effectiveness evaluation of system of systems(SoS). In the past, indicator systems were founded based on qualitative methods, and every indicator was mainly determined by the expert with experience. This paper proposed a brand-new method to construct indicator systems based on the repeated simulation of the scenario space, and calculated by quantitative data. Firstly, the selection of key indicators using the Gini indicator importance measure(IIM)is calculated by random forests(RFs). Then, principal component analysis(PCA) is applied when we use the selected indicators to construct the composite indicator system of SoS. Furthermore,a set of rulesare is developed to verify the practicability of the indicator system such as correlation, robustness, accuracy and convergence. Experiment shows that the algorithm achieves good results for the construction of composite indicators of So S.展开更多
In the field of weapon system of systems (WSOS) simulation, various indicators are widely used to describe the capability of WSOS, but it is always difficult to describe the comprehensive capability of WSOS quickly an...In the field of weapon system of systems (WSOS) simulation, various indicators are widely used to describe the capability of WSOS, but it is always difficult to describe the comprehensive capability of WSOS quickly and intuitively by visualization of multi-dimensional indicators. A method of machine learning and visualization is proposed, which can display and analyze the capabilities of different WSOS in a two-dimensional plane. The analysis and comparison of the comprehensive capability of different components of WSOS is realized by the method, which consists of six parts: multiple simulations, key indicators mining, three spatial distance calculation, fusion project calculation, calculation of individual capability density, and calculation of multiple capability ranges overlay. Binding a simulation experiment, the collaborative analysis of six indicators and 100 possible kinds of red WSOS are achieved. The experimental results show that this method can effectively improve the quality and speed of capabilities analysis, reveal a large number of potential information, and provide a visual support for the qualitative and quantitative analysis model.展开更多
基金support from the“Scientific and Technical Innovation Action Plan”Basic Research Field of Shanghai Science and Technology Committee (19JC1410500)the National Natural Science Foundation of China (21972017).
文摘Development of high-performance hydroxide-conductive membranes is a focus research subject owing to promising applications in electrochemical reduction of CO_(2)(eCO_(2)RR).However,few satisfactory membranes have been developed to maximize the performance of CO_(2) electrolyzers,despite its role as the core in regulating ion transport and preventing product crossover or fuel loss.Herein,we report the synthesis of alkaline anion-exchange membranes fabricated by poly(vinyl-alcohol)(PVA)and poly[(3-methyl-1-vinylimidazoliummethylsulfate)-co-(1-vinylpyrrolidone)](PQ44)for use in CO_(2) electrolysis.Owing to the unique imidazolium ring structure coupled with a three-dimensional semiinterpenetrating porous internal architecture,the PVA/PQ44-OH-membranes provide a high hydroxide conductivity(21.47 mS cm^(-1)),preferable mechanical property and thermal stability.In particular,the eCO_(2)RR used PVA/PQ44-OH^(-) as electrolyte membrane realized a charming Faradaic efficiency(88%)and partial current density(29 mA cm^(-2))at0.96 VRHE and,delivered the excellent durability over 20 h electrolysis in 0.5 mol L^(-1) KHCO_(3) electrolyte.Notably,it can even enable an ultrahigh current density beyond 100 mA cm^(-2) at^(-1).11 VRHE when the electrolyte was KOH instead,and produced the FEHCOOof 85%at a low potential of0.81 VRHE,superior to both commercial alkaline A201 and acidic Nafion117 membrane.
基金supported by the Major Program of the National Natural Science Foundation of China(U1435218)National Natural Science Foundation of China(6140340171401168)
文摘The indicator system is the foundation and emphasis in the effectiveness evaluation of system of systems(SoS). In the past, indicator systems were founded based on qualitative methods, and every indicator was mainly determined by the expert with experience. This paper proposed a brand-new method to construct indicator systems based on the repeated simulation of the scenario space, and calculated by quantitative data. Firstly, the selection of key indicators using the Gini indicator importance measure(IIM)is calculated by random forests(RFs). Then, principal component analysis(PCA) is applied when we use the selected indicators to construct the composite indicator system of SoS. Furthermore,a set of rulesare is developed to verify the practicability of the indicator system such as correlation, robustness, accuracy and convergence. Experiment shows that the algorithm achieves good results for the construction of composite indicators of So S.
基金supported by the National Natural Science Foundation of China(U14352186140340161273189)
文摘In the field of weapon system of systems (WSOS) simulation, various indicators are widely used to describe the capability of WSOS, but it is always difficult to describe the comprehensive capability of WSOS quickly and intuitively by visualization of multi-dimensional indicators. A method of machine learning and visualization is proposed, which can display and analyze the capabilities of different WSOS in a two-dimensional plane. The analysis and comparison of the comprehensive capability of different components of WSOS is realized by the method, which consists of six parts: multiple simulations, key indicators mining, three spatial distance calculation, fusion project calculation, calculation of individual capability density, and calculation of multiple capability ranges overlay. Binding a simulation experiment, the collaborative analysis of six indicators and 100 possible kinds of red WSOS are achieved. The experimental results show that this method can effectively improve the quality and speed of capabilities analysis, reveal a large number of potential information, and provide a visual support for the qualitative and quantitative analysis model.
