The development of passive NO_(x)adsorbers with cost-benefit and high NO_(x)storage capacity remains an on-going challenge to after-treatment technologies at lower temperatures associated with cold-start NO_(x)emissio...The development of passive NO_(x)adsorbers with cost-benefit and high NO_(x)storage capacity remains an on-going challenge to after-treatment technologies at lower temperatures associated with cold-start NO_(x)emissions.Herein,Cs_(1)Mg_(3)Al catalyst prepared by sol-gel method was cyclic tested in NO_(x)storage under 5 vol%water.At 100°C,the NO_(x)storage capacity(1219 μmol g^(-1))was much higher than that of Pt/BaO/Al_(2)O_(3)(610 μmol g^(-1)).This provided new insights for non-noble metal catalysts in low-temperature passive NO_(x)adsorption.The addition of Cs improved the mobility of oxygen species and thus improved the NO_(x)storage capacity.The XRD,XPS,IR spectra and in situ DRIFTs with NH3 probe showed an interaction between CsO_(x)and AlO_(x)sites via oxygen species formed on Cs_(1)Mg_(3)Al catalyst.The improved mobility of oxygen species inferred from O2-TPD was consistent with high NO_(x)storage capacity related to enhanced formation of nitrate and additional nitrite species by NO_(x)oxidation.Moreover,the addition of Mg might improve the stability of Cs_(1)Mg_(3)Al by stabilizing surface active oxygen species in cyclic experiments.展开更多
The rising flexible and intelligent electronics greatly facilitate the noninvasive and timely tracking of physiological information in telemedicine healthcare.Meticulously building bionic-sensitive moieties is vital f...The rising flexible and intelligent electronics greatly facilitate the noninvasive and timely tracking of physiological information in telemedicine healthcare.Meticulously building bionic-sensitive moieties is vital for designing efficient electronic skin with advanced cognitive functionalities to pluralistically capture external stimuli.However,realistic mimesis,both in the skin’s three-dimensional interlocked hierarchical structures and synchronous encoding multistimuli information capacities,remains a challenging yet vital need for simplifying the design of flexible logic circuits.Herein,we construct an artificial epidermal device by in situ growing Cu_(3)(HHTP)_(2) particles onto the hollow spherical Ti_(3)C_(2)T_(x) surface,aiming to concurrently emulate the spinous and granular layers of the skin’s epidermis.The bionic Ti_(3)C_(2)T_(x)@Cu_(3)(HHTP)_(2) exhibits independent NO_(2) and pressure response,as well as novel functionalities such as acoustic signature perception and Morse code-encrypted message communication.Ultimately,a wearable alarming system with a mobile application terminal is self-developed by integrating the bimodular senor into flexible printed circuits.This system can assess risk factors related with asthmatic,such as stimulation of external NO_(2) gas,abnormal expiratory behavior and exertion degrees of fingers,achieving a recognition accuracy of 97.6%as assisted by a machine learning algorithm.Our work provides a feasible routine to develop intelligent multifunctional healthcare equipment for burgeoning transformative telemedicine diagnosis.展开更多
Excessive emissions of nitrogen oxides from flue gas have imposed various detrimental impacts on environment,and the development of deNO_(x) catalysts with low-cost and high performance is an urgent requirement.Iron o...Excessive emissions of nitrogen oxides from flue gas have imposed various detrimental impacts on environment,and the development of deNO_(x) catalysts with low-cost and high performance is an urgent requirement.Iron oxide-based material has been explored for promising deNO_(x) catalysts.However,the unsatisfactory low-temperature activity limits their practical applications.In this study,a series of excellent low-temperature denitrification catalysts(Ha-FeO_(x)/yZS)were prepared by acid treatment of zinc slag,and the mass ratios of Fe to impure ions was regulated by adjusting the acid concentrations.Ha-FeO_(x)/yZS showed high denitrification performance(>90%)in the range of 180–300℃,and the optimal NO conversion and N2 selectivity were higher than 95%at 250℃.Among them,the Ha-FeO_(x)/2ZS synthesized with 2 mol/L HNO3 exhibited the widest temperature window(175–350℃).The excellent denitrification performance of Ha-FeO_(x)/yZS was mainly attributed to the strong interaction between Fe and impurity ions to inhibit the growth of crystals,making Ha-FeO_(x)/yZS with amorphous structure,nice fine particles,large specific surface area,more surface acid sites and high chemisorbed oxygen.The in-situ DRIFT experiments confirmed that the SCR reaction on the Ha-FeO_(x)/yZS followed both Langmuir-Hinshelwood(L-H)mechanism and Eley-Rideal(E-R)mechanism.The present work proposed a high value-added method for the preparation of cost-effective catalysts from zinc slag,which showed a promising application prospect in NO_(x) removal by selective catalytic reduction with ammonia.展开更多
Plasma-based NO_(x) synthesis has been considered as a sustainable alternative to the conventional HaberBosch process.Despite the advancements in research achieved in recent years,limited attention has been paid to th...Plasma-based NO_(x) synthesis has been considered as a sustainable alternative to the conventional HaberBosch process.Despite the advancements in research achieved in recent years,limited attention has been paid to the reversible dimerization reaction of NO_(2) to N_(2)O_(4).This reaction can significantly alter the parameters considered with the process’output,such as the concentration or volume fraction of products and the energy consumption.This work aims to investigate the significance of dimerization through theoretical analysis and experimentation.Experiments were conducted with a 2D-gliding arc reactor to evaluate the influence of dimerization in the case of plasma reactor operation.It was observed that the dimerization reaction reached equilibrium in microseconds,resulting in a maximum hypothetical NO_(2) equilibrium conversion of 48.8%.For plasma experiments,the dimerization could cause a maximum error of 14.1%in product detection,which needs to be carefully considered along with the influence of temperature variations on the measurement.展开更多
The radiant tube burner was modeled and analyzed by the numerical simulation method to investigate the influence factors and rules of NO_(x) emissions in a W-type radiant tube.These factors,which include air preheatin...The radiant tube burner was modeled and analyzed by the numerical simulation method to investigate the influence factors and rules of NO_(x) emissions in a W-type radiant tube.These factors,which include air preheating temperature,excess air coefficient,and fuel gas composition,were modified to study their effects on NO_(x) emissions under varying working conditions.Simulation results were compared with the theoretical calculation value based on chemical reaction equilibrium theory and the onsite experimental value to verify the simulation accuracy.The results show that NO_(x) emissions rise with increasing air preheating temperatures.NO_(x) production increases to an extreme value and then decreases during the oxygen-poor to oxygen-enriched process with the rise of the excess air coefficient.Enhancing the proportion of coke oven gas in the fuel gas raises the combustion temperature as well as the NO_(x) discharge.Both the thermal efficiency and NO_(x) emissions should be balanced.Therefore,the recommended values based on the simulation results are as follows:the air preheating temperature should not exceed 400℃,the excess air coefficient should be between 1.1 and 1.2,and the volume fraction of the coke oven gas should not exceed 30%.展开更多
锅炉燃烧优化在电厂锅炉经济稳定运行中起着重要作用,NO_(x)排放预测是其中的一个基本环节,因此提出了一种基于改进蜣螂优化算法优化卷积神经网络(convolutional neural network,CNN)与双向长短期记忆神经网络(long short term memory,L...锅炉燃烧优化在电厂锅炉经济稳定运行中起着重要作用,NO_(x)排放预测是其中的一个基本环节,因此提出了一种基于改进蜣螂优化算法优化卷积神经网络(convolutional neural network,CNN)与双向长短期记忆神经网络(long short term memory,LSTM)的组合模型超参数的超超临界锅炉NO_(x)排放预测的方法。首先通过Pearson相关性判定与NO_(x)排放相关的特征参数;其次建立CNN-LSTM预测模型,利用卷积神经网络CNN提取分层数据结构,长短期记忆网络挖掘长期依赖关系,然后结合佳点集、t分布变异策略对蜣螂算法进行改进,用改进后的算法对LSTM超参数进行优化得到最终预测模型;最后与其他神经网络模型进行对比验证。以某660 MW机组锅炉深度调峰实际数据进行预测,结果得到NO_(x)排放浓度实际值与预测值的平均绝对误差为3.3516,平均相对误差为2.4667,数据结果表明该预测模型具有更准确的预测效果。展开更多
基金supported by the National Natural Science Foundation of China(Grant No.51938014,Grant No.22176217,Grant No.22276215)the Fundamental Research Funds for the Central Universities and the Research Funds of Renmin University of China(No.22XNKJ28).
文摘The development of passive NO_(x)adsorbers with cost-benefit and high NO_(x)storage capacity remains an on-going challenge to after-treatment technologies at lower temperatures associated with cold-start NO_(x)emissions.Herein,Cs_(1)Mg_(3)Al catalyst prepared by sol-gel method was cyclic tested in NO_(x)storage under 5 vol%water.At 100°C,the NO_(x)storage capacity(1219 μmol g^(-1))was much higher than that of Pt/BaO/Al_(2)O_(3)(610 μmol g^(-1)).This provided new insights for non-noble metal catalysts in low-temperature passive NO_(x)adsorption.The addition of Cs improved the mobility of oxygen species and thus improved the NO_(x)storage capacity.The XRD,XPS,IR spectra and in situ DRIFTs with NH3 probe showed an interaction between CsO_(x)and AlO_(x)sites via oxygen species formed on Cs_(1)Mg_(3)Al catalyst.The improved mobility of oxygen species inferred from O2-TPD was consistent with high NO_(x)storage capacity related to enhanced formation of nitrate and additional nitrite species by NO_(x)oxidation.Moreover,the addition of Mg might improve the stability of Cs_(1)Mg_(3)Al by stabilizing surface active oxygen species in cyclic experiments.
基金supported by the National Natural Science Foundation of China(Grant Nos.U22A20184,52250077,and 52272080)the Jilin Province Natural Science Foundation of China(No.20220201093GX)+2 种基金the Fundamental Research Funds for the Central Universitiessupported by the National Research Foundation of Korea(2018R1A3B1052702 to JSK)the Starting growth Technological R&D Program(TIPS Program,No.S3201803,2021,MW)funded by the Ministry of SMEs and Startups(MSS,Korea).
文摘The rising flexible and intelligent electronics greatly facilitate the noninvasive and timely tracking of physiological information in telemedicine healthcare.Meticulously building bionic-sensitive moieties is vital for designing efficient electronic skin with advanced cognitive functionalities to pluralistically capture external stimuli.However,realistic mimesis,both in the skin’s three-dimensional interlocked hierarchical structures and synchronous encoding multistimuli information capacities,remains a challenging yet vital need for simplifying the design of flexible logic circuits.Herein,we construct an artificial epidermal device by in situ growing Cu_(3)(HHTP)_(2) particles onto the hollow spherical Ti_(3)C_(2)T_(x) surface,aiming to concurrently emulate the spinous and granular layers of the skin’s epidermis.The bionic Ti_(3)C_(2)T_(x)@Cu_(3)(HHTP)_(2) exhibits independent NO_(2) and pressure response,as well as novel functionalities such as acoustic signature perception and Morse code-encrypted message communication.Ultimately,a wearable alarming system with a mobile application terminal is self-developed by integrating the bimodular senor into flexible printed circuits.This system can assess risk factors related with asthmatic,such as stimulation of external NO_(2) gas,abnormal expiratory behavior and exertion degrees of fingers,achieving a recognition accuracy of 97.6%as assisted by a machine learning algorithm.Our work provides a feasible routine to develop intelligent multifunctional healthcare equipment for burgeoning transformative telemedicine diagnosis.
基金National Natural Science Foundation of China(21676209)Natural Science Basic Research Program of Shaanxi(2022JQ-328)Postdoctoral Research Foundation of the Xi’an University of Architecture and Technology(19603210120).
文摘Excessive emissions of nitrogen oxides from flue gas have imposed various detrimental impacts on environment,and the development of deNO_(x) catalysts with low-cost and high performance is an urgent requirement.Iron oxide-based material has been explored for promising deNO_(x) catalysts.However,the unsatisfactory low-temperature activity limits their practical applications.In this study,a series of excellent low-temperature denitrification catalysts(Ha-FeO_(x)/yZS)were prepared by acid treatment of zinc slag,and the mass ratios of Fe to impure ions was regulated by adjusting the acid concentrations.Ha-FeO_(x)/yZS showed high denitrification performance(>90%)in the range of 180–300℃,and the optimal NO conversion and N2 selectivity were higher than 95%at 250℃.Among them,the Ha-FeO_(x)/2ZS synthesized with 2 mol/L HNO3 exhibited the widest temperature window(175–350℃).The excellent denitrification performance of Ha-FeO_(x)/yZS was mainly attributed to the strong interaction between Fe and impurity ions to inhibit the growth of crystals,making Ha-FeO_(x)/yZS with amorphous structure,nice fine particles,large specific surface area,more surface acid sites and high chemisorbed oxygen.The in-situ DRIFT experiments confirmed that the SCR reaction on the Ha-FeO_(x)/yZS followed both Langmuir-Hinshelwood(L-H)mechanism and Eley-Rideal(E-R)mechanism.The present work proposed a high value-added method for the preparation of cost-effective catalysts from zinc slag,which showed a promising application prospect in NO_(x) removal by selective catalytic reduction with ammonia.
基金supported by the NOW’s Prescient project(16271)the LEAP-AGRI project AFRICA。
文摘Plasma-based NO_(x) synthesis has been considered as a sustainable alternative to the conventional HaberBosch process.Despite the advancements in research achieved in recent years,limited attention has been paid to the reversible dimerization reaction of NO_(2) to N_(2)O_(4).This reaction can significantly alter the parameters considered with the process’output,such as the concentration or volume fraction of products and the energy consumption.This work aims to investigate the significance of dimerization through theoretical analysis and experimentation.Experiments were conducted with a 2D-gliding arc reactor to evaluate the influence of dimerization in the case of plasma reactor operation.It was observed that the dimerization reaction reached equilibrium in microseconds,resulting in a maximum hypothetical NO_(2) equilibrium conversion of 48.8%.For plasma experiments,the dimerization could cause a maximum error of 14.1%in product detection,which needs to be carefully considered along with the influence of temperature variations on the measurement.
文摘The radiant tube burner was modeled and analyzed by the numerical simulation method to investigate the influence factors and rules of NO_(x) emissions in a W-type radiant tube.These factors,which include air preheating temperature,excess air coefficient,and fuel gas composition,were modified to study their effects on NO_(x) emissions under varying working conditions.Simulation results were compared with the theoretical calculation value based on chemical reaction equilibrium theory and the onsite experimental value to verify the simulation accuracy.The results show that NO_(x) emissions rise with increasing air preheating temperatures.NO_(x) production increases to an extreme value and then decreases during the oxygen-poor to oxygen-enriched process with the rise of the excess air coefficient.Enhancing the proportion of coke oven gas in the fuel gas raises the combustion temperature as well as the NO_(x) discharge.Both the thermal efficiency and NO_(x) emissions should be balanced.Therefore,the recommended values based on the simulation results are as follows:the air preheating temperature should not exceed 400℃,the excess air coefficient should be between 1.1 and 1.2,and the volume fraction of the coke oven gas should not exceed 30%.
文摘锅炉燃烧优化在电厂锅炉经济稳定运行中起着重要作用,NO_(x)排放预测是其中的一个基本环节,因此提出了一种基于改进蜣螂优化算法优化卷积神经网络(convolutional neural network,CNN)与双向长短期记忆神经网络(long short term memory,LSTM)的组合模型超参数的超超临界锅炉NO_(x)排放预测的方法。首先通过Pearson相关性判定与NO_(x)排放相关的特征参数;其次建立CNN-LSTM预测模型,利用卷积神经网络CNN提取分层数据结构,长短期记忆网络挖掘长期依赖关系,然后结合佳点集、t分布变异策略对蜣螂算法进行改进,用改进后的算法对LSTM超参数进行优化得到最终预测模型;最后与其他神经网络模型进行对比验证。以某660 MW机组锅炉深度调峰实际数据进行预测,结果得到NO_(x)排放浓度实际值与预测值的平均绝对误差为3.3516,平均相对误差为2.4667,数据结果表明该预测模型具有更准确的预测效果。
