Currently, land resources are becoming more and more constrained and structures are getting closer to each other. To investigate the seismic response of inter-story isolated structure to adjacent structure, models con...Currently, land resources are becoming more and more constrained and structures are getting closer to each other. To investigate the seismic response of inter-story isolated structure to adjacent structure, models considering no soil-structure interaction (SSI), considering soil-structure interaction (SSI), and considering structure-soil-structure interaction (SSSI) were established. Nonlinear seismic response comparative analysis was conducted by varying the spacing between adjacent structure and inter-story isolated structure, as well as the weight of adjacent structure, under different earthquake inputs, in order to obtain the structural response characteristics. The results indicate that the inter-story drift and inter-story shear of the inter-story isolated structure without considering SSI are smaller than those considering SSI and SSSI. The inter-story drift and inter-story shear of the inter-story isolated structure considering SSSI are further affected compared to that of the inter-story isolated structure considering only SSI. As the spacing between adjacent structure and inter-story isolated structure increases, the influence of adjacent structure on inter-story isolated structure decreases. The variation in the spacing between the two structures has a negligible effect on the isolation layer of the inter-story isolated structure. With the increase in the weight of adjacent structure, the influence of adjacent structure on inter-story isolated structure becomes more significant. The increasing weight of adjacent structure has an increasing effect on the Isolation layer of the inter-story isolated structure.展开更多
The one-step conversion of ethanol to 1,3-butadiene has achieved a breakthrough with the development of beta zeolite supported dual metal catalysts.However,the reaction mechanism from ethanol to butadiene is complex a...The one-step conversion of ethanol to 1,3-butadiene has achieved a breakthrough with the development of beta zeolite supported dual metal catalysts.However,the reaction mechanism from ethanol to butadiene is complex and has not yet been fully elucidated,and no catalyst screening effort has been done based on central metal atoms.In this work,density functional theory(DFT)calculations were employed to study the mechanism of one-step conversion of ethanol to butadiene over ZnY/BEA catalyst.The results show that ethanol dehydrogenation prefers to proceed on Zn site with a reaction energy of 0.77 eV in the rate-determining step,and the aldol condensation to produce butadiene prefers to proceed on Y site with a reaction energy of 0.69 eV in the rate-determining step.Based on the mechanism revealed,six elements were selected to replace Y for screening superior combination of Zn-M/BEA(M=Sn,Nb,Ta,Hf,Zr,Ti;BEA:beta polymorph A)for this reaction.As a result,Zn-Y/BEA(0.69 eV)is proven to be the most preferring catalyst compared with the other six ones,and Zn-Zr/BEA(0.85 eV),Zn-Ti/BEA(0.87 eV),and Zn-Sn/BEA(0.93 eV)can be potential candidates for the conversion of ethanol to butadiene.This work not only provides mechanistic insights into one-step catalytic conversion of ethanol to butadiene over Zn-Y/BEA catalyst but also offers more promising catalyst candidates for this reaction.展开更多
In this paper, we propose a new online system that can quickly detect malicious spam emails and adapt to the changes in the email contents and the Uniform Resource Locator (URL) links leading to malicious websites by ...In this paper, we propose a new online system that can quickly detect malicious spam emails and adapt to the changes in the email contents and the Uniform Resource Locator (URL) links leading to malicious websites by updating the system daily. We introduce an autonomous function for a server to generate training examples, in which double-bounce emails are automatically collected and their class labels are given by a crawler-type software to analyze the website maliciousness called SPIKE. In general, since spammers use botnets to spread numerous malicious emails within a short time, such distributed spam emails often have the same or similar contents. Therefore, it is not necessary for all spam emails to be learned. To adapt to new malicious campaigns quickly, only new types of spam emails should be selected for learning and this can be realized by introducing an active learning scheme into a classifier model. For this purpose, we adopt Resource Allocating Network with Locality Sensitive Hashing (RAN-LSH) as a classifier model with a data selection function. In RAN-LSH, the same or similar spam emails that have already been learned are quickly searched for a hash table in Locally Sensitive Hashing (LSH), in which the matched similar emails located in “well-learned” are discarded without being used as training data. To analyze email contents, we adopt the Bag of Words (BoW) approach and generate feature vectors whose attributes are transformed based on the normalized term frequency-inverse document frequency (TF-IDF). We use a data set of double-bounce spam emails collected at National Institute of Information and Communications Technology (NICT) in Japan from March 1st, 2013 until May 10th, 2013 to evaluate the performance of the proposed system. The results confirm that the proposed spam email detection system has capability of detecting with high detection rate.展开更多
One-step conversion of methane and formaldehyde into ethanol is a 100% atom-efficient process for carbon resources utilization and environment protection but still faces eminent challenges due to the lacking of effici...One-step conversion of methane and formaldehyde into ethanol is a 100% atom-efficient process for carbon resources utilization and environment protection but still faces eminent challenges due to the lacking of efficient catalysts. Therefore, developing active and stable catalysts is crucial for the co-conversion of methane and formaldehyde. Herein, twelve kinds of “Single-Atom”-“Frustrated Lewis Pair”(SA-FLP)dual-active-site catalysts are designed for the direct conversion of methane and formaldehyde to ethanol based on density functional theory(DFT) calculations and microkinetic simulations. The results show that the SA-FLP dual active sites can simultaneously activate methane at the SA site and activate formaldehyde at the FLP site. Among the twelve designed SA-FLP catalysts, Fe1-FLP shows the best performance in the co-conversion of methane and formaldehyde to ethanol with the rate-determining barrier of 1.15 e V.Ethanol is proved as the main product with the turnover frequency of 1.32 × 10^(-4)s^(-1)at 573 K and 3 bar.This work provides a universal strategy to design dual active sites on metal oxide materials and offers new insights into the effective conversion of methane and formaldehyde to desired C_(2) chemicals.展开更多
Olefin hydrogenation under mild condition is crucial and challenging for industrial applications. Herein, defective UiO-66(Ce) was constructed by using cyanuric acid as the molecular etching “scissors” and further t...Olefin hydrogenation under mild condition is crucial and challenging for industrial applications. Herein, defective UiO-66(Ce) was constructed by using cyanuric acid as the molecular etching “scissors” and further to synthesize heterogeneous catalyst with highly dispersed RuNi nanoparticles (Ru1Ni1.5@UiO-66(Ce)-12 h). The construction of Ce-O-Ru/Ni heterogeneous interfaces and Ni–Ru bonds provide electron transfer channels from Ce-oxo clusters and Ni species to Ru species. Furthermore, the microenvironment and electronic structure of Ru0 active sites were synergistically regulated by adjusting the content of metal-organic frameworks (MOFs) defects and Ni promoter, thereby enhancing the adsorption and activation ability of H–H and C=C bonds. Therefore, Ru1Ni1.5@UiO-66(Ce)-12 h achieved dicyclopentadiene saturated hydrogenation (100% conversion) to tetrahydrodicyclopentadiene (∼ 100% selectivity) under mild condition (35℃, 1 MPa) with only 25 min. Meanwhile, the sample exhibited excellent structural stability after 6 cycles test. This study provides a promising strategy for the rational design of remarkable noble metal-based catalysts for practical applications.展开更多
Metal-organic frameworks(MOFs),renowned for structural diversity and design flexibility,exhibit potential in catalysis.However,the pursuit of higher catalytic activity through defects often compromises stability,requi...Metal-organic frameworks(MOFs),renowned for structural diversity and design flexibility,exhibit potential in catalysis.However,the pursuit of higher catalytic activity through defects often compromises stability,requiring a delicate balance.Traditional trial-and-error method for optimizing synthesis parameters within the complex chemical space is inefficient.Herein,taking the typical MOF UiO-66(Ce)as an illustrative example,a closed loop workflow is built,which integrates ma-chine learning(ML)-assissted prediction,multi-objective optimization(MOO)and experimental preparation to synergistically optimize the defect content and thermal stability of UiO-66(Ce)for efficient hydrogenation of dicyclopentadiene(DCPD).An automatic data extraction program ensures data accuracy,establishing a high-quality database.ML is employed to explore the intricate synthesis-structure-property correlations,enabling precise delineation of pure-phase subspace and accurate predictions of properties.After two iterations,MOO model identifies optimal protocols for high defect content(>40%)and thermal stability(>300℃).The optimized UiO-66(Ce)exhibits superior catalytic performance in hydroge-nation of DCPD,validating the precision and reliability of our methodology.This ML-assisted approach offers a valuable paradigm for solving the trade-off riddle in materials field.展开更多
基金supported by the National Natural Science Foundation of China(No.22038011,No.22078257,No.22108213,No.52176142)the China Postdoctoral Science Foundation(2021M692548)+1 种基金the Joint Fund of the Yulin University and the Dalian National Laboratory for Clean Energy(Grant YLU-DNL Fund 2022001)the Young Talent Support Plan of Shaanxi Province。
文摘Currently, land resources are becoming more and more constrained and structures are getting closer to each other. To investigate the seismic response of inter-story isolated structure to adjacent structure, models considering no soil-structure interaction (SSI), considering soil-structure interaction (SSI), and considering structure-soil-structure interaction (SSSI) were established. Nonlinear seismic response comparative analysis was conducted by varying the spacing between adjacent structure and inter-story isolated structure, as well as the weight of adjacent structure, under different earthquake inputs, in order to obtain the structural response characteristics. The results indicate that the inter-story drift and inter-story shear of the inter-story isolated structure without considering SSI are smaller than those considering SSI and SSSI. The inter-story drift and inter-story shear of the inter-story isolated structure considering SSSI are further affected compared to that of the inter-story isolated structure considering only SSI. As the spacing between adjacent structure and inter-story isolated structure increases, the influence of adjacent structure on inter-story isolated structure decreases. The variation in the spacing between the two structures has a negligible effect on the isolation layer of the inter-story isolated structure. With the increase in the weight of adjacent structure, the influence of adjacent structure on inter-story isolated structure becomes more significant. The increasing weight of adjacent structure has an increasing effect on the Isolation layer of the inter-story isolated structure.
基金This work was supported by the National Natural Science Foundation of China(No.22078257,No.22038011,and No.22108213)the National Key R&D Program of China(No.2020YFA0710000)+1 种基金the China Postdoctoral Science Foundation(No.2018T111034 and No.2021M692548)the Rising Star Program in Science and Technology of Shaanxi Province(No.2020KJXX-079).Chun-Ran Chang also acknowledges the support from the K.C.Wong Education Foundation.The calculations were performed by using the HPC Platform at Xi’an Jiaotong University。
文摘The one-step conversion of ethanol to 1,3-butadiene has achieved a breakthrough with the development of beta zeolite supported dual metal catalysts.However,the reaction mechanism from ethanol to butadiene is complex and has not yet been fully elucidated,and no catalyst screening effort has been done based on central metal atoms.In this work,density functional theory(DFT)calculations were employed to study the mechanism of one-step conversion of ethanol to butadiene over ZnY/BEA catalyst.The results show that ethanol dehydrogenation prefers to proceed on Zn site with a reaction energy of 0.77 eV in the rate-determining step,and the aldol condensation to produce butadiene prefers to proceed on Y site with a reaction energy of 0.69 eV in the rate-determining step.Based on the mechanism revealed,six elements were selected to replace Y for screening superior combination of Zn-M/BEA(M=Sn,Nb,Ta,Hf,Zr,Ti;BEA:beta polymorph A)for this reaction.As a result,Zn-Y/BEA(0.69 eV)is proven to be the most preferring catalyst compared with the other six ones,and Zn-Zr/BEA(0.85 eV),Zn-Ti/BEA(0.87 eV),and Zn-Sn/BEA(0.93 eV)can be potential candidates for the conversion of ethanol to butadiene.This work not only provides mechanistic insights into one-step catalytic conversion of ethanol to butadiene over Zn-Y/BEA catalyst but also offers more promising catalyst candidates for this reaction.
文摘In this paper, we propose a new online system that can quickly detect malicious spam emails and adapt to the changes in the email contents and the Uniform Resource Locator (URL) links leading to malicious websites by updating the system daily. We introduce an autonomous function for a server to generate training examples, in which double-bounce emails are automatically collected and their class labels are given by a crawler-type software to analyze the website maliciousness called SPIKE. In general, since spammers use botnets to spread numerous malicious emails within a short time, such distributed spam emails often have the same or similar contents. Therefore, it is not necessary for all spam emails to be learned. To adapt to new malicious campaigns quickly, only new types of spam emails should be selected for learning and this can be realized by introducing an active learning scheme into a classifier model. For this purpose, we adopt Resource Allocating Network with Locality Sensitive Hashing (RAN-LSH) as a classifier model with a data selection function. In RAN-LSH, the same or similar spam emails that have already been learned are quickly searched for a hash table in Locally Sensitive Hashing (LSH), in which the matched similar emails located in “well-learned” are discarded without being used as training data. To analyze email contents, we adopt the Bag of Words (BoW) approach and generate feature vectors whose attributes are transformed based on the normalized term frequency-inverse document frequency (TF-IDF). We use a data set of double-bounce spam emails collected at National Institute of Information and Communications Technology (NICT) in Japan from March 1st, 2013 until May 10th, 2013 to evaluate the performance of the proposed system. The results confirm that the proposed spam email detection system has capability of detecting with high detection rate.
基金supported by the National Natural Science Foundation of China (Nos.22078257, 22038011 and 22108213)the China Postdoctoral Science Foundation (No.2021M692548)+1 种基金the Joint Fund of the Yulin University and the Dalian National Laboratory for Clean Energy (YLU-DNL Fund No.2022001)the Young Talent Support Plan of Shaanxi Province。
文摘One-step conversion of methane and formaldehyde into ethanol is a 100% atom-efficient process for carbon resources utilization and environment protection but still faces eminent challenges due to the lacking of efficient catalysts. Therefore, developing active and stable catalysts is crucial for the co-conversion of methane and formaldehyde. Herein, twelve kinds of “Single-Atom”-“Frustrated Lewis Pair”(SA-FLP)dual-active-site catalysts are designed for the direct conversion of methane and formaldehyde to ethanol based on density functional theory(DFT) calculations and microkinetic simulations. The results show that the SA-FLP dual active sites can simultaneously activate methane at the SA site and activate formaldehyde at the FLP site. Among the twelve designed SA-FLP catalysts, Fe1-FLP shows the best performance in the co-conversion of methane and formaldehyde to ethanol with the rate-determining barrier of 1.15 e V.Ethanol is proved as the main product with the turnover frequency of 1.32 × 10^(-4)s^(-1)at 573 K and 3 bar.This work provides a universal strategy to design dual active sites on metal oxide materials and offers new insights into the effective conversion of methane and formaldehyde to desired C_(2) chemicals.
基金supported by the National Key Research and Development Program of China(No.2021YFB3500700)the National Natural Science Foundation of China(No.51972024)the Natural Science Foundation of Guangdong Province(No.2022A1515010185).
文摘Olefin hydrogenation under mild condition is crucial and challenging for industrial applications. Herein, defective UiO-66(Ce) was constructed by using cyanuric acid as the molecular etching “scissors” and further to synthesize heterogeneous catalyst with highly dispersed RuNi nanoparticles (Ru1Ni1.5@UiO-66(Ce)-12 h). The construction of Ce-O-Ru/Ni heterogeneous interfaces and Ni–Ru bonds provide electron transfer channels from Ce-oxo clusters and Ni species to Ru species. Furthermore, the microenvironment and electronic structure of Ru0 active sites were synergistically regulated by adjusting the content of metal-organic frameworks (MOFs) defects and Ni promoter, thereby enhancing the adsorption and activation ability of H–H and C=C bonds. Therefore, Ru1Ni1.5@UiO-66(Ce)-12 h achieved dicyclopentadiene saturated hydrogenation (100% conversion) to tetrahydrodicyclopentadiene (∼ 100% selectivity) under mild condition (35℃, 1 MPa) with only 25 min. Meanwhile, the sample exhibited excellent structural stability after 6 cycles test. This study provides a promising strategy for the rational design of remarkable noble metal-based catalysts for practical applications.
基金supported by the National Key R&D Program of China(Grant No.2021YFB3500700)Beijing Natural Science Foundation(Grant No.L233011)Guangdong Basic and Applied Basic Research Foundation(Grant No.2022A1515010185).
文摘Metal-organic frameworks(MOFs),renowned for structural diversity and design flexibility,exhibit potential in catalysis.However,the pursuit of higher catalytic activity through defects often compromises stability,requiring a delicate balance.Traditional trial-and-error method for optimizing synthesis parameters within the complex chemical space is inefficient.Herein,taking the typical MOF UiO-66(Ce)as an illustrative example,a closed loop workflow is built,which integrates ma-chine learning(ML)-assissted prediction,multi-objective optimization(MOO)and experimental preparation to synergistically optimize the defect content and thermal stability of UiO-66(Ce)for efficient hydrogenation of dicyclopentadiene(DCPD).An automatic data extraction program ensures data accuracy,establishing a high-quality database.ML is employed to explore the intricate synthesis-structure-property correlations,enabling precise delineation of pure-phase subspace and accurate predictions of properties.After two iterations,MOO model identifies optimal protocols for high defect content(>40%)and thermal stability(>300℃).The optimized UiO-66(Ce)exhibits superior catalytic performance in hydroge-nation of DCPD,validating the precision and reliability of our methodology.This ML-assisted approach offers a valuable paradigm for solving the trade-off riddle in materials field.
