In-situ experimental techniques have been widely applied to uncover the dynamic evolutions of both the structure of catalysts and the interfacial property of catalysis,thus serving as the most important means to gain ...In-situ experimental techniques have been widely applied to uncover the dynamic evolutions of both the structure of catalysts and the interfacial property of catalysis,thus serving as the most important means to gain molecular-level insights into the reaction mechanisms.In this mini review,we summarized recent progress in the applications of the interface-sensitive in-situ Raman and in-situ infrared(IR)spectroscopy towards CO_(2)electroreduction.Specifically,we concentrated on two aspects to clarify the role of both in-situ Raman and in-situ IR in revealing reaction mechanisms of CO_(2)electroreduction.The first one was the in-situ spectroscopy for detecting the active structures.The other one was the in-situ spectroscopy for capturing the reaction intermediates.As powerful guidance for the rational design of catalysts,the reaction mechanism was discussed in the specific examples.Finally,we try to predict the trends for the future development of in-situ spectroscopic techniques towards heterogeneous catalysis.展开更多
Discovering more and new geometrically frustrated systems remains an active point of inquiry in fundamental physics for the existence of unusual states of matter.Here,we report spin-liquid-like behavior in a two-dimen...Discovering more and new geometrically frustrated systems remains an active point of inquiry in fundamental physics for the existence of unusual states of matter.Here,we report spin-liquid-like behavior in a two-dimensional(2D)rhombic lattice Fe-metal-organic framework(Fe-MOF)with frustrated antiferromagnetism.This Fe-MOF exhibits a high frustration factor f=|θCW|/TN≥315,and its long-range magnetic order is suppressed down to 180 mK.Detailed theoretical calculations demonstrate strong antiferromagnetic coupling between adjacent Fe3+ions,indicating the potential of a classical spin-liquid-like behavior.Notably,a T-linear heat capacity parameter,γ,originating from electronic contributions and with magnetic field independence up to 8 T,can be observed in the specific heat capacity measurements at low-temperature,providing further proof for the spin-liquid-like behavior.This work highlights the potential of MOF materials in geometrically frustrated systems,and will promote the research of exotic quantum physics phenomena.展开更多
Traffic flow prediction plays an important role in intelligent transportation applications,such as traffic control,navigation,path planning,etc.,which are closely related to people's daily life.In the last twenty ...Traffic flow prediction plays an important role in intelligent transportation applications,such as traffic control,navigation,path planning,etc.,which are closely related to people's daily life.In the last twenty years,many traffic flow prediction approaches have been proposed.However,some of these approaches use the regression based mechanisms,which cannot achieve accurate short-term traffic flow predication.While,other approaches use the neural network based mechanisms,which cannot work well with limited amount of training data.To this end,a light weight tensor-based traffic flow prediction approach is proposed,which can achieve efficient and accurate short-term traffic flow prediction with continuous traffic flow data in a limited period of time.In the proposed approach,first,a tensor-based traffic flow model is proposed to establish the multi-dimensional relationships for traffic flow values in continuous time intervals.Then,a CANDECOMP/PARAFAC decomposition based algorithm is employed to complete the missing values in the constructed tensor.Finally,the completed tensor can be directly used to achieve efficient and accurate traffic flow prediction.The experiments on the real dataset indicate that the proposed approach outperforms many current approaches on traffic flow prediction with limited amount of traffic flow data.展开更多
As one of the key technologies of intelligent transportation systems, short-term traffic volume prediction plays an increasingly important role in solving urban traffic problems. In the last decade, many approaches we...As one of the key technologies of intelligent transportation systems, short-term traffic volume prediction plays an increasingly important role in solving urban traffic problems. In the last decade, many approaches were proposed for the traffic volume prediction from different perspectives. However, most of these approaches are based on a large amount of historical data. When there are only finite collected traffic data, they cannot be well trained, so the prediction accuracy of these approaches will be poor. In this paper, a tensor model is proposed to capture the change patterns of continuous traffic volumes. From collected traffic volume data, the element data are extracted to update the corresponding elements of the tensor model. Then, a tucker decomposition and gradient descent based algorithm is employed to impute the missing elements of the tensor model. After missing element imputation, the tensor model can be directly applied to the short-term traffic volume prediction through searching the corresponding elements of the model and the storage cost of the model is low. Our model is evaluated on real traffic volume data from PeMS dataset, which indicates that our model has higher traffic volume prediction accuracy than other approaches in the situation of finite traffic volume data.展开更多
High-rate CO_(2)-to-CH_(4)photoreduction with high selectivity is highly attractive,which is a win-win strategy for mitigating the greenhouse effect and the energy crisis.However,the poor photocatalytic activity and l...High-rate CO_(2)-to-CH_(4)photoreduction with high selectivity is highly attractive,which is a win-win strategy for mitigating the greenhouse effect and the energy crisis.However,the poor photocatalytic activity and low product selectivity hinder the practical application.To precisely tailor the product selectivity and realize high-rate CO_(2)photoreduction,we design atomically precise Pd species supported on In_(2)O_(3)nanosheets.Taking the synthetic 1.30Pd/In_(2)O_(3)nanosheets as an example,the aberration-correction high-angle annular dark-field scanning transmission electron microscopy image displayed the Pd species atomically dispersed on the In_(2)O_(3)nanosheets.Raman spectra and X-ray photoelectron spectra established that the strong interaction between the Pd species and the In_(2)O_(3)substrate drove electron transfer from In to Pd species,resulting in electron-enriched Pd sites for CO_(2)activation.Synchrotronradiation photoemission spectroscopy demonstrated that the Pd species can tailor the conduction band edge of In_(2)O_(3)nanosheets to match the CO_(2)-to-CH_(4)pathway,instead of the CO_(2)-to-CO pathway,which theoretically accounts for the high CH_(4)selectivity.Moreover,in situ X-ray photoelectron spectroscopy unveiled that the catalytically active sites had a change from In species to Pd species over the 1.30Pd/In_(2)O_(3)nanosheets.In situ FTIR and EPR spectra reveal the atomically precise Pd species with rich electrons prefer to adsorb the electrophilic protons for accelerating the*COOH intermediates hydrogenation into CH_(4).Consequently,the 1.30Pd/In_(2)O_(3)nanosheets reached CO_(2)-to-CH_(4)photoconversion with 100%selectivity and 81.2μmol g^(−1)h^(−1)productivity.展开更多
基金supported by the National Natural Science Foundation of China(22322901 and 22209163)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB0450401)+2 种基金the CAS Project for Young Scientists in Basic Research(YSBR-022)the National Key Research and Development Program of China(2022YFC2106000)the USTC Research Funds of the Double First-Class Initiative。
文摘In-situ experimental techniques have been widely applied to uncover the dynamic evolutions of both the structure of catalysts and the interfacial property of catalysis,thus serving as the most important means to gain molecular-level insights into the reaction mechanisms.In this mini review,we summarized recent progress in the applications of the interface-sensitive in-situ Raman and in-situ infrared(IR)spectroscopy towards CO_(2)electroreduction.Specifically,we concentrated on two aspects to clarify the role of both in-situ Raman and in-situ IR in revealing reaction mechanisms of CO_(2)electroreduction.The first one was the in-situ spectroscopy for detecting the active structures.The other one was the in-situ spectroscopy for capturing the reaction intermediates.As powerful guidance for the rational design of catalysts,the reaction mechanism was discussed in the specific examples.Finally,we try to predict the trends for the future development of in-situ spectroscopic techniques towards heterogeneous catalysis.
基金supported by the National Key Research and Development Program of China(No.2021YFA1600800)the National Natural Science Foundation of China(Nos.11975234,12075243,12005227,12105286,121350122,U2032150,12275271,12205305,and U1932211)+5 种基金the Natural Science Foundation of Anhui Province(Nos.2208085QA14 and 2208085J13)the Users with Excellence Program of Hefei Science Center CAS(Nos.2020HSC-UE002,2020HSC-CIP013,2021HSC-UE002,and 2021HSC-UE003)the Major science and technology project of Anhui Province(No.202103a05020025)the Key Program of Research and Development of Hefei Science Center,CAS(Nos.2021HSC-KPRD002 and 2021HSC-KPRD003)the Fundamental Research Funds for the Central Universities(No.WK 2310000103)partially carried out at the USTC Center for Micro and Nanoscale Research and Fabrication.
文摘Discovering more and new geometrically frustrated systems remains an active point of inquiry in fundamental physics for the existence of unusual states of matter.Here,we report spin-liquid-like behavior in a two-dimensional(2D)rhombic lattice Fe-metal-organic framework(Fe-MOF)with frustrated antiferromagnetism.This Fe-MOF exhibits a high frustration factor f=|θCW|/TN≥315,and its long-range magnetic order is suppressed down to 180 mK.Detailed theoretical calculations demonstrate strong antiferromagnetic coupling between adjacent Fe3+ions,indicating the potential of a classical spin-liquid-like behavior.Notably,a T-linear heat capacity parameter,γ,originating from electronic contributions and with magnetic field independence up to 8 T,can be observed in the specific heat capacity measurements at low-temperature,providing further proof for the spin-liquid-like behavior.This work highlights the potential of MOF materials in geometrically frustrated systems,and will promote the research of exotic quantum physics phenomena.
基金supported by the Beijing Natural Science Foundation under Nos.4192004 and 4212016the National Natural Science Foundation of China under Grant Nos.61703013 and 62072016+3 种基金the Project of Beijing Municipal Education Commission under Grant Nos.KM201810005024 and KM201810005023Foundation from School of Computer Science and Technology,Beijing University of Technology under Grants No.2020JSJKY005the International Research Cooperation Seed Fund of Beijing University of Technology under Grant No.2021B29National Engineering Laboratory for Industrial Big-data Application Technology.
文摘Traffic flow prediction plays an important role in intelligent transportation applications,such as traffic control,navigation,path planning,etc.,which are closely related to people's daily life.In the last twenty years,many traffic flow prediction approaches have been proposed.However,some of these approaches use the regression based mechanisms,which cannot achieve accurate short-term traffic flow predication.While,other approaches use the neural network based mechanisms,which cannot work well with limited amount of training data.To this end,a light weight tensor-based traffic flow prediction approach is proposed,which can achieve efficient and accurate short-term traffic flow prediction with continuous traffic flow data in a limited period of time.In the proposed approach,first,a tensor-based traffic flow model is proposed to establish the multi-dimensional relationships for traffic flow values in continuous time intervals.Then,a CANDECOMP/PARAFAC decomposition based algorithm is employed to complete the missing values in the constructed tensor.Finally,the completed tensor can be directly used to achieve efficient and accurate traffic flow prediction.The experiments on the real dataset indicate that the proposed approach outperforms many current approaches on traffic flow prediction with limited amount of traffic flow data.
基金supported by the National Natural Science Foundation of China(No.62276011,62072016)the Natural Science Foundation of Beijing Municipality(No.4212016)Urban Carbon Neutral Science and Technology Innovation Fund Project of Beijing University of Technology(No.040000514122608).
文摘As one of the key technologies of intelligent transportation systems, short-term traffic volume prediction plays an increasingly important role in solving urban traffic problems. In the last decade, many approaches were proposed for the traffic volume prediction from different perspectives. However, most of these approaches are based on a large amount of historical data. When there are only finite collected traffic data, they cannot be well trained, so the prediction accuracy of these approaches will be poor. In this paper, a tensor model is proposed to capture the change patterns of continuous traffic volumes. From collected traffic volume data, the element data are extracted to update the corresponding elements of the tensor model. Then, a tucker decomposition and gradient descent based algorithm is employed to impute the missing elements of the tensor model. After missing element imputation, the tensor model can be directly applied to the short-term traffic volume prediction through searching the corresponding elements of the model and the storage cost of the model is low. Our model is evaluated on real traffic volume data from PeMS dataset, which indicates that our model has higher traffic volume prediction accuracy than other approaches in the situation of finite traffic volume data.
基金the National Key R&D Program of China(2022YFA1502904,2019YFA0210004,2021YFA1501502)National Natural Science Foundation of China(22125503,21975242,U2032212,21890754)+1 种基金Youth Innovation Promotion Association of CAS(CX2340007003)Technical Talent Promotion Plan(TS2021002).
文摘High-rate CO_(2)-to-CH_(4)photoreduction with high selectivity is highly attractive,which is a win-win strategy for mitigating the greenhouse effect and the energy crisis.However,the poor photocatalytic activity and low product selectivity hinder the practical application.To precisely tailor the product selectivity and realize high-rate CO_(2)photoreduction,we design atomically precise Pd species supported on In_(2)O_(3)nanosheets.Taking the synthetic 1.30Pd/In_(2)O_(3)nanosheets as an example,the aberration-correction high-angle annular dark-field scanning transmission electron microscopy image displayed the Pd species atomically dispersed on the In_(2)O_(3)nanosheets.Raman spectra and X-ray photoelectron spectra established that the strong interaction between the Pd species and the In_(2)O_(3)substrate drove electron transfer from In to Pd species,resulting in electron-enriched Pd sites for CO_(2)activation.Synchrotronradiation photoemission spectroscopy demonstrated that the Pd species can tailor the conduction band edge of In_(2)O_(3)nanosheets to match the CO_(2)-to-CH_(4)pathway,instead of the CO_(2)-to-CO pathway,which theoretically accounts for the high CH_(4)selectivity.Moreover,in situ X-ray photoelectron spectroscopy unveiled that the catalytically active sites had a change from In species to Pd species over the 1.30Pd/In_(2)O_(3)nanosheets.In situ FTIR and EPR spectra reveal the atomically precise Pd species with rich electrons prefer to adsorb the electrophilic protons for accelerating the*COOH intermediates hydrogenation into CH_(4).Consequently,the 1.30Pd/In_(2)O_(3)nanosheets reached CO_(2)-to-CH_(4)photoconversion with 100%selectivity and 81.2μmol g^(−1)h^(−1)productivity.
