A recently discovered family of kagome lattice materials,AV_(3)Sb_(5)(A=K,Rb,Cs),has attracted great interest,especiallyin the debate over their dominant superconducting pairing symmetry.To explore this issue,we study...A recently discovered family of kagome lattice materials,AV_(3)Sb_(5)(A=K,Rb,Cs),has attracted great interest,especiallyin the debate over their dominant superconducting pairing symmetry.To explore this issue,we study the superconductingpairing behavior within the kagome-lattice Hubbard model through the constrained path Monte Carlo method.It isfound that doping around the Dirac point generates a dominant next-nearest-neighbor-d pairing symmetry driven by on-siteCoulomb interaction U.However,when considering the nearest-neighbor interaction V,it may induce nearest-neighbor-ppairing to become the preferred pairing symmetry.Our results provide useful information to identify the dominant superconductingpairing symmetry in the AV_(3)Sb_(5)family.展开更多
The fraudulent website image is a vital information carrier for telecom fraud.The efficient and precise recognition of fraudulent website images is critical to combating and dealing with fraudulent websites.Current re...The fraudulent website image is a vital information carrier for telecom fraud.The efficient and precise recognition of fraudulent website images is critical to combating and dealing with fraudulent websites.Current research on image recognition of fraudulent websites is mainly carried out at the level of image feature extraction and similarity study,which have such disadvantages as difficulty in obtaining image data,insufficient image analysis,and single identification types.This study develops a model based on the entropy method for image leader decision and Inception-v3 transfer learning to address these disadvantages.The data processing part of the model uses a breadth search crawler to capture the image data.Then,the information in the images is evaluated with the entropy method,image weights are assigned,and the image leader is selected.In model training and prediction,the transfer learning of the Inception-v3 model is introduced into image recognition of fraudulent websites.Using selected image leaders to train the model,multiple types of fraudulent websites are identified with high accuracy.The experiment proves that this model has a superior accuracy in recognizing images on fraudulent websites compared to other current models.展开更多
This comprehensive review provides a deep exploration of the unique roles of single atom catalysts(SACs)in photocatalytic hydrogen peroxide(H_(2)O_(2))production.SACs offer multiple benefits over traditional catalysts...This comprehensive review provides a deep exploration of the unique roles of single atom catalysts(SACs)in photocatalytic hydrogen peroxide(H_(2)O_(2))production.SACs offer multiple benefits over traditional catalysts such as improved efficiency,selectivity,and flexibility due to their distinct electronic structure and unique properties.The review discusses the critical elements in the design of SACs,including the choice of metal atom,host material,and coordination environment,and how these elements impact the catalytic activity.The role of single atoms in photocatalytic H_(2)O_(2)production is also analysed,focusing on enhancing light absorption and charge generation,improving the migration and separation of charge carriers,and lowering the energy barrier of adsorption and activation of reactants.Despite these advantages,several challenges,including H_(2)O_(2)decomposition,stability of SACs,unclear mechanism,and low selectivity,need to be overcome.Looking towards the future,the review suggests promising research directions such as direct utilization of H_(2)O_(2),high-throughput synthesis and screening,the creation of dual active sites,and employing density functional theory for investigating the mechanisms of SACs in H_(2)O_(2)photosynthesis.This review provides valuable insights into the potential of single atom catalysts for advancing the field of photocatalytic H_(2)O_(2)production.展开更多
High-order quantum coherence reveals the statistical correlation of quantum particles. Manipulation of quantum coherence of light in the temporal domain enables the production of the single-photon source, which has be...High-order quantum coherence reveals the statistical correlation of quantum particles. Manipulation of quantum coherence of light in the temporal domain enables the production of the single-photon source, which has become one of the most important quantum resources. High-order quantum coherence in the spatial domain plays a crucial role in a variety of applications, such as quantum imaging, holography, and microscopy. However, the active control of second-order spatial quantum coherence remains a challenging task. Here we predict theoretically and demonstrate experimentally the first active manipulation of second-order spatial quantum coherence,which exhibits the capability of switching between bunching and anti-bunching, by mapping the entanglement of spatially structured photons. We also show that signal processing based on quantum coherence exhibits robust resistance to intensity disturbance. Our findings not only enhance existing applications but also pave the way for broader utilization of higher-order spatial quantum coherence.展开更多
Coal burst is a severe hazard that can result in fatalities and damage of facilities in underground coal mines.To address this issue,a robust unascertained combination model is proposed to study the coal burst hazard ...Coal burst is a severe hazard that can result in fatalities and damage of facilities in underground coal mines.To address this issue,a robust unascertained combination model is proposed to study the coal burst hazard based on an updated database.Four assessment indexes are used in the model,which are the dynamic failure duration(DT),elastic energy index(WET),impact energy index(KE)and uniaxial compressive strength(RC).Four membership functions,including linear(L),parabolic(P),S and Weibull(W)functions,are proposed to measure the uncertainty level of individual index.The corresponding weights are determined through information entropy(EN),analysis hierarchy process(AHP)and synthetic weights(CW).Simultaneously,the classification criteria,including unascertained cluster(UC)and credible identification principle(CIP),are analyzed.The combination algorithm,consisting of P function,CW and CIP(P-CW-CIP),is selected as the optimal classification model in function of theory analysis and to train the samples.Ultimately,the established ensemble model is further validated through test samples with 100%accuracy.The results reveal that the hybrid model has a great potential in the coal burst hazard evaluation in underground coal mines.展开更多
Amine-silica composite materials for post-combustion COcapture have attracted considerable attention because of their high COuptake at low COconcentrations, excellent COcapture selectivity in the presence of moisture,...Amine-silica composite materials for post-combustion COcapture have attracted considerable attention because of their high COuptake at low COconcentrations, excellent COcapture selectivity in the presence of moisture, and lower energy requirements for sorbent regeneration. This review discusses the recent advances in amine-silica composites for COcapture, including adsorbent preparation and characterization, COcapture under dry and moisture conditions at different COpartial pressures, sorbent regeneration, and stability after many cyclic sorption-desorption runs.展开更多
A large database is desired for machine learning(ML) technology to make accurate predictions of materials physicochemical properties based on their molecular structure.When a large database is not available,the develo...A large database is desired for machine learning(ML) technology to make accurate predictions of materials physicochemical properties based on their molecular structure.When a large database is not available,the development of proper featurization method based on physicochemical nature of target proprieties can improve the predictive power of ML models with a smaller database.In this work,we show that two new featurization methods,volume occupation spatial matrix and heat contribution spatial matrix,can improve the accuracy in predicting energetic materials' crystal density(ρ_(crystal)) and solid phase enthalpy of formation(H_(f,solid)) using a database containing 451 energetic molecules.Their mean absolute errors are reduced from 0.048 g/cm~3 and 24.67 kcal/mol to 0.035 g/cm~3 and 9.66 kcal/mol,respectively.By leave-one-out-cross-validation,the newly developed ML models can be used to determine the performance of most kinds of energetic materials except cubanes.Our ML models are applied to predict ρ_(crystal) and H_(f,solid) of CHON-based molecules of the 150 million sized PubChem database,and screened out 56 candidates with competitive detonation performance and reasonable chemical structures.With further improvement in future,spatial matrices have the potential of becoming multifunctional ML simulation tools that could provide even better predictions in wider fields of materials science.展开更多
金属锂因其具有极高的理论容量(3860 mAh·g^(−1))、最低的电极电位(−3.04 V vs.标准氢电极)和低的密度(0.534 g·cm^(−3)),被认为是最具潜力的负极材料。但循环过程中不可控的枝晶生长及不稳定的固体电解质相界面膜所引起的安...金属锂因其具有极高的理论容量(3860 mAh·g^(−1))、最低的电极电位(−3.04 V vs.标准氢电极)和低的密度(0.534 g·cm^(−3)),被认为是最具潜力的负极材料。但循环过程中不可控的枝晶生长及不稳定的固体电解质相界面膜所引起的安全隐患和电池库伦效率低等问题严重阻碍了锂金属负极的发展。通过在电极表面构建人造保护膜可以有效调控锂离子沉积行为,因此人造保护膜的构建是一种简单高效抑制锂枝晶生长的策略。本综述将从聚合物保护膜、无机保护膜、有机-无机复合保护膜和合金保护膜总结了人造保护膜的构建方法、抑制锂枝晶生长机理,为促进高比能锂金属电池的商业化应用提供借鉴参考作用。展开更多
This study established a method for the simultaneous determination of 74 pesticide residues in Panax notoginseng by QuEChERS pretreatment method coupled with GC-MS/MS,and carried out pesticide residue analysis on 20 b...This study established a method for the simultaneous determination of 74 pesticide residues in Panax notoginseng by QuEChERS pretreatment method coupled with GC-MS/MS,and carried out pesticide residue analysis on 20 batches of market samples in China.The samples were extracted with acetonitrile,cleaned up with primary secondary amine(PSA)and octadecylsilane(C18)and determined by GC-MS/MS in multiple reaction monitoring(MRM)mode.Matrix-matched calibration was recommended to combat the matrix effect.A good linearity was observed in the range of 10−500 ng/mL with correlation coefficients≥0.9950.The mean recoveries for most of the pesticides were in the range of 70%−120%with RSD<20%.The limits of detection ranged 0.28–2.00μg/kg,while the limits of quantification were 0.94–6.65μg/kg.Following the application of“top-down”approach,the expanded measurement uncertainty for all the analytes was<30%.The proposed method was successfully applied to determine pesticide residues in 20 market samples in China,where 9 pesticides were detected and quintozene exceeded the criteria domestically and abroad.展开更多
Elastic waves are affected by viscoelasticity during the propagation through the Earth,resulting in energy attenuation and phase distortion,in turn resulting in low seismic imaging accuracy.Therefore,viscoelasticity s...Elastic waves are affected by viscoelasticity during the propagation through the Earth,resulting in energy attenuation and phase distortion,in turn resulting in low seismic imaging accuracy.Therefore,viscoelasticity should be considered in seismic migration imaging.We propose a Q compensated multicomponent elastic Gaussian beam migration(Q-EGBM)method to(1)separate the elastic-wave data into longitudinal(P)and transverse(S)waves to perform PP-wave and PS-wave imaging;(2)recover the amplitude loss caused by attenuation;(3)correct phase distortions caused by dispersion;(4)improve the resolution of migration imaging.In this paper,to accomplish(2),(3),and(4),we derive complex-valued traveltimes in viscoelastic media.The results of numerical experiments using a simple five-layer model and a sophisticated BP gas model show that the method presented here has significant advantages in recovering energy decay and correcting phase distortion,as well as significantly improving imaging resolution.展开更多
基金supported by Beijing Natural Science Foundation(Grant No.1242022).The numerical simulations in this work were performed at HSCC of Beijing Normal University.
文摘A recently discovered family of kagome lattice materials,AV_(3)Sb_(5)(A=K,Rb,Cs),has attracted great interest,especiallyin the debate over their dominant superconducting pairing symmetry.To explore this issue,we study the superconductingpairing behavior within the kagome-lattice Hubbard model through the constrained path Monte Carlo method.It isfound that doping around the Dirac point generates a dominant next-nearest-neighbor-d pairing symmetry driven by on-siteCoulomb interaction U.However,when considering the nearest-neighbor interaction V,it may induce nearest-neighbor-ppairing to become the preferred pairing symmetry.Our results provide useful information to identify the dominant superconductingpairing symmetry in the AV_(3)Sb_(5)family.
基金supported by the National Social Science Fund of China(23BGL272)。
文摘The fraudulent website image is a vital information carrier for telecom fraud.The efficient and precise recognition of fraudulent website images is critical to combating and dealing with fraudulent websites.Current research on image recognition of fraudulent websites is mainly carried out at the level of image feature extraction and similarity study,which have such disadvantages as difficulty in obtaining image data,insufficient image analysis,and single identification types.This study develops a model based on the entropy method for image leader decision and Inception-v3 transfer learning to address these disadvantages.The data processing part of the model uses a breadth search crawler to capture the image data.Then,the information in the images is evaluated with the entropy method,image weights are assigned,and the image leader is selected.In model training and prediction,the transfer learning of the Inception-v3 model is introduced into image recognition of fraudulent websites.Using selected image leaders to train the model,multiple types of fraudulent websites are identified with high accuracy.The experiment proves that this model has a superior accuracy in recognizing images on fraudulent websites compared to other current models.
基金This work was financially supported by the Guangdong Basic and Applied Basic Research Foundation(2020A1515010982)the National Natural Science Foundation of China(21805191)+2 种基金Shenzhen Science and Technology Program(JCYJ20210324094000001,20190808142001745,20200812122947002)Shenzhen Peacock Plan(20210802524B and 20180921273B)the Australian Research Council(FT200100015)。
文摘This comprehensive review provides a deep exploration of the unique roles of single atom catalysts(SACs)in photocatalytic hydrogen peroxide(H_(2)O_(2))production.SACs offer multiple benefits over traditional catalysts such as improved efficiency,selectivity,and flexibility due to their distinct electronic structure and unique properties.The review discusses the critical elements in the design of SACs,including the choice of metal atom,host material,and coordination environment,and how these elements impact the catalytic activity.The role of single atoms in photocatalytic H_(2)O_(2)production is also analysed,focusing on enhancing light absorption and charge generation,improving the migration and separation of charge carriers,and lowering the energy barrier of adsorption and activation of reactants.Despite these advantages,several challenges,including H_(2)O_(2)decomposition,stability of SACs,unclear mechanism,and low selectivity,need to be overcome.Looking towards the future,the review suggests promising research directions such as direct utilization of H_(2)O_(2),high-throughput synthesis and screening,the creation of dual active sites,and employing density functional theory for investigating the mechanisms of SACs in H_(2)O_(2)photosynthesis.This review provides valuable insights into the potential of single atom catalysts for advancing the field of photocatalytic H_(2)O_(2)production.
基金supported by the National Natural Science Foundation of China (Grant Nos.12234009,12275048,12304359,and 12274215)the National Key R&D Program of China (Grant No.2020YFA0309500)+4 种基金the Innovation Program for Quantum Science and Technology (Grant No.2021ZD0301400)the Program for Innovative Talents and Entrepreneurs in Jiangsu,the Natural Science Foundation of Jiangsu Province (Grant No.BK20220759)the Key R&D Program of Guangdong Province,China (Grant No.2020B0303010001)the China Postdoctoral Science Foundation (Grant No.2023M731611)the Jiangsu Funding Program for Excellent Postdoctoral Talent (Grant No.2023ZB717)。
文摘High-order quantum coherence reveals the statistical correlation of quantum particles. Manipulation of quantum coherence of light in the temporal domain enables the production of the single-photon source, which has become one of the most important quantum resources. High-order quantum coherence in the spatial domain plays a crucial role in a variety of applications, such as quantum imaging, holography, and microscopy. However, the active control of second-order spatial quantum coherence remains a challenging task. Here we predict theoretically and demonstrate experimentally the first active manipulation of second-order spatial quantum coherence,which exhibits the capability of switching between bunching and anti-bunching, by mapping the entanglement of spatially structured photons. We also show that signal processing based on quantum coherence exhibits robust resistance to intensity disturbance. Our findings not only enhance existing applications but also pave the way for broader utilization of higher-order spatial quantum coherence.
基金funded by the National Science Foundation of China(Nos.72088101 and 41807259)the Innovation-Driven Project of Central South University(No.2020CX040)the Shenghua Lieying Program of Central South University(Principle Investigator:Dr.Jian Zhou)。
文摘Coal burst is a severe hazard that can result in fatalities and damage of facilities in underground coal mines.To address this issue,a robust unascertained combination model is proposed to study the coal burst hazard based on an updated database.Four assessment indexes are used in the model,which are the dynamic failure duration(DT),elastic energy index(WET),impact energy index(KE)and uniaxial compressive strength(RC).Four membership functions,including linear(L),parabolic(P),S and Weibull(W)functions,are proposed to measure the uncertainty level of individual index.The corresponding weights are determined through information entropy(EN),analysis hierarchy process(AHP)and synthetic weights(CW).Simultaneously,the classification criteria,including unascertained cluster(UC)and credible identification principle(CIP),are analyzed.The combination algorithm,consisting of P function,CW and CIP(P-CW-CIP),is selected as the optimal classification model in function of theory analysis and to train the samples.Ultimately,the established ensemble model is further validated through test samples with 100%accuracy.The results reveal that the hybrid model has a great potential in the coal burst hazard evaluation in underground coal mines.
基金supported financially by the National Natural Science Foundation of China (No. 21607121)by the National Research Foundation of Korea (NRF) (Grant number: NRF2015R1A4A1042434)
文摘Amine-silica composite materials for post-combustion COcapture have attracted considerable attention because of their high COuptake at low COconcentrations, excellent COcapture selectivity in the presence of moisture, and lower energy requirements for sorbent regeneration. This review discusses the recent advances in amine-silica composites for COcapture, including adsorbent preparation and characterization, COcapture under dry and moisture conditions at different COpartial pressures, sorbent regeneration, and stability after many cyclic sorption-desorption runs.
基金support from the Ministry of Education(MOE) Singapore Tier 1 (RG8/20)。
文摘A large database is desired for machine learning(ML) technology to make accurate predictions of materials physicochemical properties based on their molecular structure.When a large database is not available,the development of proper featurization method based on physicochemical nature of target proprieties can improve the predictive power of ML models with a smaller database.In this work,we show that two new featurization methods,volume occupation spatial matrix and heat contribution spatial matrix,can improve the accuracy in predicting energetic materials' crystal density(ρ_(crystal)) and solid phase enthalpy of formation(H_(f,solid)) using a database containing 451 energetic molecules.Their mean absolute errors are reduced from 0.048 g/cm~3 and 24.67 kcal/mol to 0.035 g/cm~3 and 9.66 kcal/mol,respectively.By leave-one-out-cross-validation,the newly developed ML models can be used to determine the performance of most kinds of energetic materials except cubanes.Our ML models are applied to predict ρ_(crystal) and H_(f,solid) of CHON-based molecules of the 150 million sized PubChem database,and screened out 56 candidates with competitive detonation performance and reasonable chemical structures.With further improvement in future,spatial matrices have the potential of becoming multifunctional ML simulation tools that could provide even better predictions in wider fields of materials science.
文摘金属锂因其具有极高的理论容量(3860 mAh·g^(−1))、最低的电极电位(−3.04 V vs.标准氢电极)和低的密度(0.534 g·cm^(−3)),被认为是最具潜力的负极材料。但循环过程中不可控的枝晶生长及不稳定的固体电解质相界面膜所引起的安全隐患和电池库伦效率低等问题严重阻碍了锂金属负极的发展。通过在电极表面构建人造保护膜可以有效调控锂离子沉积行为,因此人造保护膜的构建是一种简单高效抑制锂枝晶生长的策略。本综述将从聚合物保护膜、无机保护膜、有机-无机复合保护膜和合金保护膜总结了人造保护膜的构建方法、抑制锂枝晶生长机理,为促进高比能锂金属电池的商业化应用提供借鉴参考作用。
基金the National Key Research and Development Plan of China(2017YFC1702500).
文摘This study established a method for the simultaneous determination of 74 pesticide residues in Panax notoginseng by QuEChERS pretreatment method coupled with GC-MS/MS,and carried out pesticide residue analysis on 20 batches of market samples in China.The samples were extracted with acetonitrile,cleaned up with primary secondary amine(PSA)and octadecylsilane(C18)and determined by GC-MS/MS in multiple reaction monitoring(MRM)mode.Matrix-matched calibration was recommended to combat the matrix effect.A good linearity was observed in the range of 10−500 ng/mL with correlation coefficients≥0.9950.The mean recoveries for most of the pesticides were in the range of 70%−120%with RSD<20%.The limits of detection ranged 0.28–2.00μg/kg,while the limits of quantification were 0.94–6.65μg/kg.Following the application of“top-down”approach,the expanded measurement uncertainty for all the analytes was<30%.The proposed method was successfully applied to determine pesticide residues in 20 market samples in China,where 9 pesticides were detected and quintozene exceeded the criteria domestically and abroad.
文摘Elastic waves are affected by viscoelasticity during the propagation through the Earth,resulting in energy attenuation and phase distortion,in turn resulting in low seismic imaging accuracy.Therefore,viscoelasticity should be considered in seismic migration imaging.We propose a Q compensated multicomponent elastic Gaussian beam migration(Q-EGBM)method to(1)separate the elastic-wave data into longitudinal(P)and transverse(S)waves to perform PP-wave and PS-wave imaging;(2)recover the amplitude loss caused by attenuation;(3)correct phase distortions caused by dispersion;(4)improve the resolution of migration imaging.In this paper,to accomplish(2),(3),and(4),we derive complex-valued traveltimes in viscoelastic media.The results of numerical experiments using a simple five-layer model and a sophisticated BP gas model show that the method presented here has significant advantages in recovering energy decay and correcting phase distortion,as well as significantly improving imaging resolution.
