The development of efficient photocatalysts for selective organic transformations under visible light remains a major challenge in sustainable chemistry.In this study,we present a straightforward solvothermal strategy...The development of efficient photocatalysts for selective organic transformations under visible light remains a major challenge in sustainable chemistry.In this study,we present a straightforward solvothermal strategy for fabricating a defect-engineered ZrO_(2)/UiO-66-NH_(2)hybrid material with abundant oxygen vacancies,enabling the visible-light-driven oxidation of benzyl alcohol to benzaldehyde.By optimizing the solvothermal treatment duration,the composite(UiO-66-NH_(2)-2h)achieves a 74.1%conversion of benzyl alcohol with>99%selectivity toward benzaldehyde under mild conditions,substantially out-performing pristine UiO-66-NH_(2).Structural and mechanistic studies reveal that the solvothermal process induces the in situ formation of ultrasmall,uniformly dispersed ZrO_(2)nanoparticles(~2.3 nm)within the MOF matrix,while simultaneously generating abundant oxygen vacancies,as confirmed by XPS,EPR,and HRTEM analyses.The defect-mediated electronic structure of the ZrO_(2)/UiO-66-NH_(2)hybrid enhances visible-light absorption,facilitates charge carrier separation,and pro-motes efficient activation of O_(2)into superoxide radicals(·O_(2)^(−)),the primary reactive species.Transient photocurrent measure-ments and electrochemical impedance spectroscopy further verify the improved charge separation efficiency.The synergistic interplay between oxygen vacancies and the intimate ZrO_(2)/UiO-66-NH_(2)interface provides a unique defect-mediated charge transfer pathway,distinguishing this system from conventional heterojunctions.This study demonstrates a facile,one-step approach to integrate defect engineering with interfacial hybridization in MOF-based photocatalysts,off ering a scalable route for solar-driven organic synthesis.展开更多
High-throughput transcriptomics has evolved from bulk RNA-seq to single-cell and spatial profiling,yet its clinical translation still depends on effective integration across diverse omics and data modalities.Emerging ...High-throughput transcriptomics has evolved from bulk RNA-seq to single-cell and spatial profiling,yet its clinical translation still depends on effective integration across diverse omics and data modalities.Emerging foundation models and multimodal learning frameworks are enabling scalable and transferable representations of cellular states,while advances in interpretability and real-world data integration are bridging the gap between discovery and clinical application.This paper outlines a concise roadmap for AI-driven,transcriptome-centered multi-omics integration in precision medicine(Figure 1).展开更多
Ternary Ag/AgC l/BiO IO3 composite photocatalysts are prepared by a facile method. Enhanced visible-light absorption and charge carrier separation are achieved after the introduction of Ag/AgC l particles into BiO IO3...Ternary Ag/AgC l/BiO IO3 composite photocatalysts are prepared by a facile method. Enhanced visible-light absorption and charge carrier separation are achieved after the introduction of Ag/AgC l particles into BiO IO3 systems,as revealed by ultraviolet-visible diffuse-reflectance spectrometry,photocurrent response and electrochemical impedance spectroscopy. The Ag/AgC l/BiO IO3 composites are applied to the visible-light photocatalytic oxidization of NO in air and exhibit an enhanced activity for NO removal in comparison with Ag/AgC l and pure BiO IO3. A possible photocatalytic mechanism for Ag/AgC l/BiO IO3 is proposed,which is related to the surface plasmon resonance effects of Ag metal and the effective carrier separation ability of BiO IO3. This work provides insight into the design and preparation of BiO IO3-based materials with enhanced visible-light photocatalysis ability.展开更多
The high exciton binding energy and lack of a positive oxidation band potential restrict the photocatalytic CO_(2)reduction efficiency of lead-free Bi-based halide perovskites Cs_(3)Bi_(2)X_(9)(X=Br,I).In this study,a...The high exciton binding energy and lack of a positive oxidation band potential restrict the photocatalytic CO_(2)reduction efficiency of lead-free Bi-based halide perovskites Cs_(3)Bi_(2)X_(9)(X=Br,I).In this study,a sequential growth method is presented to prepare a visible-light-driven(λ>420 nm)Z-scheme heterojunction photocatalyst composed of BiVO_(4)nanocrystals decorated on a Cs_(3)Bi_(2)I_(9)nanosheet for photocatalytic CO_(2)reduction coupled with water oxidation.The Cs_(3)Bi_(2)I_(9)/BiVO_(4)Z-scheme heterojunction photocatalyst is stable in the gas-solid photocatalytic CO_(2)reduction system,demonstrating a high visible-light-driven photocatalytic CO_(2)-to-CO production rate of 17.5μmol/(g·h),which is approximately three times that of pristine Cs_(3)Bi_(2)I_(9).The high efficiency of the Cs_(3)Bi_(2)I_(9)/BiVO_(4)heterojunction was attributed to the improved charge separation in Cs_(3)Bi_(2)I_(9).Moreover,the Z-scheme charge-transfer pathway preserves the negative reduction potential of Cs_(3)Bi_(2)I_(9)and the positive oxidation potential of BiVO_()4.This study off ers solid evidence of constructing Z-scheme heterojunctions to improve the photocatalytic performance of lead-free halide perovskites and would inspire more ideas for developing leadfree halide perovskite photocatalysts.展开更多
With the aim of developing a low-cost and efficient visible-light-driven photocatalyst for radical polymerization,iron-chelating polyimide networks(Fe@MPI)was fabricated by firstly synthesizing photoactive melamine-co...With the aim of developing a low-cost and efficient visible-light-driven photocatalyst for radical polymerization,iron-chelating polyimide networks(Fe@MPI)was fabricated by firstly synthesizing photoactive melamine-containing polyimide(MPI)networks and then incorporating Fe(III)cations into the polymer networks.Fe@MPI exhibits a wide absorption spectrum ranging from 220 to 1250 nm and 3.5 times higher photocurrent intensity as compared with the pristine MPI.Based on its excellent photo-electric properties,Fe@MPI was employed as a recyclable heterogeneous catalyst,providing sufficient activity for the visible-light driven radical polymerization to synthesize poly(methyl methacrylate)with molecular weight up to 31.×10^4 g mol.Taking advantage of the heterogeneous nature of the catalyst,Fe@MPI could be facilely regenerated from the polymerization solution by filtration without an obvious loss of its activity.This research provides a novel recyclable catalyst for visible-light driven radical polymerization.展开更多
We use a two‐step hydrothermal method to successfully synthesize Sn2Nb2O7nanocrystals with an average size of approximately20nm.The as‐obtained samples are characterized by powder X‐ray diffraction,ultraviolet‐vis...We use a two‐step hydrothermal method to successfully synthesize Sn2Nb2O7nanocrystals with an average size of approximately20nm.The as‐obtained samples are characterized by powder X‐ray diffraction,ultraviolet‐visible diffuse reflectance spectroscopy,Brunauer‐Emmett‐Teller analysis,scanning electron microscopy,and transmission electron microscopy.The photocatalytic activity of the Sn2Nb2O7nanocrystals is evaluated by photocatalytic water splitting under visible light irradiation.The Sn2Nb2O7nanocrystals with a large surface area of52.2m2/g show an enhanced visible‐light‐driven photocatalytic H2production activity,approximately5.5times higher than that of bulk Sn2Nb2O7powder.The higher photocatalytic activity of Sn2Nb2O7nanocrystals is mainly attributed to its relatively high dispersity of nanosized particles and larger specific surface area when compared with the bulk powder.展开更多
Monoclinic BiVO4 with multiple morphologies and/or porous structures were fabricated using the hydrothermal strategy. The materials were characterized by means of the XRD, Raman, TGA/DSC, SEM, XPS, and UV-Vis techniqu...Monoclinic BiVO4 with multiple morphologies and/or porous structures were fabricated using the hydrothermal strategy. The materials were characterized by means of the XRD, Raman, TGA/DSC, SEM, XPS, and UV-Vis techniques. The photocatalytic activities of the BiVO4 materials were evaluated for the degradation of Methyl Orange under visible-light irradiation. It is observed that pH value and surfactant exerted a great effect on the morphology and pore structure of the BiVO4 product. Spherical BiVO4 with porous structures, flower-cluster-like BiVO4, and flower-bundle-like BiVO4 were generated hydrothermally at 100°C with poly（vinyl pyrrolidone） （PVP） and urea （pH = 2） and at 160°C with NaHCO3 （pH = 7 and 8）, respectively. The PVP-derived BiVO4 showed much higher surface areas （5.0-8.4 m2/g） and narrower bandgap energies （2.45-2.49 eV）. The best photocatalytic performance of the spherical BiVO4 material with a surface area of 8.4 m2/g was associated with its higher surface area, narrower bandgap energy, higher surface oxygen vacancy density, and unique porous architecture.展开更多
This study presents a machine learning-based method for predicting fragment velocity distribution in warhead fragmentation under explosive loading condition.The fragment resultant velocities are correlated with key de...This study presents a machine learning-based method for predicting fragment velocity distribution in warhead fragmentation under explosive loading condition.The fragment resultant velocities are correlated with key design parameters including casing dimensions and detonation positions.The paper details the finite element analysis for fragmentation,the characterizations of the dynamic hardening and fracture models,the generation of comprehensive datasets,and the training of the ANN model.The results show the influence of casing dimensions on fragment velocity distributions,with the tendencies indicating increased resultant velocity with reduced thickness,increased length and diameter.The model's predictive capability is demonstrated through the accurate predictions for both training and testing datasets,showing its potential for the real-time prediction of fragmentation performance.展开更多
Visible-light-mediated O-H functionalization reactions of alcohols with diazo compounds have been fully developed in recent years.However,alkenyl and acetylenic alcohols were rarely examined in these reactions due to ...Visible-light-mediated O-H functionalization reactions of alcohols with diazo compounds have been fully developed in recent years.However,alkenyl and acetylenic alcohols were rarely examined in these reactions due to the inevitable side reactions involving cycloaddition.Herein,the visible-light-mediated O-H functionalization reactions of alkenyl alcohols with diazo compounds were developed.This process competed favorably with the cycloaddition reaction.A series of multifunctional ethers were provided in low to high yields with aryldiazoacetates or 3-diazooxindoles.Biologically relevant spirooxindole-fused oxacycle could be easily accessed from the O-H functionalization product of alkenyl alcohol and 3-diazooxindole.展开更多
Methane(CH4),the predominant component of natural gas and shale gas,is regarded as a promising carbon feedstock for chemical synthesis[1].However,considering the extreme stability of CH4 molecules,it's quite chall...Methane(CH4),the predominant component of natural gas and shale gas,is regarded as a promising carbon feedstock for chemical synthesis[1].However,considering the extreme stability of CH4 molecules,it's quite challenging in simultaneously achieving high activity and selectivity for target products under mild conditions,especially when synthesizing high-value C2t chemicals such as ethanol[2].The conversion of methane to ethanol by photocatalysis is promising for achieving transformation under ambient temperature and pressure conditions.Currently,the apparent quantum efficiency(AQE)of solar-driven methane-to-ethanol conversion is generally below 0.5%[3,4].Furthermore,the stability of photocatalysts remains inadequate,offering substantial potential for further improvement.展开更多
The conventional Kibble–Zurek mechanism,describing driven dynamics across critical points based on the adiabatic-impulse scenario(AIS),has attracted broad attention.However,the driven dynamics at the tricritical poin...The conventional Kibble–Zurek mechanism,describing driven dynamics across critical points based on the adiabatic-impulse scenario(AIS),has attracted broad attention.However,the driven dynamics at the tricritical point with two independent relevant directions have not been adequately studied.Here,we employ the time-dependent variational principle to study the driven critical dynamics at a one-dimensional supersymmetric Ising tricritical point.For the relevant direction along the Ising critical line,the AIS apparently breaks down.Nevertheless,we find that the critical dynamics can still be described by finite-time scaling in which the driving rate has a dimension of r_(μ)=z+1/v_(μ)with z and v_(μ)being the dynamic exponent and correlation length exponent in this direction,respectively.For driven dynamics along another direction,the driving rate has a dimension of r_(p)=z+1/v_(p)with v_(p)being another correlation length exponent.Our work brings a new fundamental perspective into nonequilibrium critical dynamics near the tricritical point,which could be realized in programmable quantum processors in Rydberg atomic systems.展开更多
In order to protect the environment and economize energy,a nitrogen-fixing photocatalyst,VMCeact,is investigated in this work.This catalyst is prepared from a natural mineral,vermiculite,and modified by Ce-based metal...In order to protect the environment and economize energy,a nitrogen-fixing photocatalyst,VMCeact,is investigated in this work.This catalyst is prepared from a natural mineral,vermiculite,and modified by Ce-based metal-organic framework,Ce-UiO-66.Vermiculite was treated with formic acid;thus,Ce-UiO-66 particles grew in-situ on vermiculite;then,Ce-UiO-66 particles were activated by ultraviolet irradiation.The vermiculite absorbed visible light with a narrow band gap,and transferred photogenerated electrons to the active sites on Ce-UiO-66.Moreover,the lamella structure of vermiculite protected Ce-UiO-66 during photocatalytic process.Therefore,with only 45.92 wt%of Ce-UiO-66,the nitrogen fixation performance of VMCeact was 2.29 times that of pure activated Ce-UiO-66 particles under 455nm light irradiation(apparent quantum efficiency of 4.49%),and retained at least 96.05%performance after 7×24 h of photocatalytic reaction.This cost-reduced,efficient and stable photocatalyst has the opportunity to facilitate environmentally friendly ammonia production.展开更多
As the number of distributed power supplies increases on the user side,smart grids are becoming larger and more complex.These changes bring new security challenges,especially with the widespread adop-tion of data-driv...As the number of distributed power supplies increases on the user side,smart grids are becoming larger and more complex.These changes bring new security challenges,especially with the widespread adop-tion of data-driven control methods.This paper introduces a novel black-box false data injection attack(FDIA)method that exploits the measurement modules of distributed power supplies within smart grids,highlighting its effectiveness in bypassing conventional security measures.Unlike traditional methods that focus on data manipulation within communication networks,this approach directly injects false data at the point of measurement,using a generative adversarial network(GAN)to generate stealthy attack vectors.This method requires no detailed knowledge of the target system,making it practical for real-world attacks.The attack’s impact on power system stability is demonstrated through experiments,high-lighting the significant cybersecurity risks introduced by data-driven algorithms in smart grids.展开更多
Current research on robot calibration can be roughly classified into two categories,and both of them have certain inherent limitations.Model-based methods are difficult to model and compensate the pose errors arising ...Current research on robot calibration can be roughly classified into two categories,and both of them have certain inherent limitations.Model-based methods are difficult to model and compensate the pose errors arising from configuration-dependent geometric and non-geometric source errors,whereas the accuracy of data-driven methods depends on a large amount of measurement data.Using a 5-DOF(degrees of freedom)hybrid machining robot as an exemplar,this study presents a model data-driven approach for the calibration of robotic manipulators.An f-DOF realistic robot containing various source errors is visualized as a 6-DOF fictitious robot having error-free parameters,but erroneous actuated/virtual joint motions.The calibration process essentially involves four steps:(1)formulating the linear map relating the pose error twist to the joint motion errors,(2)parameterizing the joint motion errors using second-order polynomials in terms of nominal actuated joint variables,(3)identifying the polynomial coefficients using the weighted least squares plus principal component analysis,and(4)compensating the compensable pose errors by updating the nominal actuated joint variables.The merit of this approach is that it enables compensation of the pose errors caused by configuration-dependent geometric and non-geometric source errors using finite measurement configurations.Experimental studies on a prototype machine illustrate the effectiveness of the proposed approach.展开更多
Driven critical dynamics in quantum phase transitions holds significant theoretical importance,and also has practical applications in fast-developing quantum devices.While scaling corrections have been shown to play i...Driven critical dynamics in quantum phase transitions holds significant theoretical importance,and also has practical applications in fast-developing quantum devices.While scaling corrections have been shown to play important roles in fully characterizing equilibrium quantum criticality,their impact on nonequilibrium critical dynamics has not been extensively explored.In this work,we investigate the driven critical dynamics in a two-dimensional quantum Heisenberg model.We find that in this model the scaling corrections arising from both finite system size and finite driving rate must be incorporated into the finite-time scaling form in order to properly describe the nonequilibrium scaling behaviors.In addition,improved scaling relations are obtained from the expansion of the full scaling form.We numerically verify these scaling forms and improved scaling relations for different starting states using the nonequilibrium quantum Monte Carlo algorithm.展开更多
Despite significant progress in the Prognostics and Health Management(PHM)domain using pattern learning systems from data,machine learning(ML)still faces challenges related to limited generalization and weak interpret...Despite significant progress in the Prognostics and Health Management(PHM)domain using pattern learning systems from data,machine learning(ML)still faces challenges related to limited generalization and weak interpretability.A promising approach to overcoming these challenges is to embed domain knowledge into the ML pipeline,enhancing the model with additional pattern information.In this paper,we review the latest developments in PHM,encapsulated under the concept of Knowledge Driven Machine Learning(KDML).We propose a hierarchical framework to define KDML in PHM,which includes scientific paradigms,knowledge sources,knowledge representations,and knowledge embedding methods.Using this framework,we examine current research to demonstrate how various forms of knowledge can be integrated into the ML pipeline and provide roadmap to specific usage.Furthermore,we present several case studies that illustrate specific implementations of KDML in the PHM domain,including inductive experience,physical model,and signal processing.We analyze the improvements in generalization capability and interpretability that KDML can achieve.Finally,we discuss the challenges,potential applications,and usage recommendations of KDML in PHM,with a particular focus on the critical need for interpretability to ensure trustworthy deployment of artificial intelligence in PHM.展开更多
Acute lung injury(ALI)was characterized by excessive reactive oxygen species(ROS)levels and inflammatory response in the lung.Scavenging ROS could inhibit the excessive inflammatory response,further treating ALI.Herei...Acute lung injury(ALI)was characterized by excessive reactive oxygen species(ROS)levels and inflammatory response in the lung.Scavenging ROS could inhibit the excessive inflammatory response,further treating ALI.Herein,we designed a novel nanozyme(P@Co)comprised of polydopamine(PDA)nanoparticles(NPs)loading with ultra-small Co,combining with near infrared(NIR)irradiation,which could efficiently scavenge intracellular ROS and suppress inflammatory responses against ALI.For lipopolysaccharide(LPS)induced macrophages,P@Co+NIR presented excellent antioxidant and anti-inflammatory capacities through lowering intracellular ROS levels,decreasing the expression levels of interleukin-6(IL-6)and tumor necrosis factor-α(TNF-α)as well as inducing macrophage M2 directional polarization.Significantly,it displayed the outstanding activities of lowering acute lung inflammation,relieving diffuse alveolar damage,and up-regulating heat shock protein 70(HSP70)expression,resulting in synergistic enhanced ALI therapy effect.It offers a novel strategy for the clinical treatment of ROS related diseases.展开更多
Additive manufacturing(AM)technology has revolutionized engineering field by enabling the creation of intricate,high-performance structures that were once difficult or impossible to fabricate.This transformative techn...Additive manufacturing(AM)technology has revolutionized engineering field by enabling the creation of intricate,high-performance structures that were once difficult or impossible to fabricate.This transformative technology has particularly advanced the development of metamaterials-engineered materials whose unique properties arise from their structure rather than composition-unlocking immense potential in fields ranging from aerospace to biomedical engineering.展开更多
Accurate identification and effective support of key blocks are crucial for ensuring the stability and safety of rock slopes.The number of structural planes and rock blocks were reduced in previous studies.This impair...Accurate identification and effective support of key blocks are crucial for ensuring the stability and safety of rock slopes.The number of structural planes and rock blocks were reduced in previous studies.This impairs the ability to characterize complex rock slopes accurately and inhibits the identification of key blocks.In this paper,a knowledge-data dually driven paradigm for accurate identification of key blocks in complex rock slopes is proposed.Our basic idea is to integrate key block theory into data-driven models based on finely characterizing structural features to identify key blocks in complex rock slopes accurately.The proposed novel paradigm consists of(1)representing rock slopes as graph-structured data based on complex systems theory,(2)identifying key nodes in the graph-structured data using graph deep learning,and(3)mapping the key nodes of graph-structured data to corresponding key blocks in the rock slope.Verification experiments and real-case applications are conducted by the proposed method.The verification results demonstrate excellent model performance,strong generalization capability,and effective classification results.Moreover,the real case application is conducted on the northern slope of the Yanqianshan Iron Mine.The results show that the proposed method can accurately identify key blocks in complex rock slopes,which can provide a decision-making basis and rational recommendations for effective support and instability prevention of rock slopes,thereby ensuring the stability of rock engineering and the safety of life and property.展开更多
The discovery of new superconducting materials,particularly those exhibiting high critical temperature(Tc),has been a vibrant area of study within the field of condensed matter physics.Conventional approaches primaril...The discovery of new superconducting materials,particularly those exhibiting high critical temperature(Tc),has been a vibrant area of study within the field of condensed matter physics.Conventional approaches primarily rely on physical intuition to search for potential superconductors within the existing databases.However,the known materials only scratch the surface of the extensive array of possibilities within the realm of materials.展开更多
基金the National Natural Sci-ence Foundation of China(Nos.22271038,22378038,22172012)C.P.thanks Dalian Science and Technology Innovation Fund(No.2024JJ12CG033)+1 种基金C.P.and Z.S thank State Key Laboratory of Heavy Oil Processing(Nos.WX20230149,SKLHOP202402005)Y.-Y.L.thanks the Guangxi Key Laboratory of Information Materials,Guilin University of Electronic Technology(No.231019-K).
文摘The development of efficient photocatalysts for selective organic transformations under visible light remains a major challenge in sustainable chemistry.In this study,we present a straightforward solvothermal strategy for fabricating a defect-engineered ZrO_(2)/UiO-66-NH_(2)hybrid material with abundant oxygen vacancies,enabling the visible-light-driven oxidation of benzyl alcohol to benzaldehyde.By optimizing the solvothermal treatment duration,the composite(UiO-66-NH_(2)-2h)achieves a 74.1%conversion of benzyl alcohol with>99%selectivity toward benzaldehyde under mild conditions,substantially out-performing pristine UiO-66-NH_(2).Structural and mechanistic studies reveal that the solvothermal process induces the in situ formation of ultrasmall,uniformly dispersed ZrO_(2)nanoparticles(~2.3 nm)within the MOF matrix,while simultaneously generating abundant oxygen vacancies,as confirmed by XPS,EPR,and HRTEM analyses.The defect-mediated electronic structure of the ZrO_(2)/UiO-66-NH_(2)hybrid enhances visible-light absorption,facilitates charge carrier separation,and pro-motes efficient activation of O_(2)into superoxide radicals(·O_(2)^(−)),the primary reactive species.Transient photocurrent measure-ments and electrochemical impedance spectroscopy further verify the improved charge separation efficiency.The synergistic interplay between oxygen vacancies and the intimate ZrO_(2)/UiO-66-NH_(2)interface provides a unique defect-mediated charge transfer pathway,distinguishing this system from conventional heterojunctions.This study demonstrates a facile,one-step approach to integrate defect engineering with interfacial hybridization in MOF-based photocatalysts,off ering a scalable route for solar-driven organic synthesis.
文摘High-throughput transcriptomics has evolved from bulk RNA-seq to single-cell and spatial profiling,yet its clinical translation still depends on effective integration across diverse omics and data modalities.Emerging foundation models and multimodal learning frameworks are enabling scalable and transferable representations of cellular states,while advances in interpretability and real-world data integration are bridging the gap between discovery and clinical application.This paper outlines a concise roadmap for AI-driven,transcriptome-centered multi-omics integration in precision medicine(Figure 1).
基金supported by the National Natural Science Foundation of China(5147807051108487)the Science and Technology Project from Chongqing Education Commission(KJ1400617)~~
文摘Ternary Ag/AgC l/BiO IO3 composite photocatalysts are prepared by a facile method. Enhanced visible-light absorption and charge carrier separation are achieved after the introduction of Ag/AgC l particles into BiO IO3 systems,as revealed by ultraviolet-visible diffuse-reflectance spectrometry,photocurrent response and electrochemical impedance spectroscopy. The Ag/AgC l/BiO IO3 composites are applied to the visible-light photocatalytic oxidization of NO in air and exhibit an enhanced activity for NO removal in comparison with Ag/AgC l and pure BiO IO3. A possible photocatalytic mechanism for Ag/AgC l/BiO IO3 is proposed,which is related to the surface plasmon resonance effects of Ag metal and the effective carrier separation ability of BiO IO3. This work provides insight into the design and preparation of BiO IO3-based materials with enhanced visible-light photocatalysis ability.
基金support from the National Key R&D Plan Project(No.2022YFA1505000)Prospective Basic Research Projects of CNPC(Nos.2021DQ03(2022Z-29)+4 种基金2022DJ5406,2022DJ5407,2022DJ5408,2022DJ4507,and TGRI-2021-1)the Natural Science Foundation of Shaanxi Province(No.2022JQ-078)the Natural Science Foundation of China(No.52302308)the Outstanding Youth Science Foundation Project of the National Natural Science Foundation of China(Overseas)(No.GYKP033)the Qinchuangyuan Cited High-Level Innovative and Entrepreneurial Talents Project(No.QCYRCXM-2022-143).
文摘The high exciton binding energy and lack of a positive oxidation band potential restrict the photocatalytic CO_(2)reduction efficiency of lead-free Bi-based halide perovskites Cs_(3)Bi_(2)X_(9)(X=Br,I).In this study,a sequential growth method is presented to prepare a visible-light-driven(λ>420 nm)Z-scheme heterojunction photocatalyst composed of BiVO_(4)nanocrystals decorated on a Cs_(3)Bi_(2)I_(9)nanosheet for photocatalytic CO_(2)reduction coupled with water oxidation.The Cs_(3)Bi_(2)I_(9)/BiVO_(4)Z-scheme heterojunction photocatalyst is stable in the gas-solid photocatalytic CO_(2)reduction system,demonstrating a high visible-light-driven photocatalytic CO_(2)-to-CO production rate of 17.5μmol/(g·h),which is approximately three times that of pristine Cs_(3)Bi_(2)I_(9).The high efficiency of the Cs_(3)Bi_(2)I_(9)/BiVO_(4)heterojunction was attributed to the improved charge separation in Cs_(3)Bi_(2)I_(9).Moreover,the Z-scheme charge-transfer pathway preserves the negative reduction potential of Cs_(3)Bi_(2)I_(9)and the positive oxidation potential of BiVO_()4.This study off ers solid evidence of constructing Z-scheme heterojunctions to improve the photocatalytic performance of lead-free halide perovskites and would inspire more ideas for developing leadfree halide perovskite photocatalysts.
文摘With the aim of developing a low-cost and efficient visible-light-driven photocatalyst for radical polymerization,iron-chelating polyimide networks(Fe@MPI)was fabricated by firstly synthesizing photoactive melamine-containing polyimide(MPI)networks and then incorporating Fe(III)cations into the polymer networks.Fe@MPI exhibits a wide absorption spectrum ranging from 220 to 1250 nm and 3.5 times higher photocurrent intensity as compared with the pristine MPI.Based on its excellent photo-electric properties,Fe@MPI was employed as a recyclable heterogeneous catalyst,providing sufficient activity for the visible-light driven radical polymerization to synthesize poly(methyl methacrylate)with molecular weight up to 31.×10^4 g mol.Taking advantage of the heterogeneous nature of the catalyst,Fe@MPI could be facilely regenerated from the polymerization solution by filtration without an obvious loss of its activity.This research provides a novel recyclable catalyst for visible-light driven radical polymerization.
文摘We use a two‐step hydrothermal method to successfully synthesize Sn2Nb2O7nanocrystals with an average size of approximately20nm.The as‐obtained samples are characterized by powder X‐ray diffraction,ultraviolet‐visible diffuse reflectance spectroscopy,Brunauer‐Emmett‐Teller analysis,scanning electron microscopy,and transmission electron microscopy.The photocatalytic activity of the Sn2Nb2O7nanocrystals is evaluated by photocatalytic water splitting under visible light irradiation.The Sn2Nb2O7nanocrystals with a large surface area of52.2m2/g show an enhanced visible‐light‐driven photocatalytic H2production activity,approximately5.5times higher than that of bulk Sn2Nb2O7powder.The higher photocatalytic activity of Sn2Nb2O7nanocrystals is mainly attributed to its relatively high dispersity of nanosized particles and larger specific surface area when compared with the bulk powder.
基金supported by the National Natural Science Foundation of China (No. 20973017, 21077007)the Creative Research Foundation of Beijing University of Technology (No. 00500054R4003, 005000543111501)+2 种基金the HiTech Research and Development Program (863)of China (No. 2009AA063201)the Funding Projectfor Academic Human Resources Development in Institutions of Higher Learning under the Jurisdiction of Beijing Municipality (No. PHR200907105, PHR201007105,PHR201107104)the Hong Kong Baptist University (FRG2/09-10/023)
文摘Monoclinic BiVO4 with multiple morphologies and/or porous structures were fabricated using the hydrothermal strategy. The materials were characterized by means of the XRD, Raman, TGA/DSC, SEM, XPS, and UV-Vis techniques. The photocatalytic activities of the BiVO4 materials were evaluated for the degradation of Methyl Orange under visible-light irradiation. It is observed that pH value and surfactant exerted a great effect on the morphology and pore structure of the BiVO4 product. Spherical BiVO4 with porous structures, flower-cluster-like BiVO4, and flower-bundle-like BiVO4 were generated hydrothermally at 100°C with poly（vinyl pyrrolidone） （PVP） and urea （pH = 2） and at 160°C with NaHCO3 （pH = 7 and 8）, respectively. The PVP-derived BiVO4 showed much higher surface areas （5.0-8.4 m2/g） and narrower bandgap energies （2.45-2.49 eV）. The best photocatalytic performance of the spherical BiVO4 material with a surface area of 8.4 m2/g was associated with its higher surface area, narrower bandgap energy, higher surface oxygen vacancy density, and unique porous architecture.
基金supported by Poongsan-KAIST Future Research Center Projectthe fund support provided by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(Grant No.2023R1A2C2005661)。
文摘This study presents a machine learning-based method for predicting fragment velocity distribution in warhead fragmentation under explosive loading condition.The fragment resultant velocities are correlated with key design parameters including casing dimensions and detonation positions.The paper details the finite element analysis for fragmentation,the characterizations of the dynamic hardening and fracture models,the generation of comprehensive datasets,and the training of the ANN model.The results show the influence of casing dimensions on fragment velocity distributions,with the tendencies indicating increased resultant velocity with reduced thickness,increased length and diameter.The model's predictive capability is demonstrated through the accurate predictions for both training and testing datasets,showing its potential for the real-time prediction of fragmentation performance.
文摘Visible-light-mediated O-H functionalization reactions of alcohols with diazo compounds have been fully developed in recent years.However,alkenyl and acetylenic alcohols were rarely examined in these reactions due to the inevitable side reactions involving cycloaddition.Herein,the visible-light-mediated O-H functionalization reactions of alkenyl alcohols with diazo compounds were developed.This process competed favorably with the cycloaddition reaction.A series of multifunctional ethers were provided in low to high yields with aryldiazoacetates or 3-diazooxindoles.Biologically relevant spirooxindole-fused oxacycle could be easily accessed from the O-H functionalization product of alkenyl alcohol and 3-diazooxindole.
基金the support from the National Natural Science Foundation of China(52202306)Program from Guangdong Introducing Innovative and Entrepreneurial Teams(2019ZT08L101 and RCTDPT-2020-001)+1 种基金Shenzhen Key Laboratory of Eco-materials and Renewable Energy(ZDSYS20200922160400001)the Provincial Talent Plan of Guangdong(2023TB0012).
文摘Methane(CH4),the predominant component of natural gas and shale gas,is regarded as a promising carbon feedstock for chemical synthesis[1].However,considering the extreme stability of CH4 molecules,it's quite challenging in simultaneously achieving high activity and selectivity for target products under mild conditions,especially when synthesizing high-value C2t chemicals such as ethanol[2].The conversion of methane to ethanol by photocatalysis is promising for achieving transformation under ambient temperature and pressure conditions.Currently,the apparent quantum efficiency(AQE)of solar-driven methane-to-ethanol conversion is generally below 0.5%[3,4].Furthermore,the stability of photocatalysts remains inadequate,offering substantial potential for further improvement.
基金supported by the National Natural Science Foundation of China(Grant Nos.12222515,12075324 for S.Yin,and 12347107,1257-4160 for Y.F.Jiang)the National Key R&D Program of China(Grant No.2022YFA1402703 for Y.F.Jiang)+1 种基金the Science and Technology Projects in Guangdong Province(Grant No.2021QN02X561 for S.Yin)the Science and Technology Projects in Guangzhou City(Grant No.2025A04J5408 for S.Yin)。
文摘The conventional Kibble–Zurek mechanism,describing driven dynamics across critical points based on the adiabatic-impulse scenario(AIS),has attracted broad attention.However,the driven dynamics at the tricritical point with two independent relevant directions have not been adequately studied.Here,we employ the time-dependent variational principle to study the driven critical dynamics at a one-dimensional supersymmetric Ising tricritical point.For the relevant direction along the Ising critical line,the AIS apparently breaks down.Nevertheless,we find that the critical dynamics can still be described by finite-time scaling in which the driving rate has a dimension of r_(μ)=z+1/v_(μ)with z and v_(μ)being the dynamic exponent and correlation length exponent in this direction,respectively.For driven dynamics along another direction,the driving rate has a dimension of r_(p)=z+1/v_(p)with v_(p)being another correlation length exponent.Our work brings a new fundamental perspective into nonequilibrium critical dynamics near the tricritical point,which could be realized in programmable quantum processors in Rydberg atomic systems.
基金supported by the National Natural Science Foundation of China(Nos.21978251,22102141 and U1904215)Natural Science Foundation of Jiangsu Province(No.BK20200044).
文摘In order to protect the environment and economize energy,a nitrogen-fixing photocatalyst,VMCeact,is investigated in this work.This catalyst is prepared from a natural mineral,vermiculite,and modified by Ce-based metal-organic framework,Ce-UiO-66.Vermiculite was treated with formic acid;thus,Ce-UiO-66 particles grew in-situ on vermiculite;then,Ce-UiO-66 particles were activated by ultraviolet irradiation.The vermiculite absorbed visible light with a narrow band gap,and transferred photogenerated electrons to the active sites on Ce-UiO-66.Moreover,the lamella structure of vermiculite protected Ce-UiO-66 during photocatalytic process.Therefore,with only 45.92 wt%of Ce-UiO-66,the nitrogen fixation performance of VMCeact was 2.29 times that of pure activated Ce-UiO-66 particles under 455nm light irradiation(apparent quantum efficiency of 4.49%),and retained at least 96.05%performance after 7×24 h of photocatalytic reaction.This cost-reduced,efficient and stable photocatalyst has the opportunity to facilitate environmentally friendly ammonia production.
基金supported by the National Natural Science Foundation of China(62302234).
文摘As the number of distributed power supplies increases on the user side,smart grids are becoming larger and more complex.These changes bring new security challenges,especially with the widespread adop-tion of data-driven control methods.This paper introduces a novel black-box false data injection attack(FDIA)method that exploits the measurement modules of distributed power supplies within smart grids,highlighting its effectiveness in bypassing conventional security measures.Unlike traditional methods that focus on data manipulation within communication networks,this approach directly injects false data at the point of measurement,using a generative adversarial network(GAN)to generate stealthy attack vectors.This method requires no detailed knowledge of the target system,making it practical for real-world attacks.The attack’s impact on power system stability is demonstrated through experiments,high-lighting the significant cybersecurity risks introduced by data-driven algorithms in smart grids.
基金Supported by National Natural Science Foundation of China(Grant Nos.52325501,U24B2047).
文摘Current research on robot calibration can be roughly classified into two categories,and both of them have certain inherent limitations.Model-based methods are difficult to model and compensate the pose errors arising from configuration-dependent geometric and non-geometric source errors,whereas the accuracy of data-driven methods depends on a large amount of measurement data.Using a 5-DOF(degrees of freedom)hybrid machining robot as an exemplar,this study presents a model data-driven approach for the calibration of robotic manipulators.An f-DOF realistic robot containing various source errors is visualized as a 6-DOF fictitious robot having error-free parameters,but erroneous actuated/virtual joint motions.The calibration process essentially involves four steps:(1)formulating the linear map relating the pose error twist to the joint motion errors,(2)parameterizing the joint motion errors using second-order polynomials in terms of nominal actuated joint variables,(3)identifying the polynomial coefficients using the weighted least squares plus principal component analysis,and(4)compensating the compensable pose errors by updating the nominal actuated joint variables.The merit of this approach is that it enables compensation of the pose errors caused by configuration-dependent geometric and non-geometric source errors using finite measurement configurations.Experimental studies on a prototype machine illustrate the effectiveness of the proposed approach.
基金supported by the National Natural Science Foundation of China(Grant Nos.12104109,12222515,and 12075324)the Science and Technology Projects in Guangzhou(Grant No.2024A04J2092)the Science and Technology Projects in Guangdong Province(Grant No.211193863020).
文摘Driven critical dynamics in quantum phase transitions holds significant theoretical importance,and also has practical applications in fast-developing quantum devices.While scaling corrections have been shown to play important roles in fully characterizing equilibrium quantum criticality,their impact on nonequilibrium critical dynamics has not been extensively explored.In this work,we investigate the driven critical dynamics in a two-dimensional quantum Heisenberg model.We find that in this model the scaling corrections arising from both finite system size and finite driving rate must be incorporated into the finite-time scaling form in order to properly describe the nonequilibrium scaling behaviors.In addition,improved scaling relations are obtained from the expansion of the full scaling form.We numerically verify these scaling forms and improved scaling relations for different starting states using the nonequilibrium quantum Monte Carlo algorithm.
基金Supported in part by Science Center for Gas Turbine Project(Project No.P2022-DC-I-003-001)National Natural Science Foundation of China(Grant No.52275130).
文摘Despite significant progress in the Prognostics and Health Management(PHM)domain using pattern learning systems from data,machine learning(ML)still faces challenges related to limited generalization and weak interpretability.A promising approach to overcoming these challenges is to embed domain knowledge into the ML pipeline,enhancing the model with additional pattern information.In this paper,we review the latest developments in PHM,encapsulated under the concept of Knowledge Driven Machine Learning(KDML).We propose a hierarchical framework to define KDML in PHM,which includes scientific paradigms,knowledge sources,knowledge representations,and knowledge embedding methods.Using this framework,we examine current research to demonstrate how various forms of knowledge can be integrated into the ML pipeline and provide roadmap to specific usage.Furthermore,we present several case studies that illustrate specific implementations of KDML in the PHM domain,including inductive experience,physical model,and signal processing.We analyze the improvements in generalization capability and interpretability that KDML can achieve.Finally,we discuss the challenges,potential applications,and usage recommendations of KDML in PHM,with a particular focus on the critical need for interpretability to ensure trustworthy deployment of artificial intelligence in PHM.
基金financially supported by the Key Research&Development Program of Guangxi(No.GuiKeAB22080088)the Joint Project on Regional High-Incidence Diseases Research of Guangxi Natural Science Foundation(No.2023GXNSFDA026023)+3 种基金the Natural Science Foundation of Guangxi(No.2023JJA140322)the National Natural Science Foundation of China(No.82360372)the High-level Medical Expert Training Program of Guangxi“139 Plan Funding(No.G202003010)the Medical Appropriate Technology Development and Popularization and Application Project of Guangxi(No.S2020099)。
文摘Acute lung injury(ALI)was characterized by excessive reactive oxygen species(ROS)levels and inflammatory response in the lung.Scavenging ROS could inhibit the excessive inflammatory response,further treating ALI.Herein,we designed a novel nanozyme(P@Co)comprised of polydopamine(PDA)nanoparticles(NPs)loading with ultra-small Co,combining with near infrared(NIR)irradiation,which could efficiently scavenge intracellular ROS and suppress inflammatory responses against ALI.For lipopolysaccharide(LPS)induced macrophages,P@Co+NIR presented excellent antioxidant and anti-inflammatory capacities through lowering intracellular ROS levels,decreasing the expression levels of interleukin-6(IL-6)and tumor necrosis factor-α(TNF-α)as well as inducing macrophage M2 directional polarization.Significantly,it displayed the outstanding activities of lowering acute lung inflammation,relieving diffuse alveolar damage,and up-regulating heat shock protein 70(HSP70)expression,resulting in synergistic enhanced ALI therapy effect.It offers a novel strategy for the clinical treatment of ROS related diseases.
文摘Additive manufacturing(AM)technology has revolutionized engineering field by enabling the creation of intricate,high-performance structures that were once difficult or impossible to fabricate.This transformative technology has particularly advanced the development of metamaterials-engineered materials whose unique properties arise from their structure rather than composition-unlocking immense potential in fields ranging from aerospace to biomedical engineering.
基金supported by the National Natural Science Foundation of China(Grant Nos.42277161,42230709).
文摘Accurate identification and effective support of key blocks are crucial for ensuring the stability and safety of rock slopes.The number of structural planes and rock blocks were reduced in previous studies.This impairs the ability to characterize complex rock slopes accurately and inhibits the identification of key blocks.In this paper,a knowledge-data dually driven paradigm for accurate identification of key blocks in complex rock slopes is proposed.Our basic idea is to integrate key block theory into data-driven models based on finely characterizing structural features to identify key blocks in complex rock slopes accurately.The proposed novel paradigm consists of(1)representing rock slopes as graph-structured data based on complex systems theory,(2)identifying key nodes in the graph-structured data using graph deep learning,and(3)mapping the key nodes of graph-structured data to corresponding key blocks in the rock slope.Verification experiments and real-case applications are conducted by the proposed method.The verification results demonstrate excellent model performance,strong generalization capability,and effective classification results.Moreover,the real case application is conducted on the northern slope of the Yanqianshan Iron Mine.The results show that the proposed method can accurately identify key blocks in complex rock slopes,which can provide a decision-making basis and rational recommendations for effective support and instability prevention of rock slopes,thereby ensuring the stability of rock engineering and the safety of life and property.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.62476278,12434009,and 12204533)the National Key R&D Program of China(Grant No.2024YFA1408601)the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0302402)。
文摘The discovery of new superconducting materials,particularly those exhibiting high critical temperature(Tc),has been a vibrant area of study within the field of condensed matter physics.Conventional approaches primarily rely on physical intuition to search for potential superconductors within the existing databases.However,the known materials only scratch the surface of the extensive array of possibilities within the realm of materials.
