The synchrotron radiation beamline BL17B of the National Facility for Protein Science(NFPS)in Shanghai,situated at the Shanghai Synchrotron Radiation Facility(SSRF),was originally designed for diffraction experiments ...The synchrotron radiation beamline BL17B of the National Facility for Protein Science(NFPS)in Shanghai,situated at the Shanghai Synchrotron Radiation Facility(SSRF),was originally designed for diffraction experiments and accommodates techniques including single-crystal diffraction,powder diffraction,and grazing-incidence wide-angle X-ray scattering(GIWAXS)to enable the characterization of long-range ordered atomic structures.The academic community associated with BL17B engages in research domains encompassing biology,environment,energy,and materials,and a pronounced demand for characterizing short-range ordered structures exists.To address these requirements,BL17B established an advanced X-ray absorption fine structure(XAFS)experimental platform that enabled it to address a wide range of systems,from crystalline to amorphous and from long-range order to short-range order.The XAFS platform allows simultaneous XAFS data acquisition for both the transmission and fluorescence modes within an energy range of 5-23 keV,encompassing the K-edges of titanium to ruthenium and the L3-edges of cesium to bismuth.The platform exemplifies high levels of automation achieved through automated sample assessment and data collection based on large-capacity sample wheels that facilitate remote sample loading.When integrated with a highly integrated control system that simplifies experimental preparation and data collection,the XAFS platform significantly bolsters experimental efficiency and enhances user experience.Notably,the platform boasts an impressively low extended X-ray absorption fine structure(EXAFS)detection limit of 0.04 wt%for dilute copper phthalocyanine(CuPc)samples and an even more remarkable X-ray absorption near edge structure(XANES)detection threshold of 0.01 wt%.These results demonstrate the methodology?s reliability in low-concentration sample analysis,confirming its capability to generate high-quality XAFS data.展开更多
The stable nanobubbles adhered to mineral surfaces may facilitate their efficient separation via flotation in the mining industry.However,the state of nanobubbles on mineral solid surfaces is still elusive.In this stu...The stable nanobubbles adhered to mineral surfaces may facilitate their efficient separation via flotation in the mining industry.However,the state of nanobubbles on mineral solid surfaces is still elusive.In this study,molecular dynamics(MD)simulations are employed to examine mineral-like model surfaces with varying degrees of hydrophobicity,modulated by surface charges,to elucidate the adsorption behavior of nanobubbles at the interface.Our findings not only contribute to the fundamental understanding of nanobubbles but also have potential applications in the mining industry.We observed that as the surface charge increases,the contact angle of the nanobubbles increases accordingly with shape transformation from a pancake-like gas film to a cap-like shape,and ultimately forming a stable nanobubble upon an ordered water monolayer.When the solid–water interactions are weak with a small partial charge,the hydrophobic gas(N_(2))molecules accumulate near the solid surfaces.However,we have found,for the first time,that gas molecules assemble a nanobubble on the water monolayer adjacent to the solid surfaces with large partial charges.Such phenomena are attributed to the formation of a hydrophobic water monolayer with a hydrogen bond network structure near the surface.展开更多
To enhance the prediction accuracy of unsteady wakes behind wind turbines,a novel reduced-order model is proposed by integrating a multifunctional recurrent fuzzy neural network(MFRFNN)and proper orthogonal decom-posi...To enhance the prediction accuracy of unsteady wakes behind wind turbines,a novel reduced-order model is proposed by integrating a multifunctional recurrent fuzzy neural network(MFRFNN)and proper orthogonal decom-position(POD).First,POD is employed to reduce the di-mensionality of the wind field data,extracting spatiotempo-rally correlated modal coefficients and modes.These reduced-order variables can effectively capture the essential features of unsteady wake behaviors.Next,MFRFNN is utilized to predict the time series of modal coefficients.Fi-nally,by combining the predicted modal coefficients with their corresponding modes,a flow field is reconstructed,al-lowing accurate prediction of unsteady wake dynamics.The predicted wake data exhibit high consistency with large eddy simulation results in both the near-and far-wake re-gions and outperform existing data-driven methods.This ap-proach offers significant potential for optimizing wind farm design and provides a new solution for the precise prediction of wind turbine wake behavior.展开更多
In this manuscript,we propose an analytical equivalent linear viscoelastic constitutive model for fiber-reinforced composites,bypassing general computational homogenization.The method is based on the reduced-order hom...In this manuscript,we propose an analytical equivalent linear viscoelastic constitutive model for fiber-reinforced composites,bypassing general computational homogenization.The method is based on the reduced-order homogenization(ROH)approach.The ROH method typically involves solving multiple finite element problems under periodic conditions to evaluate elastic strain and eigenstrain influence functions in an‘off-line’stage,which offers substantial cost savings compared to direct computational homogenization methods.Due to the unique structure of the fibrous unit cell,“off-line”stage calculation can be eliminated by influence functions obtained analytically.Introducing the standard solid model to the ROH method enables the creation of a comprehensive analytical homogeneous viscoelastic constitutive model.This method treats fibrous composite materials as homogeneous,anisotropic viscoelastic materials,significantly reducing computational time due to its analytical nature.This approach also enables precise determination of a homogenized anisotropic relaxation modulus and accurate capture of various viscoelastic responses under different loading conditions.Three sets of numerical examples,including unit cell tests,three-point beam bending tests,and torsion tests,are given to demonstrate the predictive performance of the homogenized viscoelastic model.Furthermore,the model is validated against experimental measurements,confirming its accuracy and reliability.展开更多
In this paper,we delve into a generalized higher order Camassa-Holm type equation,(or,an ghmCH equation for short).We establish local well-posedness for this equation under the condition that the initial data uo belon...In this paper,we delve into a generalized higher order Camassa-Holm type equation,(or,an ghmCH equation for short).We establish local well-posedness for this equation under the condition that the initial data uo belongs to the Sobolev space H'(R)for some s>2.In addition,we obtain the weak formulation of this equation and prove the existence of both single peakon solution and a multi-peakon dynamic system.展开更多
In this paper,we give a complete characterization of all self-adjoint domains of odd order differential operators on two intervals.These two intervals with all four endpoints are singular(one endpoint of each interval...In this paper,we give a complete characterization of all self-adjoint domains of odd order differential operators on two intervals.These two intervals with all four endpoints are singular(one endpoint of each interval is singular or all four endpoints are regulars are the special cases).And these extensions yield"new"self-adjoint operators,which involve interactions between the two intervals.展开更多
Alloying transition metals with Pt is an effective strategy for optimizing Pt-based catalysts toward the oxygen reduction reaction(ORR).Atomic ordered intermetallic compounds(IMC)provide unique electronic and geometri...Alloying transition metals with Pt is an effective strategy for optimizing Pt-based catalysts toward the oxygen reduction reaction(ORR).Atomic ordered intermetallic compounds(IMC)provide unique electronic and geometrical effects as well as stronger intermetallic interactions due to the ordered arrangement of metal atoms,thus exhibiting superior electrocata-lytic activity and durability.However,quantitatively analyzing the ordering degree of IMC and exploring the correlation between the ordering degree and ORR activity remains extremely challenging.Herein,a series of ternary Pt_(2)NiCo interme-tallic catalysts(o-Pt_(2)NiCo)with different ordering degree were synthesized by annealing temperature modulation.Among them,the o-Pt_(2)NiCo which annealed at 800℃for two hours exhibits the highest ordering degree and the optimal ORR ac-tivity,which the mass activity of o-Pt_(2)NiCo is 1.8 times and 2.8 times higher than that of disordered Pt_(2)NiCo alloy and Pt/C.Furthermore,the o-Pt_(2)NiCo still maintains 70.8%mass activity after 30,000 potential cycles.Additionally,the ORR activity test results for Pt_(2)NiCo IMC with different ordering degree also provide a positive correlation between the ordering degree and ORR activity.This work provides a prospective design direction for ternary Pt-based electrocatalysts.展开更多
Higher-order band topology not only enriches our understanding of topological phases but also unveils pioneering lower-dimensional boundary states,which harbors substantial potential for next-generation device applica...Higher-order band topology not only enriches our understanding of topological phases but also unveils pioneering lower-dimensional boundary states,which harbors substantial potential for next-generation device applications.The distinct electronic configurations and tunable attributes of two-dimensional materials position them as a quintessential platform for the realization of second-order topological insulators(SOTIs).This article provides an overview of the research progress in SOTIs within the field of two-dimensional electronic materials,focusing on the characterization of higher-order topological properties and the numerous candidate materials proposed in theoretical studies.These endeavors not only enhance our understanding of higher-order topological states but also highlight potential material systems that could be experimentally realized.展开更多
In this paper,a new technique is introduced to construct higher-order iterative methods for solving nonlinear systems.The order of convergence of some iterative methods can be improved by three at the cost of introduc...In this paper,a new technique is introduced to construct higher-order iterative methods for solving nonlinear systems.The order of convergence of some iterative methods can be improved by three at the cost of introducing only one additional evaluation of the function in each step.Furthermore,some new efficient methods with a higher-order of convergence are obtained by using only a single matrix inversion in each iteration.Analyses of convergence properties and computational efficiency of these new methods are made and testified by several numerical problems.By comparison,the new schemes are more efficient than the corresponding existing ones,particularly for large problem sizes.展开更多
In the third quarter of 2025,the orders index for textile machinery-compiled by ACIMIT's Economics Department(the Association of Italian Textile Machinery Manufacturers)-recorded a16%decrease compared to the same ...In the third quarter of 2025,the orders index for textile machinery-compiled by ACIMIT's Economics Department(the Association of Italian Textile Machinery Manufacturers)-recorded a16%decrease compared to the same period in 2024.In absolute terms,the index stood at 41.8 points(base year2021=100).The decline reflects negative performances in both the domestic and foreign markets.Specifically,on the domestic market,orders fell by 17%compared to the same quarter of the previous year,with the absolute index value reaching49.9points.展开更多
Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectiv...Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system.展开更多
On May 14th,following the U.S.adjustment of additional tariffs on Chinese goods,American buyers began stockpiling in earnest.Many cross-border e-commerce companies also received a surge of orders.At 7 PM,a bustling Ha...On May 14th,following the U.S.adjustment of additional tariffs on Chinese goods,American buyers began stockpiling in earnest.Many cross-border e-commerce companies also received a surge of orders.At 7 PM,a bustling Hangzhou-based cross-border e-commerce company was alive with multiple languages echoing through its live-streaming rooms as backend order numbers climbed steadily.展开更多
An orderly competition mechanism is used to change unexpected competition into predictable competition so as to reduce access collision during access process.The scheme is realized by learning,queuing,and accessing.Qu...An orderly competition mechanism is used to change unexpected competition into predictable competition so as to reduce access collision during access process.The scheme is realized by learning,queuing,and accessing.Queuing is the key step to reduce random and realize orderly competition.Related parameters leading to access random including the arrival rate,the delay requirements,the number of devices,and so on,are defined as queue factors in this paper.The queue factors are obtained from the improved double deep Q network(DDQN)algorithm which is proposed here by setting asynchronous weights of two target networks.By learning,the queue factors will guide the devices with diverse delay requirements to queue.Then the queued devices start the access process according to their learning optimal access slot and preamble.Different from traditional competition solutions,markov decision process of the orderly competition mechanism has only two states,which remarkably cuts down the back-off rate and reduces the access delay.The simulation results show that the access success rate of this method can be close to 100%before the system capacity approaches the maximum value.展开更多
The ground-state magnetic ordering of uranium mononitride(UN)remains a contentious topic due to the unexpected lack of crystallographic distortion in the traditionally accepted 1k antiferromagnetic(AFM)state.This disc...The ground-state magnetic ordering of uranium mononitride(UN)remains a contentious topic due to the unexpected lack of crystallographic distortion in the traditionally accepted 1k antiferromagnetic(AFM)state.This discrepancy casts doubt on the validity of the 1k magnetic ordering of UN.Here,we investigate the crystal structure,high-pressure phase transitions,and dynamical and mechanical properties of UN in its 1k and 3k AFM ground states using density functional theory(DFT).Our results reveal that the undistorted 3k AFM state of Fm3m within the DFT+U+SOC scheme is more consistent with experimental results.The Hubbard U and spin-orbit coupling(SOC)are critical for accurately capturing the crystal structure,high-pressure structural phase transition,and dynamical properties of UN.In addition,we have identified a new high-pressure magnetic phase transition from the nonmagnetic(NM)phase of R3m to the P63/mmc AFM state.Electronic structure analysis reveals that the magnetic ordering in the ground state is primarily linked to variations in partial 5f orbital distributions.Our calculations provide valuable theoretical insights into the complex magnetic structures of a typical strongly correlated uranium-based compound.Moreover,they provide a framework for understanding other similar actinide systems.展开更多
Music recommendation systems are essential due to the vast amount of music available on streaming platforms,which can overwhelm users trying to find new tracks that match their preferences.These systems analyze users...Music recommendation systems are essential due to the vast amount of music available on streaming platforms,which can overwhelm users trying to find new tracks that match their preferences.These systems analyze users’emotional responses,listening habits,and personal preferences to provide personalized suggestions.A significant challenge they face is the“cold start”problem,where new users have no past interactions to guide recommendations.To improve user experience,these systems aimto effectively recommendmusic even to such users by considering their listening behavior and music popularity.This paper introduces a novel music recommendation system that combines order clustering and a convolutional neural network,utilizing user comments and rankings as input.Initially,the system organizes users into clusters based on semantic similarity,followed by the utilization of their rating similarities as input for the convolutional neural network.This network then predicts ratings for unreviewed music by users.Additionally,the system analyses user music listening behaviour and music popularity.Music popularity can help to address cold start users as well.Finally,the proposed method recommends unreviewed music based on predicted high rankings and popularity,taking into account each user’s music listening habits.The proposed method combines predicted high rankings and popularity by first selecting popular unreviewedmusic that themodel predicts to have the highest ratings for each user.Among these,the most popular tracks are prioritized,defined by metrics such as frequency of listening across users.The number of recommended tracks is aligned with each user’s typical listening rate.The experimental findings demonstrate that the new method outperformed other classification techniques and prior recommendation systems,yielding a mean absolute error(MAE)rate and rootmean square error(RMSE)rate of approximately 0.0017,a hit rate of 82.45%,an average normalized discounted cumulative gain(nDCG)of 82.3%,and a prediction accuracy of new ratings at 99.388%.展开更多
Higher-order topological insulators,which host topologically protected states at boundaries that are at least two dimensions lower than the bulk,are an emerging class of topological materials.They provide great opport...Higher-order topological insulators,which host topologically protected states at boundaries that are at least two dimensions lower than the bulk,are an emerging class of topological materials.They provide great opportunities for exploring novel topological phenomena and fascinating applications.Utilizing a low-temperature scanning tunneling microscope,we construct breathing-kagome lattices with Fe adatoms on Ag(111)and investigate their electronic properties.We observe the higher-order topological boundary states in the topological phase but not in the trivial one,which is consistent with the theory.These states are found to be robust against the removal of bulk or edge adatoms.Further,we show the arbitrary positioning of these states either at corner,edge,or bulk sites by slightly modifying their neighbors.Our study not only demonstrates the formation and robustness of the electronic higher-order topological boundary states in real atomic systems but also provides a route for controlling their positions.展开更多
Chemical short-range order(SRO),a phenomenon at the atomic scale resulting from inhomogeneities in the local chemical environment,is usually studied using machine learning force field-based molecular dynamics simulati...Chemical short-range order(SRO),a phenomenon at the atomic scale resulting from inhomogeneities in the local chemical environment,is usually studied using machine learning force field-based molecular dynamics simulations due to the limitations of experimental methods.To promote the reliable application of machine potentials in high-entropy alloy simulations,first,this work uses NEP models trained on two different datasets to predict the SRO coefficients of NbMoTaW.The results show that within the same machine learning framework,there are significant differences in the prediction of SRO coefficients for the Nb-Nb atomic pair.Subsequently,this work predicts the SRO coefficients of NbMoTaW using the NEP model and the SNAP model,both of which are trained on the same dataset.The results reveal significant discrepancies in SRO predictions for like-element pairs(e.g.,Nb-Nb and W-W)between the two potentials,despite the identical training data.The findings of this study indicate that discrepancies in the prediction results of SRO coefficients can arise from either the same machine learning framework trained on different datasets or different learning frameworks trained on the same dataset.This reflects possible incompleteness in the current training set's coverage of local chemical environments at the atomic scale.Future research should establish unified evaluation standards to assess the capability of training sets to accurately describe complex atomic-scale behaviors such as SRO.展开更多
The performance of organic solar cells is significantly influenced by the acceptor molecular packing properties within the active layers,which is essential for optimizing charge dynamics and photovoltaic performance.H...The performance of organic solar cells is significantly influenced by the acceptor molecular packing properties within the active layers,which is essential for optimizing charge dynamics and photovoltaic performance.However,achieving precise control over this packaging structure presents a considerable challenge.Herein,we propose a dual additive strategy utilizing dibenzofuran and halogenated naphthalene to systematically manipulate molecular packing orientation and enhance the long-range molecular packing order of the acceptors.Dibenzofuran is crucial in promoting crystallinity within the material,facilitating the formation of an ordered structure,while halogenated naphthalene regulates the orientation of the molecules,ensuring proper alignment.Specifically,the combination of dibenzofuran and 1-chloronaphthalene promotes edge-on molecular packing and enhances the formation of nanofibrillar structures with improved order,leading to improved charge transport and device performance.Implementing this strategy in devices composed of PM6 and L8-BO has yielded a power conversion efficiency of 19.58%,accompanied by long-term stability.Similarly,1-fluoronaphthalene has also demonstrated effectiveness in improving molecular orientation and overall device efficiency,demonstrating the robustness of this dual additive strategy.By addressing the challenges associated with molecular packing and orientation in active layers,our result contributes valuable insights into optimizing organic solar cells for practical applications.展开更多
In this paper,we study the weighted higher order semilinear equation in an exterior domain(-△)^(m)u=|x|^(α)g(u)in R^(N)\B_(R_(0)),where N≥1,m≥2 are integers,α>-2m,g is a continuous and nondecreasing function i...In this paper,we study the weighted higher order semilinear equation in an exterior domain(-△)^(m)u=|x|^(α)g(u)in R^(N)\B_(R_(0)),where N≥1,m≥2 are integers,α>-2m,g is a continuous and nondecreasing function in(0,+∞)and positive in(0,+∞),B_(R_(0))is the ball of the radius R0 centered at the origin.We prove that a positive supersolution of the problem which verifies(-△)_(i)u>0 in R^(N)\B_(R_(0))(i=0,…,m-1)exists if and only if N>2m and∫_(0)^(δ)g(t)/t^(2(N-m)+α/N-2m)dt<∞,,for someδ>0.We further obtain some existence and nonexistence results for the positive solution to the Dirichlet problem when g(u)=u^(p)with p>1,by using the Pohozaev identity and an embedding lemma of radial Sobolev spaces.展开更多
Weak interactions prevent the magnetic particles from achieving excellent electromagnetic wave absorp-tion(EMA)at a low filler loading(FL).The construction of one-dimensional magnetic metal fibers(1D-MMFs)contributes ...Weak interactions prevent the magnetic particles from achieving excellent electromagnetic wave absorp-tion(EMA)at a low filler loading(FL).The construction of one-dimensional magnetic metal fibers(1D-MMFs)contributes to the formation of an electromagnetic(EM)coupling network,enhancing EM properties at a low FL.However,precisely controlling the length of 1D-MMFs to regulate permittivity at low FL poses a challenge.Herein,a novel magnetic field-assisted growth strategy was used to fabricate Co-based fibers with adjustable permittivity and aspect ratios.With a variety of FL changes,centimeter-level Co long fibers(Co-lf)consistently exhibited higher permittivity than Co particles and Co short fibers due to the enhancement of the effective EM coupling.The Co-lf exhibits excellent EMA performance(-54.85 dB,5.8 GHz)at 10 wt.%FL.Meanwhile,heterogeneous interfaces were introduced to increase the interfacial polarization through a fine phosphorylation design,resulting in elevated EMA performances(-51.50 dB,6.6 GHz)at 10 wt.%FL for Co_(2)P/Co long fibers.This study improves the orderliness of the particle arrangement by regulating the length of 1D-MMFs,which affects the behavior of electrons inside the fibers,providing a new perspective for improving the EMA properties of magnetic materials at a low FL.展开更多
基金supported by the Chinese Academy of Science(CAS)Key Technology Talent Program(No.2021000022)。
文摘The synchrotron radiation beamline BL17B of the National Facility for Protein Science(NFPS)in Shanghai,situated at the Shanghai Synchrotron Radiation Facility(SSRF),was originally designed for diffraction experiments and accommodates techniques including single-crystal diffraction,powder diffraction,and grazing-incidence wide-angle X-ray scattering(GIWAXS)to enable the characterization of long-range ordered atomic structures.The academic community associated with BL17B engages in research domains encompassing biology,environment,energy,and materials,and a pronounced demand for characterizing short-range ordered structures exists.To address these requirements,BL17B established an advanced X-ray absorption fine structure(XAFS)experimental platform that enabled it to address a wide range of systems,from crystalline to amorphous and from long-range order to short-range order.The XAFS platform allows simultaneous XAFS data acquisition for both the transmission and fluorescence modes within an energy range of 5-23 keV,encompassing the K-edges of titanium to ruthenium and the L3-edges of cesium to bismuth.The platform exemplifies high levels of automation achieved through automated sample assessment and data collection based on large-capacity sample wheels that facilitate remote sample loading.When integrated with a highly integrated control system that simplifies experimental preparation and data collection,the XAFS platform significantly bolsters experimental efficiency and enhances user experience.Notably,the platform boasts an impressively low extended X-ray absorption fine structure(EXAFS)detection limit of 0.04 wt%for dilute copper phthalocyanine(CuPc)samples and an even more remarkable X-ray absorption near edge structure(XANES)detection threshold of 0.01 wt%.These results demonstrate the methodology?s reliability in low-concentration sample analysis,confirming its capability to generate high-quality XAFS data.
基金supported by the National Natural Science Foundation of China(Grant Nos.12022508,12074394,and 22125604)Shanghai Supercomputer Center of ChinaShanghai Snowlake Technology Co.Ltd.
文摘The stable nanobubbles adhered to mineral surfaces may facilitate their efficient separation via flotation in the mining industry.However,the state of nanobubbles on mineral solid surfaces is still elusive.In this study,molecular dynamics(MD)simulations are employed to examine mineral-like model surfaces with varying degrees of hydrophobicity,modulated by surface charges,to elucidate the adsorption behavior of nanobubbles at the interface.Our findings not only contribute to the fundamental understanding of nanobubbles but also have potential applications in the mining industry.We observed that as the surface charge increases,the contact angle of the nanobubbles increases accordingly with shape transformation from a pancake-like gas film to a cap-like shape,and ultimately forming a stable nanobubble upon an ordered water monolayer.When the solid–water interactions are weak with a small partial charge,the hydrophobic gas(N_(2))molecules accumulate near the solid surfaces.However,we have found,for the first time,that gas molecules assemble a nanobubble on the water monolayer adjacent to the solid surfaces with large partial charges.Such phenomena are attributed to the formation of a hydrophobic water monolayer with a hydrogen bond network structure near the surface.
基金The National Natural Science Foundation of China (No. 51908107)。
文摘To enhance the prediction accuracy of unsteady wakes behind wind turbines,a novel reduced-order model is proposed by integrating a multifunctional recurrent fuzzy neural network(MFRFNN)and proper orthogonal decom-position(POD).First,POD is employed to reduce the di-mensionality of the wind field data,extracting spatiotempo-rally correlated modal coefficients and modes.These reduced-order variables can effectively capture the essential features of unsteady wake behaviors.Next,MFRFNN is utilized to predict the time series of modal coefficients.Fi-nally,by combining the predicted modal coefficients with their corresponding modes,a flow field is reconstructed,al-lowing accurate prediction of unsteady wake dynamics.The predicted wake data exhibit high consistency with large eddy simulation results in both the near-and far-wake re-gions and outperform existing data-driven methods.This ap-proach offers significant potential for optimizing wind farm design and provides a new solution for the precise prediction of wind turbine wake behavior.
基金support by the National Key R&D Program of China(Grant No.2023YFA1008901)the National Natural Science Foundation of China(Grant Nos.11988102,12172009)is gratefully acknowledged.
文摘In this manuscript,we propose an analytical equivalent linear viscoelastic constitutive model for fiber-reinforced composites,bypassing general computational homogenization.The method is based on the reduced-order homogenization(ROH)approach.The ROH method typically involves solving multiple finite element problems under periodic conditions to evaluate elastic strain and eigenstrain influence functions in an‘off-line’stage,which offers substantial cost savings compared to direct computational homogenization methods.Due to the unique structure of the fibrous unit cell,“off-line”stage calculation can be eliminated by influence functions obtained analytically.Introducing the standard solid model to the ROH method enables the creation of a comprehensive analytical homogeneous viscoelastic constitutive model.This method treats fibrous composite materials as homogeneous,anisotropic viscoelastic materials,significantly reducing computational time due to its analytical nature.This approach also enables precise determination of a homogenized anisotropic relaxation modulus and accurate capture of various viscoelastic responses under different loading conditions.Three sets of numerical examples,including unit cell tests,three-point beam bending tests,and torsion tests,are given to demonstrate the predictive performance of the homogenized viscoelastic model.Furthermore,the model is validated against experimental measurements,confirming its accuracy and reliability.
文摘In this paper,we delve into a generalized higher order Camassa-Holm type equation,(or,an ghmCH equation for short).We establish local well-posedness for this equation under the condition that the initial data uo belongs to the Sobolev space H'(R)for some s>2.In addition,we obtain the weak formulation of this equation and prove the existence of both single peakon solution and a multi-peakon dynamic system.
基金Supported by NSFC (No.12361027)NSF of Inner Mongolia (No.2018MS01021)+1 种基金NSF of Shandong Province (No.ZR2020QA009)Science and Technology Innovation Program for Higher Education Institutions of Shanxi Province (No.2024L533)。
文摘In this paper,we give a complete characterization of all self-adjoint domains of odd order differential operators on two intervals.These two intervals with all four endpoints are singular(one endpoint of each interval is singular or all four endpoints are regulars are the special cases).And these extensions yield"new"self-adjoint operators,which involve interactions between the two intervals.
基金supported by the National Natural Science Foundation(22279036)the Innovation and Talent Recruitment Base of New Energy Chemistry and Device(B21003).
文摘Alloying transition metals with Pt is an effective strategy for optimizing Pt-based catalysts toward the oxygen reduction reaction(ORR).Atomic ordered intermetallic compounds(IMC)provide unique electronic and geometrical effects as well as stronger intermetallic interactions due to the ordered arrangement of metal atoms,thus exhibiting superior electrocata-lytic activity and durability.However,quantitatively analyzing the ordering degree of IMC and exploring the correlation between the ordering degree and ORR activity remains extremely challenging.Herein,a series of ternary Pt_(2)NiCo interme-tallic catalysts(o-Pt_(2)NiCo)with different ordering degree were synthesized by annealing temperature modulation.Among them,the o-Pt_(2)NiCo which annealed at 800℃for two hours exhibits the highest ordering degree and the optimal ORR ac-tivity,which the mass activity of o-Pt_(2)NiCo is 1.8 times and 2.8 times higher than that of disordered Pt_(2)NiCo alloy and Pt/C.Furthermore,the o-Pt_(2)NiCo still maintains 70.8%mass activity after 30,000 potential cycles.Additionally,the ORR activity test results for Pt_(2)NiCo IMC with different ordering degree also provide a positive correlation between the ordering degree and ORR activity.This work provides a prospective design direction for ternary Pt-based electrocatalysts.
基金supported by the National Natu-ral Science Foundation of China(Grants No.12174220 and No.12074217)the Shandong Provincial Science Foundation for Excellent Young Scholars(Grant No.ZR2023YQ001)+1 种基金the Taishan Young Scholar Program of Shandong Provincethe Qilu Young Scholar Pro-gram of Shandong University.
文摘Higher-order band topology not only enriches our understanding of topological phases but also unveils pioneering lower-dimensional boundary states,which harbors substantial potential for next-generation device applications.The distinct electronic configurations and tunable attributes of two-dimensional materials position them as a quintessential platform for the realization of second-order topological insulators(SOTIs).This article provides an overview of the research progress in SOTIs within the field of two-dimensional electronic materials,focusing on the characterization of higher-order topological properties and the numerous candidate materials proposed in theoretical studies.These endeavors not only enhance our understanding of higher-order topological states but also highlight potential material systems that could be experimentally realized.
基金Supported by the National Natural Science Foundation of China(12061048)NSF of Jiangxi Province(20232BAB201026,20232BAB201018)。
文摘In this paper,a new technique is introduced to construct higher-order iterative methods for solving nonlinear systems.The order of convergence of some iterative methods can be improved by three at the cost of introducing only one additional evaluation of the function in each step.Furthermore,some new efficient methods with a higher-order of convergence are obtained by using only a single matrix inversion in each iteration.Analyses of convergence properties and computational efficiency of these new methods are made and testified by several numerical problems.By comparison,the new schemes are more efficient than the corresponding existing ones,particularly for large problem sizes.
文摘In the third quarter of 2025,the orders index for textile machinery-compiled by ACIMIT's Economics Department(the Association of Italian Textile Machinery Manufacturers)-recorded a16%decrease compared to the same period in 2024.In absolute terms,the index stood at 41.8 points(base year2021=100).The decline reflects negative performances in both the domestic and foreign markets.Specifically,on the domestic market,orders fell by 17%compared to the same quarter of the previous year,with the absolute index value reaching49.9points.
基金supported in part by the National Natural Science Foundation of China(62173255,62188101)Shenzhen Key Laboratory of Control Theory and Intelligent Systems(ZDSYS20220330161800001)
文摘Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system.
文摘On May 14th,following the U.S.adjustment of additional tariffs on Chinese goods,American buyers began stockpiling in earnest.Many cross-border e-commerce companies also received a surge of orders.At 7 PM,a bustling Hangzhou-based cross-border e-commerce company was alive with multiple languages echoing through its live-streaming rooms as backend order numbers climbed steadily.
基金supported by Key Technologies R&D Program of Jiangsu(Prospective and Key Technologies for Industry)(BE2022067,BE2022067-1 and BE2022067-2)National Natural Science Foundation of China(No.61771255)Provincial and Ministerial Key Laboratory Open Project under Grant No.20190904.
文摘An orderly competition mechanism is used to change unexpected competition into predictable competition so as to reduce access collision during access process.The scheme is realized by learning,queuing,and accessing.Queuing is the key step to reduce random and realize orderly competition.Related parameters leading to access random including the arrival rate,the delay requirements,the number of devices,and so on,are defined as queue factors in this paper.The queue factors are obtained from the improved double deep Q network(DDQN)algorithm which is proposed here by setting asynchronous weights of two target networks.By learning,the queue factors will guide the devices with diverse delay requirements to queue.Then the queued devices start the access process according to their learning optimal access slot and preamble.Different from traditional competition solutions,markov decision process of the orderly competition mechanism has only two states,which remarkably cuts down the back-off rate and reduces the access delay.The simulation results show that the access success rate of this method can be close to 100%before the system capacity approaches the maximum value.
基金supported by the National Natural Science Foundation of China(Grant Nos.12204482 and U2430211)the Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi(Grant No.2020L0537)the Fundamental Research Program of Shanxi Province(Grant No.202103021224250)the Hainan Provincial Natural Science Foundation of China(Grant No.225MS076).
文摘The ground-state magnetic ordering of uranium mononitride(UN)remains a contentious topic due to the unexpected lack of crystallographic distortion in the traditionally accepted 1k antiferromagnetic(AFM)state.This discrepancy casts doubt on the validity of the 1k magnetic ordering of UN.Here,we investigate the crystal structure,high-pressure phase transitions,and dynamical and mechanical properties of UN in its 1k and 3k AFM ground states using density functional theory(DFT).Our results reveal that the undistorted 3k AFM state of Fm3m within the DFT+U+SOC scheme is more consistent with experimental results.The Hubbard U and spin-orbit coupling(SOC)are critical for accurately capturing the crystal structure,high-pressure structural phase transition,and dynamical properties of UN.In addition,we have identified a new high-pressure magnetic phase transition from the nonmagnetic(NM)phase of R3m to the P63/mmc AFM state.Electronic structure analysis reveals that the magnetic ordering in the ground state is primarily linked to variations in partial 5f orbital distributions.Our calculations provide valuable theoretical insights into the complex magnetic structures of a typical strongly correlated uranium-based compound.Moreover,they provide a framework for understanding other similar actinide systems.
基金funded by the National Nature Sciences Foundation of China with Grant No.42250410321。
文摘Music recommendation systems are essential due to the vast amount of music available on streaming platforms,which can overwhelm users trying to find new tracks that match their preferences.These systems analyze users’emotional responses,listening habits,and personal preferences to provide personalized suggestions.A significant challenge they face is the“cold start”problem,where new users have no past interactions to guide recommendations.To improve user experience,these systems aimto effectively recommendmusic even to such users by considering their listening behavior and music popularity.This paper introduces a novel music recommendation system that combines order clustering and a convolutional neural network,utilizing user comments and rankings as input.Initially,the system organizes users into clusters based on semantic similarity,followed by the utilization of their rating similarities as input for the convolutional neural network.This network then predicts ratings for unreviewed music by users.Additionally,the system analyses user music listening behaviour and music popularity.Music popularity can help to address cold start users as well.Finally,the proposed method recommends unreviewed music based on predicted high rankings and popularity,taking into account each user’s music listening habits.The proposed method combines predicted high rankings and popularity by first selecting popular unreviewedmusic that themodel predicts to have the highest ratings for each user.Among these,the most popular tracks are prioritized,defined by metrics such as frequency of listening across users.The number of recommended tracks is aligned with each user’s typical listening rate.The experimental findings demonstrate that the new method outperformed other classification techniques and prior recommendation systems,yielding a mean absolute error(MAE)rate and rootmean square error(RMSE)rate of approximately 0.0017,a hit rate of 82.45%,an average normalized discounted cumulative gain(nDCG)of 82.3%,and a prediction accuracy of new ratings at 99.388%.
基金supported by the National Key R&D Program of China(Grant Nos.2024YFA140850,2022YFA1403601,and 2023YFC2410501)the National Natural Science Foundation of China(Grants Nos.12241402,12474059,12274203,12374113,and 12274204)。
文摘Higher-order topological insulators,which host topologically protected states at boundaries that are at least two dimensions lower than the bulk,are an emerging class of topological materials.They provide great opportunities for exploring novel topological phenomena and fascinating applications.Utilizing a low-temperature scanning tunneling microscope,we construct breathing-kagome lattices with Fe adatoms on Ag(111)and investigate their electronic properties.We observe the higher-order topological boundary states in the topological phase but not in the trivial one,which is consistent with the theory.These states are found to be robust against the removal of bulk or edge adatoms.Further,we show the arbitrary positioning of these states either at corner,edge,or bulk sites by slightly modifying their neighbors.Our study not only demonstrates the formation and robustness of the electronic higher-order topological boundary states in real atomic systems but also provides a route for controlling their positions.
基金Project supported by the Hunan Provincial Natural Science Foundation(Grant Nos.2024JJ6190 and 2024JK2007-1)。
文摘Chemical short-range order(SRO),a phenomenon at the atomic scale resulting from inhomogeneities in the local chemical environment,is usually studied using machine learning force field-based molecular dynamics simulations due to the limitations of experimental methods.To promote the reliable application of machine potentials in high-entropy alloy simulations,first,this work uses NEP models trained on two different datasets to predict the SRO coefficients of NbMoTaW.The results show that within the same machine learning framework,there are significant differences in the prediction of SRO coefficients for the Nb-Nb atomic pair.Subsequently,this work predicts the SRO coefficients of NbMoTaW using the NEP model and the SNAP model,both of which are trained on the same dataset.The results reveal significant discrepancies in SRO predictions for like-element pairs(e.g.,Nb-Nb and W-W)between the two potentials,despite the identical training data.The findings of this study indicate that discrepancies in the prediction results of SRO coefficients can arise from either the same machine learning framework trained on different datasets or different learning frameworks trained on the same dataset.This reflects possible incompleteness in the current training set's coverage of local chemical environments at the atomic scale.Future research should establish unified evaluation standards to assess the capability of training sets to accurately describe complex atomic-scale behaviors such as SRO.
基金the financial support from the National Natural Science Foundation of China(62275057)the Guangxi Natural Science Foundation(2023GXNSFFA026004)+2 种基金the Guangxi Talent Program("Highland of Innovation Talents")the Shenzhen High-tech Development Special Plan-Pingshan Districts Innovation Platform Project(29853M-KCJ-2023-002-04)Industry and Energy(MOTIE),Republic of Korea(Project No.:RS-2025-02413058)。
文摘The performance of organic solar cells is significantly influenced by the acceptor molecular packing properties within the active layers,which is essential for optimizing charge dynamics and photovoltaic performance.However,achieving precise control over this packaging structure presents a considerable challenge.Herein,we propose a dual additive strategy utilizing dibenzofuran and halogenated naphthalene to systematically manipulate molecular packing orientation and enhance the long-range molecular packing order of the acceptors.Dibenzofuran is crucial in promoting crystallinity within the material,facilitating the formation of an ordered structure,while halogenated naphthalene regulates the orientation of the molecules,ensuring proper alignment.Specifically,the combination of dibenzofuran and 1-chloronaphthalene promotes edge-on molecular packing and enhances the formation of nanofibrillar structures with improved order,leading to improved charge transport and device performance.Implementing this strategy in devices composed of PM6 and L8-BO has yielded a power conversion efficiency of 19.58%,accompanied by long-term stability.Similarly,1-fluoronaphthalene has also demonstrated effectiveness in improving molecular orientation and overall device efficiency,demonstrating the robustness of this dual additive strategy.By addressing the challenges associated with molecular packing and orientation in active layers,our result contributes valuable insights into optimizing organic solar cells for practical applications.
文摘In this paper,we study the weighted higher order semilinear equation in an exterior domain(-△)^(m)u=|x|^(α)g(u)in R^(N)\B_(R_(0)),where N≥1,m≥2 are integers,α>-2m,g is a continuous and nondecreasing function in(0,+∞)and positive in(0,+∞),B_(R_(0))is the ball of the radius R0 centered at the origin.We prove that a positive supersolution of the problem which verifies(-△)_(i)u>0 in R^(N)\B_(R_(0))(i=0,…,m-1)exists if and only if N>2m and∫_(0)^(δ)g(t)/t^(2(N-m)+α/N-2m)dt<∞,,for someδ>0.We further obtain some existence and nonexistence results for the positive solution to the Dirichlet problem when g(u)=u^(p)with p>1,by using the Pohozaev identity and an embedding lemma of radial Sobolev spaces.
基金supported by the National Key Research and Development Program of China(No.2024YFE0100600)the National Natural Science Foundation of China(No.52373303)+1 种基金the Shanghai Municipal Science and Technology Major Project(No.2021SHZDZX0100)the Fundamental Research Funds for the Central Universities and the Interdisciplinary Joint Research and Development Project of Tongji University(No.2022-4-ZD-01).
文摘Weak interactions prevent the magnetic particles from achieving excellent electromagnetic wave absorp-tion(EMA)at a low filler loading(FL).The construction of one-dimensional magnetic metal fibers(1D-MMFs)contributes to the formation of an electromagnetic(EM)coupling network,enhancing EM properties at a low FL.However,precisely controlling the length of 1D-MMFs to regulate permittivity at low FL poses a challenge.Herein,a novel magnetic field-assisted growth strategy was used to fabricate Co-based fibers with adjustable permittivity and aspect ratios.With a variety of FL changes,centimeter-level Co long fibers(Co-lf)consistently exhibited higher permittivity than Co particles and Co short fibers due to the enhancement of the effective EM coupling.The Co-lf exhibits excellent EMA performance(-54.85 dB,5.8 GHz)at 10 wt.%FL.Meanwhile,heterogeneous interfaces were introduced to increase the interfacial polarization through a fine phosphorylation design,resulting in elevated EMA performances(-51.50 dB,6.6 GHz)at 10 wt.%FL for Co_(2)P/Co long fibers.This study improves the orderliness of the particle arrangement by regulating the length of 1D-MMFs,which affects the behavior of electrons inside the fibers,providing a new perspective for improving the EMA properties of magnetic materials at a low FL.
