The reactions of the four-coordinated macrocyclic copper complex [CuL]（ClO4）2（L = 1,4,8,11-tetraazacyclotetradecane） with NH4VO3 under different conditions gave three inorganic-organic hybrid materials of [CuL][VO...The reactions of the four-coordinated macrocyclic copper complex [CuL]（ClO4）2（L = 1,4,8,11-tetraazacyclotetradecane） with NH4VO3 under different conditions gave three inorganic-organic hybrid materials of [CuL][VO3]2·2.33H2O（1）, [CuL]3[V（10）O（28）]·8H2O（2） and [Cu L]3[V6O（18）]·8H2O（3）. Single-crystal X-ray diffraction analyses reveal that three diverse vanadium polyoxoanions, [V6O（18）]6- ring, [V（10）O（28）]6- cluster, and [V（12）O（35）]^10- ring, were isolated from the same reactant NH4VO3 under different conditions. The [CuL]^2＋ bridges the [V10O28]6- clusters to form a two-dimensional sheet in 2, and link the [V6O（18）]^6- rings in 1 and [V（12）O（35）]^10- rings in 3 into three-dimensional frameworks, respectively.展开更多
Hybrid materials incorporating Eu-(TTA)(3). 2H(2)O (7hereafter designated as Eu-TTA, with TTA: thenoyltrifluoroacetone) in unmodified or modified MCM-41 by 3-aminopropyl-triethoxysilane (APTES) were prepared by impreg...Hybrid materials incorporating Eu-(TTA)(3). 2H(2)O (7hereafter designated as Eu-TTA, with TTA: thenoyltrifluoroacetone) in unmodified or modified MCM-41 by 3-aminopropyl-triethoxysilane (APTES) were prepared by impregnation method. The obtained materials were characterized using X-ray diffraction (XRD), IR and diffuse reflectance spectroscopy and luminescence spectra. All the hybrid samples exhibited the characteristic emission bands of EU3+ under UV light excitation at room temperature, and the excitation spectra showed significant blue-shifts compared to the pure rare-earth complex. Although the red emission intensity in the modified hybrid was almost the half of the red emission intensity in the pure Eu-TTA complex at room temperature, the hybrid showed a much higher thermal stability due to the shielding character of the MCM-41 host.展开更多
Thework presents the electronic structure computations and optical spectroscopy studies of half-Heusler ScNiBi and YNiBi compounds.Our first-principles computations of the electronic structures were based on density f...Thework presents the electronic structure computations and optical spectroscopy studies of half-Heusler ScNiBi and YNiBi compounds.Our first-principles computations of the electronic structures were based on density functional theory accounting for spin-orbit coupling.These compounds are computed to be semiconductors.The calculated gap values make ScNiBi and YNiBi valid for thermoelectric and optoelectronic applications and as selective filters.In ScNiBi and YNiBi,an intense peak at the energy of−2 eV is composed of theNi 3d states in the conduction band,and the valence band mostly contains these states with some contributions from the Bi 6p and Sc 3d or Y 4d electronic states.These states participate in the formation of the indirect gap of 0.16 eV(ScNiBi)and 0.18 eV(YNiBi).Within the spectral ellipsometry technique in the interval 0.22–15μm of wavelength,the optical functions of materials are studied,and their dispersion features are revealed.A good matching of the experimental and modeled optical conductivity spectra allowed us to analyze orbital contributions.The abnormally low optical absorption observed in the low-energy region of the spectrum is referred to as the results of band calculations indicating a small density of electronic states near the Fermi energy of these complex materials.展开更多
High-resolution imaging tools have revolutionized energy science by enabling direct visualization of local chemical and physical transformations across scales in highly complex material systems�from atomic rearrangeme...High-resolution imaging tools have revolutionized energy science by enabling direct visualization of local chemical and physical transformations across scales in highly complex material systems�from atomic rearrangements at catalytic surfaces and interfaces to mesoscale heterogeneities within battery electrodes.展开更多
Manufacturing of composite materials is usually accompanied with residual stresses.These stresses should be evaluated and assessed.To this end,a micromechanical model for periodic material whose temperature dependent ...Manufacturing of composite materials is usually accompanied with residual stresses.These stresses should be evaluated and assessed.To this end,a micromechanical model for periodic material whose temperature dependent constituents behave as thermorheologically complex materials(TCM)has been developed.This model,referred as the high fidelity generalized method of cells(HFGMC),takes into account the detailed interaction between the fiber and resin,their volume ratios,the fibers distribution and their waviness.This model is linked,in conjunction with a special UMAT subroutine,to the ABAQUS finite element code for prediction of the response of thermoviscoelastic composite structures during cool down process.The present investigation shows the effect of the cool down rate on the residual stress developed in the composite cylindrical structures.展开更多
With the techniques provided by the complex my method,like co,nplex ray expansion, complex mytracing,complex my paraxial approximation, etc.,the back scatter of dihedral corner reflectors is evaluated.Numerical result...With the techniques provided by the complex my method,like co,nplex ray expansion, complex mytracing,complex my paraxial approximation, etc.,the back scatter of dihedral corner reflectors is evaluated.Numerical results show that this method gives good and useful RCS prediction of the targets.展开更多
This paper demonstrates a new interpretation of the material purchasing management system(MPMS) from the perspective of complex adaptive systems(CAS).Within the framework of CAS,the authors design the self-adaptive me...This paper demonstrates a new interpretation of the material purchasing management system(MPMS) from the perspective of complex adaptive systems(CAS).Within the framework of CAS,the authors design the self-adaptive mechanism of the MPMS responding to the changing environment,such as the change of the price,by using risk measurement theory,modern portfolio theory(MPT) and the information of the material's modifying priority.As a bottom-up systems view,CAS focuses on the individual level and studies system's overall complexity by analyzing the mutual competition and adaptation among the individuals.This paper demonstrates a quantitative description of CAS by discussing the MPMS which can be viewed as a kind of CAS,and makes numerical simulations of Daqing oilfield MPMS.Compared to the benchmarks,the authors set the simulations show that the self-adaptive mechanism adapts well to the change of the material's market price.Hence,this paper accomplishes a numerical simulation of CAS's quantitative self-adaptive mechanism responding to the environment's change.展开更多
Measuring fluctuations in matter’s low-energy excitations is the key to unveiling the nature of the non-equilibrium response of materials.A promising outlook in this respect is offered by spectroscopic methods that a...Measuring fluctuations in matter’s low-energy excitations is the key to unveiling the nature of the non-equilibrium response of materials.A promising outlook in this respect is offered by spectroscopic methods that address matter fluctuations by exploiting the statistical nature of light-matter interactions with weak few-photon probes.Here we report the first implementation of ultrafast phase randomized tomography,combining pump-probe experiments with quantum optical state tomography,to measure the ultrafast non-equilibrium dynamics in complex materials.Our approach utilizes a time-resolved multimode heterodyne detection scheme with phase-randomized coherent ultrashort laser pulses,overcoming the limitations of phase-stable configurations and enabling a robust reconstruction of the statistical distribution of phase-averaged optical observables.This methodology is validated by measuring the coherent phonon response inα-quartz.By tracking the dynamics of the shot-noise limited photon number distribution of fewphoton probes with ultrafast resolution,our results set an upper limit to the non-classical features of phononic state inα-quartz and provide a pathway to access non-equilibrium quantum fluctuations in more complex quantum materials.展开更多
Artificial neural network(ANN)potentials enable accurate atomistic simulations of complex materials at unprecedented scales,but training them for potential energy surfaces(PES)of diverse chemical environments remains ...Artificial neural network(ANN)potentials enable accurate atomistic simulations of complex materials at unprecedented scales,but training them for potential energy surfaces(PES)of diverse chemical environments remains computationally intensive,especially when the PES gradients are trained on atomic force data.Here,we present an efficient methodology incorporating forces intoANNtraining by translating them to synthetic energy data using Gaussian process regression(GPR),leading to accurate PES models with fewer additional first-principles calculations and a reduced computational effort for training.We evaluated the method on hybrid density-functional theory data for ethylene carbonate(EC)molecules and their interfaces with Li metal,which are relevant for Li-metal batteries.The GPR-ANN potentials achieved an accuracy comparable to fully force-trained ANN potentials with a significantly reduced computational and memory overhead,establishing the method as a powerful and scalable framework for constructing high-fidelity ANN potentials for complex materials systems.展开更多
There are currently many materials for treating residual antibiotics in the environment, but none of them can specifically remove antibiotics. In addition, these materials are not sensitive enough to low concentration...There are currently many materials for treating residual antibiotics in the environment, but none of them can specifically remove antibiotics. In addition, these materials are not sensitive enough to low concentrations of antibiotics. Here we show that a sensitive and specific material was developed by the preparation of magnetic Fe_(3)O_(4)-PAMAM-antibody complexes for treating tetracycline. The prepared antibody complexes can specifically treat tetracycline from aqueous solutions and the tetracycline removal ability by adsorption was also investigated. Controlled experiments were carried out with the effects of solution pH, temperature, and initial concentration of the tetracycline. The tetracycline was completely removed within 35 min at room temperature 30 ℃ with the maximum removal rate of almost 100%. Therefore, this material for specifically combining antigen and antibody to treat tetracycline indicated good application prospects for the waste water treatment.展开更多
Density-functional theory with extended Hubbard functionals(DFT+U+V)provides a robust framework to accurately describe complex materials containing transition-metal or rare-earth elements.It does so by mitigating self...Density-functional theory with extended Hubbard functionals(DFT+U+V)provides a robust framework to accurately describe complex materials containing transition-metal or rare-earth elements.It does so by mitigating self-interaction errors inherent to semi-local functionals which are particularly pronounced in systems with partially-filled d and f electronic states.However,achieving accuracy in this approach hinges upon the accurate determination of the on-site U and inter-site V Hubbard parameters.In practice,these are obtained either by semi-empirical tuning,requiring prior knowledge,or,more correctly,by using predictive but expensive first-principles calculations.Here,we present a machine learning model based on equivariant neural networks which uses atomic occupation matrices as descriptors,directly capturing the electronic structure,local chemical environment,and oxidation states of the system at hand.We target here the prediction of Hubbard parameters computed self-consistently with iterative linear-response calculations,as implemented in density-functional perturbation theory(DFPT),and structural relaxations.Remarkably,when trained on data from 12 materials spanning various crystal structures and compositions,our model achieves mean absolute relative errors of 3%and 5%for Hubbard U and V parameters,respectively.By circumventing computationally expensive DFT or DFPT self-consistent protocols,our model significantly expedites the prediction of Hubbard parameters with negligible computational overhead,while approaching the accuracy of DFPT.Moreover,owing to its robust transferability,the model facilitates accelerated materials discovery and design via high-throughput calculations,with relevance for various technological applications.展开更多
Graphene foam(GF),synthesized via Chemical Vapor Deposition(CVD),has been proven to be the ideal bulk porous material.The addition of poly(dimethylsiloxane)(PDMS)within the porous structure enables enhancement of mech...Graphene foam(GF),synthesized via Chemical Vapor Deposition(CVD),has been proven to be the ideal bulk porous material.The addition of poly(dimethylsiloxane)(PDMS)within the porous structure enables enhancement of mechanical strength and alteration of heat transfer behavior.This study focuses on the thermodynamic behavior of GF/PDMS composites during deformation,and employs stochastic modeling and neuroevolution potential(NEP)for complex material modeling with precise prediction of microscopic mechanisms governing thermal property variations.The results demonstrate that the composite with a 5%doping rate of PDMS achieves the optimal mechanical performance and shows a 7.13-fold modulation in thermal resistance during the deformation from 40%stretching to 50%compression.Findings indicate PDMS fortifies structural stability while enabling dynamic thermal conductivity modulation in GF.This research provides critical insights into the micro-mechanisms of GF/PDMS composites and offers a theoretical foundation for applications in dynamic thermal management and self-powered sensor networks.展开更多
Since the introduction of Hooke's Law,the development of material constitutive laws has progressed rapidly over the past century.However,their establishment remains reliant on phenomenological models that often in...Since the introduction of Hooke's Law,the development of material constitutive laws has progressed rapidly over the past century.However,their establishment remains reliant on phenomenological models that often inadequately describe material responses [1].Symbolic learning,characterized by its high interpretability and flexibility driven by data,offers a novel approach to discovering these laws,significantly impacting key challenges such as capturing complex nonlinear material relationships and accelerating the discovery of constitutive laws.展开更多
基金Supported by the Opening Project of Key Laboratory of Comprehensive Utilization of Advantage Plants Resources in Hunan South(XNZW14C08)the NSF of Hunan Province(2015JJ2072)+2 种基金the Construct Program of the Key Discipline in Hunan Provincethe Science and Technology Innovative Research Team in Higher Educational Institutions of Hunan Provincethe Project for Undergraduate Research Study and Innovative Experiment of Hunan Provincial(2016-283)
文摘The reactions of the four-coordinated macrocyclic copper complex [CuL]（ClO4）2（L = 1,4,8,11-tetraazacyclotetradecane） with NH4VO3 under different conditions gave three inorganic-organic hybrid materials of [CuL][VO3]2·2.33H2O（1）, [CuL]3[V（10）O（28）]·8H2O（2） and [Cu L]3[V6O（18）]·8H2O（3）. Single-crystal X-ray diffraction analyses reveal that three diverse vanadium polyoxoanions, [V6O（18）]6- ring, [V（10）O（28）]6- cluster, and [V（12）O（35）]^10- ring, were isolated from the same reactant NH4VO3 under different conditions. The [CuL]^2＋ bridges the [V10O28]6- clusters to form a two-dimensional sheet in 2, and link the [V6O（18）]^6- rings in 1 and [V（12）O（35）]^10- rings in 3 into three-dimensional frameworks, respectively.
基金financial supportfrom PRAMX 98-05 and helpful discussion with Dr.A.C.Franville.
文摘Hybrid materials incorporating Eu-(TTA)(3). 2H(2)O (7hereafter designated as Eu-TTA, with TTA: thenoyltrifluoroacetone) in unmodified or modified MCM-41 by 3-aminopropyl-triethoxysilane (APTES) were prepared by impregnation method. The obtained materials were characterized using X-ray diffraction (XRD), IR and diffuse reflectance spectroscopy and luminescence spectra. All the hybrid samples exhibited the characteristic emission bands of EU3+ under UV light excitation at room temperature, and the excitation spectra showed significant blue-shifts compared to the pure rare-earth complex. Although the red emission intensity in the modified hybrid was almost the half of the red emission intensity in the pure Eu-TTA complex at room temperature, the hybrid showed a much higher thermal stability due to the shielding character of the MCM-41 host.
文摘Thework presents the electronic structure computations and optical spectroscopy studies of half-Heusler ScNiBi and YNiBi compounds.Our first-principles computations of the electronic structures were based on density functional theory accounting for spin-orbit coupling.These compounds are computed to be semiconductors.The calculated gap values make ScNiBi and YNiBi valid for thermoelectric and optoelectronic applications and as selective filters.In ScNiBi and YNiBi,an intense peak at the energy of−2 eV is composed of theNi 3d states in the conduction band,and the valence band mostly contains these states with some contributions from the Bi 6p and Sc 3d or Y 4d electronic states.These states participate in the formation of the indirect gap of 0.16 eV(ScNiBi)and 0.18 eV(YNiBi).Within the spectral ellipsometry technique in the interval 0.22–15μm of wavelength,the optical functions of materials are studied,and their dispersion features are revealed.A good matching of the experimental and modeled optical conductivity spectra allowed us to analyze orbital contributions.The abnormally low optical absorption observed in the low-energy region of the spectrum is referred to as the results of band calculations indicating a small density of electronic states near the Fermi energy of these complex materials.
文摘High-resolution imaging tools have revolutionized energy science by enabling direct visualization of local chemical and physical transformations across scales in highly complex material systems�from atomic rearrangements at catalytic surfaces and interfaces to mesoscale heterogeneities within battery electrodes.
文摘Manufacturing of composite materials is usually accompanied with residual stresses.These stresses should be evaluated and assessed.To this end,a micromechanical model for periodic material whose temperature dependent constituents behave as thermorheologically complex materials(TCM)has been developed.This model,referred as the high fidelity generalized method of cells(HFGMC),takes into account the detailed interaction between the fiber and resin,their volume ratios,the fibers distribution and their waviness.This model is linked,in conjunction with a special UMAT subroutine,to the ABAQUS finite element code for prediction of the response of thermoviscoelastic composite structures during cool down process.The present investigation shows the effect of the cool down rate on the residual stress developed in the composite cylindrical structures.
文摘With the techniques provided by the complex my method,like co,nplex ray expansion, complex mytracing,complex my paraxial approximation, etc.,the back scatter of dihedral corner reflectors is evaluated.Numerical results show that this method gives good and useful RCS prediction of the targets.
基金supported by Key laboratory of Management,Decision and Information Systems,Chinese Academy of Science
文摘This paper demonstrates a new interpretation of the material purchasing management system(MPMS) from the perspective of complex adaptive systems(CAS).Within the framework of CAS,the authors design the self-adaptive mechanism of the MPMS responding to the changing environment,such as the change of the price,by using risk measurement theory,modern portfolio theory(MPT) and the information of the material's modifying priority.As a bottom-up systems view,CAS focuses on the individual level and studies system's overall complexity by analyzing the mutual competition and adaptation among the individuals.This paper demonstrates a quantitative description of CAS by discussing the MPMS which can be viewed as a kind of CAS,and makes numerical simulations of Daqing oilfield MPMS.Compared to the benchmarks,the authors set the simulations show that the self-adaptive mechanism adapts well to the change of the material's market price.Hence,this paper accomplishes a numerical simulation of CAS's quantitative self-adaptive mechanism responding to the environment's change.
基金supported by the European Research Council through the project INCEPT(grant agreement no.677488)D.F.,E.M.R.,A.M.,and G.J.acknowledge the support of the Gordon and Betty Moore Foundation through the grant(CENTQC).
文摘Measuring fluctuations in matter’s low-energy excitations is the key to unveiling the nature of the non-equilibrium response of materials.A promising outlook in this respect is offered by spectroscopic methods that address matter fluctuations by exploiting the statistical nature of light-matter interactions with weak few-photon probes.Here we report the first implementation of ultrafast phase randomized tomography,combining pump-probe experiments with quantum optical state tomography,to measure the ultrafast non-equilibrium dynamics in complex materials.Our approach utilizes a time-resolved multimode heterodyne detection scheme with phase-randomized coherent ultrashort laser pulses,overcoming the limitations of phase-stable configurations and enabling a robust reconstruction of the statistical distribution of phase-averaged optical observables.This methodology is validated by measuring the coherent phonon response inα-quartz.By tracking the dynamics of the shot-noise limited photon number distribution of fewphoton probes with ultrafast resolution,our results set an upper limit to the non-classical features of phononic state inα-quartz and provide a pathway to access non-equilibrium quantum fluctuations in more complex quantum materials.
基金support by the Columbia Center for Computational Electrochemistry(CCCE)and computing resources from Columbia University’s Shared Research Computing FacilityJ.L.Z.and N.A.thank the Project HPC-EUROPA3(Grant No.INFRAIA-2016-1-730897)for its support,provided through the EC Research and Innovation Action under the H2020 ProgramN.A.also acknowledges support by a start-up grant(Dutch Sector Plan)from Utrecht University.The authors gratefully acknowledge discussions with JoséA.Garrido Torres and Thomas Bligaard.
文摘Artificial neural network(ANN)potentials enable accurate atomistic simulations of complex materials at unprecedented scales,but training them for potential energy surfaces(PES)of diverse chemical environments remains computationally intensive,especially when the PES gradients are trained on atomic force data.Here,we present an efficient methodology incorporating forces intoANNtraining by translating them to synthetic energy data using Gaussian process regression(GPR),leading to accurate PES models with fewer additional first-principles calculations and a reduced computational effort for training.We evaluated the method on hybrid density-functional theory data for ethylene carbonate(EC)molecules and their interfaces with Li metal,which are relevant for Li-metal batteries.The GPR-ANN potentials achieved an accuracy comparable to fully force-trained ANN potentials with a significantly reduced computational and memory overhead,establishing the method as a powerful and scalable framework for constructing high-fidelity ANN potentials for complex materials systems.
基金supported by the Scientific Research Initiation Project of Fuzhou University for Thousand Talents Program Experts(0041-510248)the Science and Technology Development Fund of Fuzhou University(0041-510299)。
文摘There are currently many materials for treating residual antibiotics in the environment, but none of them can specifically remove antibiotics. In addition, these materials are not sensitive enough to low concentrations of antibiotics. Here we show that a sensitive and specific material was developed by the preparation of magnetic Fe_(3)O_(4)-PAMAM-antibody complexes for treating tetracycline. The prepared antibody complexes can specifically treat tetracycline from aqueous solutions and the tetracycline removal ability by adsorption was also investigated. Controlled experiments were carried out with the effects of solution pH, temperature, and initial concentration of the tetracycline. The tetracycline was completely removed within 35 min at room temperature 30 ℃ with the maximum removal rate of almost 100%. Therefore, this material for specifically combining antigen and antibody to treat tetracycline indicated good application prospects for the waste water treatment.
基金support by the NCCR MARVEL,a National Centre of Competence in Research,funded by the Swiss National Science Foundation(Grant number 205602)supported by a grant from the Swiss National Supercomputing Centre(CSCS)under project ID s1073(Piz Daint)and ID 465000416(LUMI-G)supported by MIAI@Grenoble Alpes,(ANR-19-P3IA-0003).
文摘Density-functional theory with extended Hubbard functionals(DFT+U+V)provides a robust framework to accurately describe complex materials containing transition-metal or rare-earth elements.It does so by mitigating self-interaction errors inherent to semi-local functionals which are particularly pronounced in systems with partially-filled d and f electronic states.However,achieving accuracy in this approach hinges upon the accurate determination of the on-site U and inter-site V Hubbard parameters.In practice,these are obtained either by semi-empirical tuning,requiring prior knowledge,or,more correctly,by using predictive but expensive first-principles calculations.Here,we present a machine learning model based on equivariant neural networks which uses atomic occupation matrices as descriptors,directly capturing the electronic structure,local chemical environment,and oxidation states of the system at hand.We target here the prediction of Hubbard parameters computed self-consistently with iterative linear-response calculations,as implemented in density-functional perturbation theory(DFPT),and structural relaxations.Remarkably,when trained on data from 12 materials spanning various crystal structures and compositions,our model achieves mean absolute relative errors of 3%and 5%for Hubbard U and V parameters,respectively.By circumventing computationally expensive DFT or DFPT self-consistent protocols,our model significantly expedites the prediction of Hubbard parameters with negligible computational overhead,while approaching the accuracy of DFPT.Moreover,owing to its robust transferability,the model facilitates accelerated materials discovery and design via high-throughput calculations,with relevance for various technological applications.
基金supported by the Shenzhen Science and Technology Program(JCYJ20220530141009020)the Taishan Industry Leading Talents Program(tscx202312007)+2 种基金National Natural Science Foundation of China(52372007)Natural Science Foundation of Shandong Province(ZR2023ME125)This work was also supported by AI TENNessee Initiative Seed Funds and Center for Materials Processing University-Industry Partnership Seed Grant at University of Tennessee Knoxville.
文摘Graphene foam(GF),synthesized via Chemical Vapor Deposition(CVD),has been proven to be the ideal bulk porous material.The addition of poly(dimethylsiloxane)(PDMS)within the porous structure enables enhancement of mechanical strength and alteration of heat transfer behavior.This study focuses on the thermodynamic behavior of GF/PDMS composites during deformation,and employs stochastic modeling and neuroevolution potential(NEP)for complex material modeling with precise prediction of microscopic mechanisms governing thermal property variations.The results demonstrate that the composite with a 5%doping rate of PDMS achieves the optimal mechanical performance and shows a 7.13-fold modulation in thermal resistance during the deformation from 40%stretching to 50%compression.Findings indicate PDMS fortifies structural stability while enabling dynamic thermal conductivity modulation in GF.This research provides critical insights into the micro-mechanisms of GF/PDMS composites and offers a theoretical foundation for applications in dynamic thermal management and self-powered sensor networks.
文摘Since the introduction of Hooke's Law,the development of material constitutive laws has progressed rapidly over the past century.However,their establishment remains reliant on phenomenological models that often inadequately describe material responses [1].Symbolic learning,characterized by its high interpretability and flexibility driven by data,offers a novel approach to discovering these laws,significantly impacting key challenges such as capturing complex nonlinear material relationships and accelerating the discovery of constitutive laws.
