To address the poor mechanical properties of polydimethylsiloxane(PDMS)and enhance the understanding of the reinforcement mechanisms of aerogel network structures in rubber matrices,this study reinforced PDMS using an...To address the poor mechanical properties of polydimethylsiloxane(PDMS)and enhance the understanding of the reinforcement mechanisms of aerogel network structures in rubber matrices,this study reinforced PDMS using an ordered interconnected three-dimensional montmorillonite(MMT)aerogel network.The average pore diameter of the aerogels was successfully reduced from 11.53μm to 2.51μm by adjusting the ratio of poly(vinyl alcohol)(PVA)to MMT via directional freezing.Changes in the aerogel network were observed in field emission scanning electron microscope(FESEM)images.After vacuum impregnation,the aerogel network structure of the composites was observed using FESEM.Tensile tests indicated that as the pore diameter decreased,the elongation at break of the composites first increased to a peak of329.61%before decreasing,while the tensile strength and Young's modulus continuously increased to their maximum values of 6.29 MPa and24.67 MPa,respectively.Meanwhile,FESEM images of the tensile cracks and fracture surfaces showed that with a reduction in aerogel pore diameter,the degrees of crack deflection and interfacial debonding increased,presenting a rougher fracture surface.These phenomena enable the composites to dissipate substantial energy during tension,thus effectively improving the mechanical strength of the composites.The present work elucidates the bearing of ordered three-dimensional aerogel network structures on the performance of rubber matrices and provides crucial theoretical insights and technical guidance for the creation and optimization of high-performance PDMS-based composites.展开更多
The internal hotspot temperature rise prediction in nanocrystalline high-frequency transformers(nanoHFTs) is essential to ensure reliable operation. This paper presents a three-dimensional thermal network(3DTN) model ...The internal hotspot temperature rise prediction in nanocrystalline high-frequency transformers(nanoHFTs) is essential to ensure reliable operation. This paper presents a three-dimensional thermal network(3DTN) model for epoxy resin encapsulated nano HFTs, which aims to precisely predict the temperature distribution inside the transformer in combination with the finite element method(FEM). A magnetothermal bidirectional coupling 3DTN model is established by analyzing the thermal conduction between the core, windings, and epoxy resin, while also considering the convection and radiation heat transfer mechanisms on the surface of the epoxy resin. The model considers the impact of loss distribution in the core and windings on the temperature field and adopts a simplified 1/2 thermal network model to reduce computational complexity. Furthermore, the results of FEM are compared with experimental results to verify the accuracy of the 3DTN model in predicting the temperature rise of nano HFT. The results show that the 3DTN model reduces errors by an average of 5.25% over the traditional two-dimensional thermal network(2DTN) model, particularly for temperature distributions in the windings and core. This paper provides a temperature rise prediction method for the thermal design and offers a theoretical basis and engineering guidance for the optimization of their thermal management systems.展开更多
The past decade has seen a growing interest in ocean sensor networks because of their wide applications in marine research,oceanography,ocean monitoring,offshore exploration,and defense or homeland security.Ocean sens...The past decade has seen a growing interest in ocean sensor networks because of their wide applications in marine research,oceanography,ocean monitoring,offshore exploration,and defense or homeland security.Ocean sensor networks are generally formed with various ocean sensors,autonomous underwater vehicles,surface stations,and research vessels.To make ocean sensor network applications viable,efficient communication among all devices and components is crucial.Due to the unique characteristics of underwater acoustic channels and the complex deployment environment in three dimensional(3D) ocean spaces,new efficient and reliable communication and networking protocols are needed in design of ocean sensor networks.In this paper,we aim to provide an overview of the most recent advances in network design principles for 3D ocean sensor networks,with focuses on deployment,localization,topology design,and position-based routing in 3D ocean spaces.展开更多
Polyvinyl alcohol hydrogels have been used in wearable devices due to their good flexibility and biocompatibility.However,due to the low thermal conductivity(κ)of pure hydrogel,its further application in high power d...Polyvinyl alcohol hydrogels have been used in wearable devices due to their good flexibility and biocompatibility.However,due to the low thermal conductivity(κ)of pure hydrogel,its further application in high power devices is limited.To solve this problem,melamine sponge(MS)was used as the skeleton to wrap boron nitride nanosheets(BNNS)through repeated layering assembly,successfully preparing a three-dimensional(3D)boron nitride network(BNNS@MS),and PVA hydrogels were formed in the pores of the network.Due to the existence of the continuous phonon conduction network,the BNNS@MS/PVA exhibited an improvedκ.When the content of BNNS is about 6 wt.%,κof the hydrogel was increased to 1.12 W m^(-1)K^(-1),about two times higher than that of pure hydrogel.The solid heat conduction network and liquid convection network cooperate to achieve good thermal management ability.Combined with its high specific heat capacity,the composites have an important application prospect in the field of wearable flexible electronic thermal management.展开更多
The space-air-ground integrated network(SAGIN)combines the superiority of the satellite,aerial,and ground communications,which is envisioned to provide high-precision positioning ability as well as seamless connectivi...The space-air-ground integrated network(SAGIN)combines the superiority of the satellite,aerial,and ground communications,which is envisioned to provide high-precision positioning ability as well as seamless connectivity in the 5G and Beyond 5G(B5G)systems.In this paper,we propose a three-dimensional SAGIN localization scheme for ground agents utilizing multi-source information from satellites,base stations and unmanned aerial vehicles(UAVs).Based on the designed scheme,we derive the positioning performance bound and establish a distributed maximum likelihood algorithm to jointly estimate the positions and clock offsets of ground agents.Simulation results demonstrate the validity of the SAGIN localization scheme and reveal the effects of the number of satellites,the number of base stations,the number of UAVs and clock noise on positioning performance.展开更多
In order to study the behavior and interconnection of network devices,graphs structures are used to formulate the properties in terms of mathematical models.Mesh network(meshnet)is a LAN topology in which devices are ...In order to study the behavior and interconnection of network devices,graphs structures are used to formulate the properties in terms of mathematical models.Mesh network(meshnet)is a LAN topology in which devices are connected either directly or through some intermediate devices.These terminating and intermediate devices are considered as vertices of graph whereas wired or wireless connections among these devices are shown as edges of graph.Topological indices are used to reflect structural property of graphs in form of one real number.This structural invariant has revolutionized the field of chemistry to identify molecular descriptors of chemical compounds.These indices are extensively used for establishing relationships between the structure of nanotubes and their physico-chemical properties.In this paper a representation of sodium chloride(NaCl)is studied,because structure of NaCl is same as the Cartesian product of three paths of length exactly like a mesh network.In this way the general formula obtained in this paper can be used in chemistry as well as for any degree-based topological polynomials of three-dimensional mesh networks.展开更多
A novel complex, (H 3O) 2[Ni(2,6-pydc) 2]·2H 2O was synthesized in an aqueous solution and characterized by means of single-crystal X-ray diffraction, elemental analyses and IR spectra. The X-ray structural a...A novel complex, (H 3O) 2[Ni(2,6-pydc) 2]·2H 2O was synthesized in an aqueous solution and characterized by means of single-crystal X-ray diffraction, elemental analyses and IR spectra. The X-ray structural analysis revealed that the novel compound forms three-dimensional(3D) networks by both π-π stacking and hydrogen-bonding interactions. The crystal data for the complex are a=13.853(3) nm, b=9.6892(19) nm, c=13.732(3) nm, α=90.00°, β=115.52(3)°, γ=90.00°, Z=3, R 1=0.0786, wR 2=0.1522.展开更多
It is of great importance to obtain precise trace data,as traces are frequently the sole visible and measurable parameter in most outcrops.The manual recognition and detection of traces on high-resolution three-dimens...It is of great importance to obtain precise trace data,as traces are frequently the sole visible and measurable parameter in most outcrops.The manual recognition and detection of traces on high-resolution three-dimensional(3D)models are relatively straightforward but time-consuming.One potential solution to enhance this process is to use machine learning algorithms to detect the 3D traces.In this study,a unique pixel-wise texture mapper algorithm generates a dense point cloud representation of an outcrop with the precise resolution of the original textured 3D model.A virtual digital image rendering was then employed to capture virtual images of selected regions.This technique helps to overcome limitations caused by the surface morphology of the rock mass,such as restricted access,lighting conditions,and shading effects.After AI-powered trace detection on two-dimensional(2D)images,a 3D data structuring technique was applied to the selected trace pixels.In the 3D data structuring,the trace data were structured through 2D thinning,3D reprojection,clustering,segmentation,and segment linking.Finally,the linked segments were exported as 3D polylines,with each polyline in the output corresponding to a trace.The efficacy of the proposed method was assessed using a 3D model of a real-world case study,which was used to compare the results of artificial intelligence(AI)-aided and human intelligence trace detection.Rosette diagrams,which visualize the distribution of trace orientations,confirmed the high similarity between the automatically and manually generated trace maps.In conclusion,the proposed semi-automatic method was easy to use,fast,and accurate in detecting the dominant jointing system of the rock mass.展开更多
The core sampling experiments were conducted after hydraulic fracturing in the three-dimensional development zone of Fuling shale gas.Six coring wells of different well types were systematically designed.Based on the ...The core sampling experiments were conducted after hydraulic fracturing in the three-dimensional development zone of Fuling shale gas.Six coring wells of different well types were systematically designed.Based on the integrated engineering technology of post-fracturing drilling,coring and monitoring of shale and the analysis of fracture source tracing,the evaluation of the fracture network after fracturing in the three-dimensional development of shale gas was conducted.The data of core fractures after fracturing indicate that three major types of fractures are formed after fracturing:natural fractures,hydraulic fractures,and fractures induced by external mechanical force,which are further classified into six subcategories:natural structural fractures,natural bedding fractures,hydraulic fractures,hydraulically activated fractures,drilling induced fractures,and fractures induced by core transportation.The forms of the artificial fracture network after fracturing are complex.Hydraulic fractures and hydraulically activated fractures interweave with each other,presenting eight forms of artificial fracture networks,among which the“一”-shaped fracture is the most common,accounting for approximately 70%of the total fractures.When the distance to the fractured wellbore is less than 35 m,the density of the artificial fracture network is relatively high;when it is 35–100 m,the density is lower;and when it is beyond 100 m,the density gradually increases.The results of the fracture tracing in the core sampling area confirm that the current fracturing technology can essentially achieve the differential transformation of the reservoir in the main area of Jiaoshiba block in Fuling.The three-layer three-dimensional development model can efficiently utilize shale gas reserves,although there is still room for improvement in the complexity and propagation uniformity of fractures.It is necessary to further optimize technologies such as close-cutting combined with temporary blocking and deflection within fractures or at fracture mouths,as well as limited flow perforation techniques,to promote the balanced initiation and extension of fractures.展开更多
The crystal structure of the title compound [Na2(OH2)5]2+[C6H12N4H2]2-2+ [Mo7O24]6 ?4H2O, prepared from an aqueous solution of Na2MoO4 ?2H2O in the presence of MoCl3 and hexamethylene tetramine, has been determined by...The crystal structure of the title compound [Na2(OH2)5]2+[C6H12N4H2]2-2+ [Mo7O24]6 ?4H2O, prepared from an aqueous solution of Na2MoO4 ?2H2O in the presence of MoCl3 and hexamethylene tetramine, has been determined by single-crystal X-ray diffraction. The crystal is of orthorhombic, space group Pnma with a = 14.6113(2), b = 18.6833(1), c = 15.3712(2), V = 4196.14(8)3, Z = 4, Mr = 1548.13, F(000) = 3016, = 2.157 mm-1 and Dc = 2.451 g/cm3. The final R factor is 0.0526 for 3818 unique observed reflections (I > 2(I)). The structural analysis reveals that heptamolybdate anions in the title compound consist of seven edge-sharing MoO6 octahedra, and are linked into a three-dimensional framework by sodium ions and hydrogen bonds.展开更多
One interesting coordination polymer, [Zn2（1,2,4-BTC）（OH）（H2O）2]2·2H2O 1, has been synthesized from 1,2,4-BTC （1,2,4-BTC = 1,2,4-bentricarboxylate） under hydrothermal conditions and characterized by eleme...One interesting coordination polymer, [Zn2（1,2,4-BTC）（OH）（H2O）2]2·2H2O 1, has been synthesized from 1,2,4-BTC （1,2,4-BTC = 1,2,4-bentricarboxylate） under hydrothermal conditions and characterized by elemental analyses, IR, TG and single-crystal X-ray diffraction. Complex I crystallizes in triclinic, space group P^-1, with a = 6.5200（13）, b = 9,0600（18）, c = 10.968（2） A^°, α = 111.55（3）, β = 92.07（3）,γ= 95.03（3）°, C9H10O10Zn2, Mr = 408.91, V= 598.7（2） A^°^3, Dc = 2.268 g/cm^3, F（000） = 408 and Z = 2. X-ray diffraction analysis reveals that complex 1 is a three-dimensional network built from tetranuclear Zn（Ⅱ） building unit. In this complex, the Zn4 unit is an eight-connected knot, while 1,2,4-BTC a four-connected knot. This results in a CaF2 topology. To the best of our knowledge, such Zn4 unit is the first 8-connected building block built from asymmetry ligand.展开更多
Ocean temperature is an important physical variable in marine ecosystems,and ocean temperature prediction is an important research objective in ocean-related fields.Currently,one of the commonly used methods for ocean...Ocean temperature is an important physical variable in marine ecosystems,and ocean temperature prediction is an important research objective in ocean-related fields.Currently,one of the commonly used methods for ocean temperature prediction is based on data-driven,but research on this method is mostly limited to the sea surface,with few studies on the prediction of internal ocean temperature.Existing graph neural network-based methods usually use predefined graphs or learned static graphs,which cannot capture the dynamic associations among data.In this study,we propose a novel dynamic spatiotemporal graph neural network(DSTGN)to predict threedimensional ocean temperature(3D-OT),which combines static graph learning and dynamic graph learning to automatically mine two unknown dependencies between sequences based on the original 3D-OT data without prior knowledge.Temporal and spatial dependencies in the time series were then captured using temporal and graph convolutions.We also integrated dynamic graph learning,static graph learning,graph convolution,and temporal convolution into an end-to-end framework for 3D-OT prediction using time-series grid data.In this study,we conducted prediction experiments using high-resolution 3D-OT from the Copernicus global ocean physical reanalysis,with data covering the vertical variation of temperature from the sea surface to 1000 m below the sea surface.We compared five mainstream models that are commonly used for ocean temperature prediction,and the results showed that the method achieved the best prediction results at all prediction scales.展开更多
To solve the volume expansion and poor electrical conductivity of germanium-based anode materials,Ge/rGO/CNTs nanocomposites with three-dimensional network structure are fabricated through the dispersion of polyethyle...To solve the volume expansion and poor electrical conductivity of germanium-based anode materials,Ge/rGO/CNTs nanocomposites with three-dimensional network structure are fabricated through the dispersion of polyethylene-polypropylene glycol(F127)and reduction of hydrogen.An interesting phenomenon is discovered that F127 can break GeO_(2)polycrystalline microparticles into 100 nm nanoparticles by only physical interaction,which promotes the uniform dispersion of GeO_(2)in a carbon network structure composed of graphene(rGO)and carbon nanotubes(CNTs).As evaluated as anode material of Lithium-ion batteries,Ge/rGO/CNTs nanocomposites exhibit excellent lithium storage performance.The initial specific capacity is high to 1549.7 mAh/g at 0.2 A/g,and the reversible capacity still retains972.4 mAh/g after 100 cycles.The improved lithium storage performance is attributed to that Ge nanoparticles can effectively slow down the volume expansion during charge and discharge processes,and threedimensional carbon networks can improve electrical conductivity and accelerate lithium-ion transfer of anode materials.展开更多
The Metropolitan Area Network (MAN) has faced serious problems after years of rapid development. The model of three-dimensional IP-based MAN, proposed by ZTE, is a next-generation MAN solution, which not only solves t...The Metropolitan Area Network (MAN) has faced serious problems after years of rapid development. The model of three-dimensional IP-based MAN, proposed by ZTE, is a next-generation MAN solution, which not only solves the existing problems but also brings new ideas for the development of next-generation MAN.展开更多
The simulation of salinity at different locations of a tidal river using physically-based hydrodynamic models is quite cumbersome because it requires many types of data, such as hydrological and hydraulic time series ...The simulation of salinity at different locations of a tidal river using physically-based hydrodynamic models is quite cumbersome because it requires many types of data, such as hydrological and hydraulic time series at boundaries, river geometry, and adjusted coefficients. Therefore, an artificial neural network (ANN) technique using a back-propagation neural network (BPNN) and a radial basis function neural network (RBFNN) is adopted as an effective alternative in salinity simulation studies. The present study focuses on comparing the performance of BPNN, RBFNN, and three-dimensional hydrodynamic models as applied to a tidal estuarine system. The observed salinity data sets collected from 18 to 22 May, 16 to 22 October, and 26 to 30 October 2002 (totaling 4320 data points) were used for BPNN and RBFNN model training and for hydrodynamic model calibration. The data sets collected from 30 May to 2 June and 11 to 15 November 2002 (totaling 2592 data points) were adopted for BPNN and RBFNN model verification and for hydrodynamic model verification. The results revealed that the ANN (BPNN and RBFNN) models were capable of predicting the nonlinear time series behavior of salinity to the multiple forcing signals of water stages at different stations and freshwater input at upstream boundaries. The salinity predicted by the ANN models was better than that predicted by the physically based hydrodynamic model. This study suggests that BPNN and RBFNN models are easy-to-use modeling tools for simulating the salinity variation in a tidal estuarine system.展开更多
The development of graphene-based composites with low density,robust absorption,wide bandwidth and thin thickness remained a great challenge in the field of electromagnetic(EM)absorption.In this work,nitrogen-doped re...The development of graphene-based composites with low density,robust absorption,wide bandwidth and thin thickness remained a great challenge in the field of electromagnetic(EM)absorption.In this work,nitrogen-doped reduced graphene oxide/hollow cobalt ferrite(NRGO/hollow CoFe_(2)O_(4))composite aerogels were constructed by a solvothermal and hydrothermal two-step route.Results demonstrated that the as-fabricated composite aerogels had the ultralow density and a unique three-dimensional(3D)network structure,and lots of hollow CoFe_(2)O_(4)microspheres were almost homogeneously distributed on the wrinkled surfaces of lamellar NRGO.Moreover,superior EM absorbing capacity could be achieved by modulating the ferrite structure,addition amounts of hollow CoFe_(2)O_(4)and thicknesses.It was noteworthy that the NRGO/hollow CoFe_(2)O_(4)composite aerogel with the addition amount of ferrite of 15.0 mg pos-sessed the minimum reflection loss of-44.7 dB and maximum absorption bandwidth of 5.2 GHz(from 12.6 to 17.8 GHz)at a very thin thickness of 1.8 mm and filling ratio of 15.0 wt.%.Furthermore,the possible EM attenuation mechanism had been proposed.The results of this work would be helpful for developing RGO-based 3D composites as lightweight,thin and highly efficient EM wave absorbers.展开更多
Al-Si alloy,a high temperature phase change material,has great potential in thermal management due to its advantages of high heat storage density and thermal conductivity.Microencapsulation of Al-Si alloy is one of th...Al-Si alloy,a high temperature phase change material,has great potential in thermal management due to its advantages of high heat storage density and thermal conductivity.Microencapsulation of Al-Si alloy is one of the effective techniques to solve high temperature leakage and corrosion.In this paper,commercial Al-10Si alloy micro powders were encapsulated with flexible ceramic shells whose total thickness is below 1μm by hydrothermal treatment and heat treatment in N_(2) atmosphere.The compositions and microstructures were characterized by XRD,SEM and TEM.The shell was composed of AlN fibers network structure embedded withα-Al_(2)O_(3)/AlN which prevented the alloy from leaking and oxidizing,as well as had excellent thermal stability.The latent heat of microcapsules was 351.8 J g^(-1)for absorption and 372.7 J g^(-1)for exothermic.The microcapsules showed near zero thermal performance loss with latent heat storage(LHS)/release(LHR)was 353.2/403.7 J g^(-1)after 3000 cycles.Compared with the published Al-Si alloy microcapsules,both high heat storage density and super thermal cycle stability were achieved,showing promising development prospects in high temperature thermal management.展开更多
Several challenging issues,such as the poor conductivity of sulfur,shuttle effects,large volume change of cathode,and the dendritic lithium in anode,have led to the low utilization of sulfur and hampered the commercia...Several challenging issues,such as the poor conductivity of sulfur,shuttle effects,large volume change of cathode,and the dendritic lithium in anode,have led to the low utilization of sulfur and hampered the commercialization of lithium–sulfur batteries.In this study,a novel three-dimensionally interconnected network structure comprising Co9 S8 and multiwalled carbon nanotubes(MWCNTs)was synthesized by a solvothermal route and used as the sulfur host.The assembled batteries delivered a specific capacity of1154 m Ah g-1 at 0.1 C,and the retention was 64%after 400 cycles at 0.5 C.The polar and catalytic Co9 S8 nanoparticles have a strong adsorbent effect for polysulfide,which can effectively reduce the shuttling effect.Meanwhile,the three-dimensionally interconnected CNT networks improve the overall conductivity and increase the contact with the electrolyte,thus enhancing the transport of electrons and Li ions.Polysulfide adsorption is greatly increased with the synergistic effect of polar Co9 S8 and MWCNTs in the three-dimensionally interconnected composites,which contributes to their promising performance for the lithium–sulfur batteries.展开更多
The title complex Mn（H2O）2（HNic）2 （C22H12MnN2O8, Mr = 367.18） crystallizes in monoclinic, space group P21/c with a = 7.5735（8）, b = 12.5295（13）, c = 7.6466（8）A.β = 101.2790（10）°, Z = 2, V= 711.59...The title complex Mn（H2O）2（HNic）2 （C22H12MnN2O8, Mr = 367.18） crystallizes in monoclinic, space group P21/c with a = 7.5735（8）, b = 12.5295（13）, c = 7.6466（8）A.β = 101.2790（10）°, Z = 2, V= 711.59（13） A^3, D, = 1.714 g/cm^3,μ（MoKa） = 0.974 mm^-1, F（000） = 374, R1 （1255 observed reflections （Ⅰ 〉 2σ（Ⅰ）） = 0.0250） and wR2 = 0.0662 （all data）. In this paper, we report the complexation of Mn（Ⅱ） by the bidentate ligand 2-hydroxynicotinic acid （HNic）. In the crystal the Mn（Ⅱ） ion exhibits a deformed octahedron structure. The title complex Mn（H2O）2（HNic）2 has a three-dimensional （3D） network structure extended by hydrogen bonds, which are formed by two typical eight-membered hydrogen-bonded rings.展开更多
基金financially supported by the National Natural Science Foundation of China(Nos.21876164 and U2030203)A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions。
文摘To address the poor mechanical properties of polydimethylsiloxane(PDMS)and enhance the understanding of the reinforcement mechanisms of aerogel network structures in rubber matrices,this study reinforced PDMS using an ordered interconnected three-dimensional montmorillonite(MMT)aerogel network.The average pore diameter of the aerogels was successfully reduced from 11.53μm to 2.51μm by adjusting the ratio of poly(vinyl alcohol)(PVA)to MMT via directional freezing.Changes in the aerogel network were observed in field emission scanning electron microscope(FESEM)images.After vacuum impregnation,the aerogel network structure of the composites was observed using FESEM.Tensile tests indicated that as the pore diameter decreased,the elongation at break of the composites first increased to a peak of329.61%before decreasing,while the tensile strength and Young's modulus continuously increased to their maximum values of 6.29 MPa and24.67 MPa,respectively.Meanwhile,FESEM images of the tensile cracks and fracture surfaces showed that with a reduction in aerogel pore diameter,the degrees of crack deflection and interfacial debonding increased,presenting a rougher fracture surface.These phenomena enable the composites to dissipate substantial energy during tension,thus effectively improving the mechanical strength of the composites.The present work elucidates the bearing of ordered three-dimensional aerogel network structures on the performance of rubber matrices and provides crucial theoretical insights and technical guidance for the creation and optimization of high-performance PDMS-based composites.
基金supported by the Project of the National Key Research and Development Program of China under Grant 2022YFB2404100。
文摘The internal hotspot temperature rise prediction in nanocrystalline high-frequency transformers(nanoHFTs) is essential to ensure reliable operation. This paper presents a three-dimensional thermal network(3DTN) model for epoxy resin encapsulated nano HFTs, which aims to precisely predict the temperature distribution inside the transformer in combination with the finite element method(FEM). A magnetothermal bidirectional coupling 3DTN model is established by analyzing the thermal conduction between the core, windings, and epoxy resin, while also considering the convection and radiation heat transfer mechanisms on the surface of the epoxy resin. The model considers the impact of loss distribution in the core and windings on the temperature field and adopts a simplified 1/2 thermal network model to reduce computational complexity. Furthermore, the results of FEM are compared with experimental results to verify the accuracy of the 3DTN model in predicting the temperature rise of nano HFT. The results show that the 3DTN model reduces errors by an average of 5.25% over the traditional two-dimensional thermal network(2DTN) model, particularly for temperature distributions in the windings and core. This paper provides a temperature rise prediction method for the thermal design and offers a theoretical basis and engineering guidance for the optimization of their thermal management systems.
基金Y. Wang was supported in part by the US National Science Foundation (NSF) under Grant Nos.CNS-0721666,CNS-0915331,and CNS-1050398Y. Liu was partially supported by the National Natural Science Foundation of China (NSFC) under Grant No. 61074092+1 种基金by the Shandong Provincial Natural Science Foundation,China under Grant No.Q2008E01Z. Guo was partially supported by the NSFC under Grant Nos. 61170258 and 6093301
文摘The past decade has seen a growing interest in ocean sensor networks because of their wide applications in marine research,oceanography,ocean monitoring,offshore exploration,and defense or homeland security.Ocean sensor networks are generally formed with various ocean sensors,autonomous underwater vehicles,surface stations,and research vessels.To make ocean sensor network applications viable,efficient communication among all devices and components is crucial.Due to the unique characteristics of underwater acoustic channels and the complex deployment environment in three dimensional(3D) ocean spaces,new efficient and reliable communication and networking protocols are needed in design of ocean sensor networks.In this paper,we aim to provide an overview of the most recent advances in network design principles for 3D ocean sensor networks,with focuses on deployment,localization,topology design,and position-based routing in 3D ocean spaces.
基金the National Natural Science Foundation of China(Nos.52173078,52130303,and 51803151)the Young Elite Scientists Sponsorship Program by CAST(No.2019QNRC001)。
文摘Polyvinyl alcohol hydrogels have been used in wearable devices due to their good flexibility and biocompatibility.However,due to the low thermal conductivity(κ)of pure hydrogel,its further application in high power devices is limited.To solve this problem,melamine sponge(MS)was used as the skeleton to wrap boron nitride nanosheets(BNNS)through repeated layering assembly,successfully preparing a three-dimensional(3D)boron nitride network(BNNS@MS),and PVA hydrogels were formed in the pores of the network.Due to the existence of the continuous phonon conduction network,the BNNS@MS/PVA exhibited an improvedκ.When the content of BNNS is about 6 wt.%,κof the hydrogel was increased to 1.12 W m^(-1)K^(-1),about two times higher than that of pure hydrogel.The solid heat conduction network and liquid convection network cooperate to achieve good thermal management ability.Combined with its high specific heat capacity,the composites have an important application prospect in the field of wearable flexible electronic thermal management.
文摘The space-air-ground integrated network(SAGIN)combines the superiority of the satellite,aerial,and ground communications,which is envisioned to provide high-precision positioning ability as well as seamless connectivity in the 5G and Beyond 5G(B5G)systems.In this paper,we propose a three-dimensional SAGIN localization scheme for ground agents utilizing multi-source information from satellites,base stations and unmanned aerial vehicles(UAVs).Based on the designed scheme,we derive the positioning performance bound and establish a distributed maximum likelihood algorithm to jointly estimate the positions and clock offsets of ground agents.Simulation results demonstrate the validity of the SAGIN localization scheme and reveal the effects of the number of satellites,the number of base stations,the number of UAVs and clock noise on positioning performance.
文摘In order to study the behavior and interconnection of network devices,graphs structures are used to formulate the properties in terms of mathematical models.Mesh network(meshnet)is a LAN topology in which devices are connected either directly or through some intermediate devices.These terminating and intermediate devices are considered as vertices of graph whereas wired or wireless connections among these devices are shown as edges of graph.Topological indices are used to reflect structural property of graphs in form of one real number.This structural invariant has revolutionized the field of chemistry to identify molecular descriptors of chemical compounds.These indices are extensively used for establishing relationships between the structure of nanotubes and their physico-chemical properties.In this paper a representation of sodium chloride(NaCl)is studied,because structure of NaCl is same as the Cartesian product of three paths of length exactly like a mesh network.In this way the general formula obtained in this paper can be used in chemistry as well as for any degree-based topological polynomials of three-dimensional mesh networks.
基金Supported by the National Natural Science Foundation of China(No.2 0 1710 10)
文摘A novel complex, (H 3O) 2[Ni(2,6-pydc) 2]·2H 2O was synthesized in an aqueous solution and characterized by means of single-crystal X-ray diffraction, elemental analyses and IR spectra. The X-ray structural analysis revealed that the novel compound forms three-dimensional(3D) networks by both π-π stacking and hydrogen-bonding interactions. The crystal data for the complex are a=13.853(3) nm, b=9.6892(19) nm, c=13.732(3) nm, α=90.00°, β=115.52(3)°, γ=90.00°, Z=3, R 1=0.0786, wR 2=0.1522.
基金supported by grants from the Human Resources Development program (Grant No.20204010600250)the Training Program of CCUS for the Green Growth (Grant No.20214000000500)by the Korea Institute of Energy Technology Evaluation and Planning (KETEP)funded by the Ministry of Trade,Industry,and Energy of the Korean Government (MOTIE).
文摘It is of great importance to obtain precise trace data,as traces are frequently the sole visible and measurable parameter in most outcrops.The manual recognition and detection of traces on high-resolution three-dimensional(3D)models are relatively straightforward but time-consuming.One potential solution to enhance this process is to use machine learning algorithms to detect the 3D traces.In this study,a unique pixel-wise texture mapper algorithm generates a dense point cloud representation of an outcrop with the precise resolution of the original textured 3D model.A virtual digital image rendering was then employed to capture virtual images of selected regions.This technique helps to overcome limitations caused by the surface morphology of the rock mass,such as restricted access,lighting conditions,and shading effects.After AI-powered trace detection on two-dimensional(2D)images,a 3D data structuring technique was applied to the selected trace pixels.In the 3D data structuring,the trace data were structured through 2D thinning,3D reprojection,clustering,segmentation,and segment linking.Finally,the linked segments were exported as 3D polylines,with each polyline in the output corresponding to a trace.The efficacy of the proposed method was assessed using a 3D model of a real-world case study,which was used to compare the results of artificial intelligence(AI)-aided and human intelligence trace detection.Rosette diagrams,which visualize the distribution of trace orientations,confirmed the high similarity between the automatically and manually generated trace maps.In conclusion,the proposed semi-automatic method was easy to use,fast,and accurate in detecting the dominant jointing system of the rock mass.
文摘The core sampling experiments were conducted after hydraulic fracturing in the three-dimensional development zone of Fuling shale gas.Six coring wells of different well types were systematically designed.Based on the integrated engineering technology of post-fracturing drilling,coring and monitoring of shale and the analysis of fracture source tracing,the evaluation of the fracture network after fracturing in the three-dimensional development of shale gas was conducted.The data of core fractures after fracturing indicate that three major types of fractures are formed after fracturing:natural fractures,hydraulic fractures,and fractures induced by external mechanical force,which are further classified into six subcategories:natural structural fractures,natural bedding fractures,hydraulic fractures,hydraulically activated fractures,drilling induced fractures,and fractures induced by core transportation.The forms of the artificial fracture network after fracturing are complex.Hydraulic fractures and hydraulically activated fractures interweave with each other,presenting eight forms of artificial fracture networks,among which the“一”-shaped fracture is the most common,accounting for approximately 70%of the total fractures.When the distance to the fractured wellbore is less than 35 m,the density of the artificial fracture network is relatively high;when it is 35–100 m,the density is lower;and when it is beyond 100 m,the density gradually increases.The results of the fracture tracing in the core sampling area confirm that the current fracturing technology can essentially achieve the differential transformation of the reservoir in the main area of Jiaoshiba block in Fuling.The three-layer three-dimensional development model can efficiently utilize shale gas reserves,although there is still room for improvement in the complexity and propagation uniformity of fractures.It is necessary to further optimize technologies such as close-cutting combined with temporary blocking and deflection within fractures or at fracture mouths,as well as limited flow perforation techniques,to promote the balanced initiation and extension of fractures.
基金This work was supported by Chinese Academy of Sciences the State Education Ministry+1 种基金 the State Personnel Ministry the NSFC (20073048)
文摘The crystal structure of the title compound [Na2(OH2)5]2+[C6H12N4H2]2-2+ [Mo7O24]6 ?4H2O, prepared from an aqueous solution of Na2MoO4 ?2H2O in the presence of MoCl3 and hexamethylene tetramine, has been determined by single-crystal X-ray diffraction. The crystal is of orthorhombic, space group Pnma with a = 14.6113(2), b = 18.6833(1), c = 15.3712(2), V = 4196.14(8)3, Z = 4, Mr = 1548.13, F(000) = 3016, = 2.157 mm-1 and Dc = 2.451 g/cm3. The final R factor is 0.0526 for 3818 unique observed reflections (I > 2(I)). The structural analysis reveals that heptamolybdate anions in the title compound consist of seven edge-sharing MoO6 octahedra, and are linked into a three-dimensional framework by sodium ions and hydrogen bonds.
基金supported by the National Natural Science Foundation of China (No. 20701005 and 20701006)
文摘One interesting coordination polymer, [Zn2（1,2,4-BTC）（OH）（H2O）2]2·2H2O 1, has been synthesized from 1,2,4-BTC （1,2,4-BTC = 1,2,4-bentricarboxylate） under hydrothermal conditions and characterized by elemental analyses, IR, TG and single-crystal X-ray diffraction. Complex I crystallizes in triclinic, space group P^-1, with a = 6.5200（13）, b = 9,0600（18）, c = 10.968（2） A^°, α = 111.55（3）, β = 92.07（3）,γ= 95.03（3）°, C9H10O10Zn2, Mr = 408.91, V= 598.7（2） A^°^3, Dc = 2.268 g/cm^3, F（000） = 408 and Z = 2. X-ray diffraction analysis reveals that complex 1 is a three-dimensional network built from tetranuclear Zn（Ⅱ） building unit. In this complex, the Zn4 unit is an eight-connected knot, while 1,2,4-BTC a four-connected knot. This results in a CaF2 topology. To the best of our knowledge, such Zn4 unit is the first 8-connected building block built from asymmetry ligand.
基金The National Key R&D Program of China under contract No.2021YFC3101603.
文摘Ocean temperature is an important physical variable in marine ecosystems,and ocean temperature prediction is an important research objective in ocean-related fields.Currently,one of the commonly used methods for ocean temperature prediction is based on data-driven,but research on this method is mostly limited to the sea surface,with few studies on the prediction of internal ocean temperature.Existing graph neural network-based methods usually use predefined graphs or learned static graphs,which cannot capture the dynamic associations among data.In this study,we propose a novel dynamic spatiotemporal graph neural network(DSTGN)to predict threedimensional ocean temperature(3D-OT),which combines static graph learning and dynamic graph learning to automatically mine two unknown dependencies between sequences based on the original 3D-OT data without prior knowledge.Temporal and spatial dependencies in the time series were then captured using temporal and graph convolutions.We also integrated dynamic graph learning,static graph learning,graph convolution,and temporal convolution into an end-to-end framework for 3D-OT prediction using time-series grid data.In this study,we conducted prediction experiments using high-resolution 3D-OT from the Copernicus global ocean physical reanalysis,with data covering the vertical variation of temperature from the sea surface to 1000 m below the sea surface.We compared five mainstream models that are commonly used for ocean temperature prediction,and the results showed that the method achieved the best prediction results at all prediction scales.
基金financially supported by National Natural Science Foundation of China(Nos.22379056,52102100)Industry foresight and common key technology research in Carbon Peak and Carbon Neutrality Special Project from Zhenjiang city(No.CG2023003)Research and Practice Innovation Plan of Postgraduate Training Innovation Project in Jiangsu Province(No.SJCX23_2164)。
文摘To solve the volume expansion and poor electrical conductivity of germanium-based anode materials,Ge/rGO/CNTs nanocomposites with three-dimensional network structure are fabricated through the dispersion of polyethylene-polypropylene glycol(F127)and reduction of hydrogen.An interesting phenomenon is discovered that F127 can break GeO_(2)polycrystalline microparticles into 100 nm nanoparticles by only physical interaction,which promotes the uniform dispersion of GeO_(2)in a carbon network structure composed of graphene(rGO)and carbon nanotubes(CNTs).As evaluated as anode material of Lithium-ion batteries,Ge/rGO/CNTs nanocomposites exhibit excellent lithium storage performance.The initial specific capacity is high to 1549.7 mAh/g at 0.2 A/g,and the reversible capacity still retains972.4 mAh/g after 100 cycles.The improved lithium storage performance is attributed to that Ge nanoparticles can effectively slow down the volume expansion during charge and discharge processes,and threedimensional carbon networks can improve electrical conductivity and accelerate lithium-ion transfer of anode materials.
文摘The Metropolitan Area Network (MAN) has faced serious problems after years of rapid development. The model of three-dimensional IP-based MAN, proposed by ZTE, is a next-generation MAN solution, which not only solves the existing problems but also brings new ideas for the development of next-generation MAN.
文摘The simulation of salinity at different locations of a tidal river using physically-based hydrodynamic models is quite cumbersome because it requires many types of data, such as hydrological and hydraulic time series at boundaries, river geometry, and adjusted coefficients. Therefore, an artificial neural network (ANN) technique using a back-propagation neural network (BPNN) and a radial basis function neural network (RBFNN) is adopted as an effective alternative in salinity simulation studies. The present study focuses on comparing the performance of BPNN, RBFNN, and three-dimensional hydrodynamic models as applied to a tidal estuarine system. The observed salinity data sets collected from 18 to 22 May, 16 to 22 October, and 26 to 30 October 2002 (totaling 4320 data points) were used for BPNN and RBFNN model training and for hydrodynamic model calibration. The data sets collected from 30 May to 2 June and 11 to 15 November 2002 (totaling 2592 data points) were adopted for BPNN and RBFNN model verification and for hydrodynamic model verification. The results revealed that the ANN (BPNN and RBFNN) models were capable of predicting the nonlinear time series behavior of salinity to the multiple forcing signals of water stages at different stations and freshwater input at upstream boundaries. The salinity predicted by the ANN models was better than that predicted by the physically based hydrodynamic model. This study suggests that BPNN and RBFNN models are easy-to-use modeling tools for simulating the salinity variation in a tidal estuarine system.
基金supported by the Foundation of Provincial Natural Science Research Project of Anhui Colleges(No.KJ2021ZD0047)the Anhui Provincial Natural Science Foundation(No.2008085J27)+1 种基金the China Postdoctoral Science Foundation(No.2019M652160)the Research Foundation of the Institute of Environment-friendly Materials and Occupational Health(Wuhu),Anhui University of Science and Technology(No.ALW2020YF05).
文摘The development of graphene-based composites with low density,robust absorption,wide bandwidth and thin thickness remained a great challenge in the field of electromagnetic(EM)absorption.In this work,nitrogen-doped reduced graphene oxide/hollow cobalt ferrite(NRGO/hollow CoFe_(2)O_(4))composite aerogels were constructed by a solvothermal and hydrothermal two-step route.Results demonstrated that the as-fabricated composite aerogels had the ultralow density and a unique three-dimensional(3D)network structure,and lots of hollow CoFe_(2)O_(4)microspheres were almost homogeneously distributed on the wrinkled surfaces of lamellar NRGO.Moreover,superior EM absorbing capacity could be achieved by modulating the ferrite structure,addition amounts of hollow CoFe_(2)O_(4)and thicknesses.It was noteworthy that the NRGO/hollow CoFe_(2)O_(4)composite aerogel with the addition amount of ferrite of 15.0 mg pos-sessed the minimum reflection loss of-44.7 dB and maximum absorption bandwidth of 5.2 GHz(from 12.6 to 17.8 GHz)at a very thin thickness of 1.8 mm and filling ratio of 15.0 wt.%.Furthermore,the possible EM attenuation mechanism had been proposed.The results of this work would be helpful for developing RGO-based 3D composites as lightweight,thin and highly efficient EM wave absorbers.
基金financial support from the National Natural Science Foundation of China(No.52072276)Hubei Important Project on Science and Technology(No.2022BECO20).
文摘Al-Si alloy,a high temperature phase change material,has great potential in thermal management due to its advantages of high heat storage density and thermal conductivity.Microencapsulation of Al-Si alloy is one of the effective techniques to solve high temperature leakage and corrosion.In this paper,commercial Al-10Si alloy micro powders were encapsulated with flexible ceramic shells whose total thickness is below 1μm by hydrothermal treatment and heat treatment in N_(2) atmosphere.The compositions and microstructures were characterized by XRD,SEM and TEM.The shell was composed of AlN fibers network structure embedded withα-Al_(2)O_(3)/AlN which prevented the alloy from leaking and oxidizing,as well as had excellent thermal stability.The latent heat of microcapsules was 351.8 J g^(-1)for absorption and 372.7 J g^(-1)for exothermic.The microcapsules showed near zero thermal performance loss with latent heat storage(LHS)/release(LHR)was 353.2/403.7 J g^(-1)after 3000 cycles.Compared with the published Al-Si alloy microcapsules,both high heat storage density and super thermal cycle stability were achieved,showing promising development prospects in high temperature thermal management.
基金National Natural Science Foundation of China(No.51974209)the Natural Science Foundation of Hubei Province of China(Nos.2013CFA021,2017CFB401,2018CFA022)。
文摘Several challenging issues,such as the poor conductivity of sulfur,shuttle effects,large volume change of cathode,and the dendritic lithium in anode,have led to the low utilization of sulfur and hampered the commercialization of lithium–sulfur batteries.In this study,a novel three-dimensionally interconnected network structure comprising Co9 S8 and multiwalled carbon nanotubes(MWCNTs)was synthesized by a solvothermal route and used as the sulfur host.The assembled batteries delivered a specific capacity of1154 m Ah g-1 at 0.1 C,and the retention was 64%after 400 cycles at 0.5 C.The polar and catalytic Co9 S8 nanoparticles have a strong adsorbent effect for polysulfide,which can effectively reduce the shuttling effect.Meanwhile,the three-dimensionally interconnected CNT networks improve the overall conductivity and increase the contact with the electrolyte,thus enhancing the transport of electrons and Li ions.Polysulfide adsorption is greatly increased with the synergistic effect of polar Co9 S8 and MWCNTs in the three-dimensionally interconnected composites,which contributes to their promising performance for the lithium–sulfur batteries.
基金This work was supported by the National Natural Science Foundation of China (No. 50572040)
文摘The title complex Mn（H2O）2（HNic）2 （C22H12MnN2O8, Mr = 367.18） crystallizes in monoclinic, space group P21/c with a = 7.5735（8）, b = 12.5295（13）, c = 7.6466（8）A.β = 101.2790（10）°, Z = 2, V= 711.59（13） A^3, D, = 1.714 g/cm^3,μ（MoKa） = 0.974 mm^-1, F（000） = 374, R1 （1255 observed reflections （Ⅰ 〉 2σ（Ⅰ）） = 0.0250） and wR2 = 0.0662 （all data）. In this paper, we report the complexation of Mn（Ⅱ） by the bidentate ligand 2-hydroxynicotinic acid （HNic）. In the crystal the Mn（Ⅱ） ion exhibits a deformed octahedron structure. The title complex Mn（H2O）2（HNic）2 has a three-dimensional （3D） network structure extended by hydrogen bonds, which are formed by two typical eight-membered hydrogen-bonded rings.
