The root system actively reacts to mechanical stimuli in its environment,transmitting mechanical signals to optimize the utilization of environmental resources.While the mechanical impedance created by the growth medi...The root system actively reacts to mechanical stimuli in its environment,transmitting mechanical signals to optimize the utilization of environmental resources.While the mechanical impedance created by the growth medium serves as the primary source of stimulation for the roots,extensive research has focused on the roots'response to static mechanical stimulation.However,the impact of dynamic mechanical stimulation on root phenotype remains underexplored.In this study,we utilized a low acyl gellan gum/polyacrylamide(GG/PAM)double network elastic hydrogel as the growth medium for rapeseed.We constructed a mechanical device to investigate the effects of reciprocating extrusion stimulation on the growth of the rapeseed root system.After three weeks of mechanical stimulation,the root system exhibited a significant increase in lateral roots.This branching enhanced the roots'anchoring and penetration into the hydrogel,thereby improving the root system's adaptability to its environment.Our findings offer valuable data and insights into the effects of reciprocating mechanical stimulation on root growth,providing a new way for engineering root phenotype.展开更多
A gel based on polyacrylamide,exhibiting delayed crosslinking characteristics,emerges as the preferred solution for mitigating degradation under conditions of high temperature and extended shear in ultralong wellbores...A gel based on polyacrylamide,exhibiting delayed crosslinking characteristics,emerges as the preferred solution for mitigating degradation under conditions of high temperature and extended shear in ultralong wellbores.High viscosity/viscoelasticity of the fracturing fluid was required to maintain excellent proppant suspension properties before gelling.Taking into account both the cost and the potential damage to reservoirs,polymers with lower concentrations and molecular weights are generally preferred.In this work,the supramolecular action was integrated into the polymer,resulting in significant increases in the viscosity and viscoelasticity of the synthesized supramolecular polymer system.The double network gel,which is formed by the combination of the supramolecular polymer system and a small quantity of Zr-crosslinker,effectively resists temperature while minimizing permeability damage to the reservoir.The results indicate that the supramolecular polymer system with a molecular weight of(268—380)×10^(4)g/mol can achieve the same viscosity and viscoelasticity at 0.4 wt%due to the supramolecular interaction between polymers,compared to the 0.6 wt%traditional polymer(hydrolyzed polyacrylamide,molecular weight of 1078×10^(4)g/mol).The supramolecular polymer system possessed excellent proppant suspension properties with a 0.55 cm/min sedimentation rate at 0.4 wt%,whereas the0.6 wt%traditional polymer had a rate of 0.57 cm/min.In comparison to the traditional gel with a Zrcrosslinker concentration of 0.6 wt%and an elastic modulus of 7.77 Pa,the double network gel with a higher elastic modulus(9.00 Pa)could be formed only at 0.1 wt%Zr-crosslinker,which greatly reduced the amount of residue of the fluid after gel-breaking.The viscosity of the double network gel was66 m Pa s after 2 h shearing,whereas the traditional gel only reached 27 m Pa s.展开更多
We developed a fluorescent double network hydrogel with ionic responsiveness and high mechanical properties for visual detection.The nanocomposite hydrogel of laponite and polyacrylamide serves as the first network,wh...We developed a fluorescent double network hydrogel with ionic responsiveness and high mechanical properties for visual detection.The nanocomposite hydrogel of laponite and polyacrylamide serves as the first network,while the ionic cross-linked hydrogel of terbium ions and sodium alginate serves as the second network.The double-network structure,the introduction of nanoparticles and the reversible ionic crosslinked interactions confer high mechanical properties to the hydrogel.Terbium ions are not only used as the ionic cross-linked points,but also used as green emitters to endow hydrogels with fluorescent properties.On the basis of the “antenna effect” of terbium ions and the ion exchange interaction,the fluorescence of the hydrogels can make selective responses to various ions(such as organic acid radical ions,transition metal ions) in aqueous solutions,which enables a convenient strategy for visual detection toward ions.Consequently,the fluorescent double network hydrogel fabricated in this study is promising for use in the field of visual sensor detection.展开更多
Multi-wall carbon nanotube filled shape memory polymer composite(MWCNT/SMC)possessed enhanced modulus,strength,and electric conductivity,as well as excellent electrothermal shape memory properties,showing wide design ...Multi-wall carbon nanotube filled shape memory polymer composite(MWCNT/SMC)possessed enhanced modulus,strength,and electric conductivity,as well as excellent electrothermal shape memory properties,showing wide design scenarios and engineering application prospects.The thermoelectrically triggered shape memory process contains complex multi-physical mechanisms,especially when coupled with finite deformation rooted on micro-mechanisms.A multi-physical finite deformation model is necessary to get a deep understanding on the coupled electro-thermomechanical properties of electrothermal shape memory composites(ESMCs),beneficial to its design and wide application.Taking into consideration of micro-physical mechanisms of the MWCNTs interacting with double-chain networks,a finite deformation theoretical model is developed in this work based on two superimposed network chains of physically crosslinked network formed among MWCNTs and the chemically crosslinked network.An intact crosslinked chemical network is considered featuring with entropic-hyperelastic properties,superimposed with a physically crosslinked network where percolation theory is based on electric conductivity and electric-heating mechanisms.The model is calibrated by experiments and used for shape recoveries triggered by heating and electric fields.It captures the coupled electro-thermomechanical behavior of ESMCs and provides design guidelines for MWCNTs filled shape memory polymers.展开更多
Hydrogels with good antifouling and mechanical properties as well as biocompatibility have great application potential in the field of biomedicine.In this paper,a newly double network(DN)hydrogel was prepared based on...Hydrogels with good antifouling and mechanical properties as well as biocompatibility have great application potential in the field of biomedicine.In this paper,a newly double network(DN)hydrogel was prepared based on zwitterionic material sulfobetaine methacrylate(SBMA)and natural polysaccharide,sodium alginate(SA).The PSBMA network is covalently crosslinked while the SA network is ionically crosslinked by Ca^(2+).The hybrid crosslinked double network structure endows the DN hydrogel with excellent mechanical properties(E=0.19±0.01 MPa,σ=0.73±0.03 MPa),fast self-recovery ability as well as excellent fatigue resistance.Moreover,the results show that the PSBMA/SA-Ca^(2+)DN hydrogel is biocompatible and resists the absorption of non-specific proteins and adhesion of microorganisms,such as cells and algae,exhibiting outstanding antifouling properties.These unique characteristics of PSBMA/SA-Ca^(2+)DN hydrogel make it a promising candidate for biomedical application,such as artificial connective tissues,implantable devices,and underwater equipment.展开更多
Developing a low-cost and well-recyclable adsorbent with high adsorption capacity is greatly desirable in dye wastewater treatment. Here, we demonstrate a kind of novel tough and reusable hydrogel beads with quite hig...Developing a low-cost and well-recyclable adsorbent with high adsorption capacity is greatly desirable in dye wastewater treatment. Here, we demonstrate a kind of novel tough and reusable hydrogel beads with quite high capacity of dye adsorption via incorporating mussel-bioinspired poly（L-DOPA） （PDOPA） into alginate/poly（acrylamide） double network （DN） hydrogels. The synthesized PDOPA nanoaggregates were introduced into the DN hydrogels by simple one-pot mixing with the monomers prior to polymerization. The fabricated hydrogel beads exhibited high mechanical strength and good elastic recovery due to the interpenetrating Ca2＋-alginate and poly（acrylamide） networks. It was shown that the beads exhibited relatively high dye adsorption capacity compared to other adsorbents reported in literature, and the introduction of PDOPA with an appropriate amount raised the adsorption capacity. It is believed that the addition of PDOPA and the matrix of double network architecture contributed synergistically to the high adsorption capacity of hydrogel beads. Moreover, the desorption of dyes could be easily realized via rinsing in acidic water and ethanol solution. The hydrogel beads remained the high adsorption capacity even after 5 times of adsorption and desorption cycles. This tough and stable hydrogel with high adsorption capacity may have potential in treatment of dye wastewater released by textile dyeing industry.展开更多
A shape-memory double network hydrogel consists of two polymer networks:a chemically crosslinked primary network that is responsible for the permanent shape and a physically crosslinked secondary network that is used ...A shape-memory double network hydrogel consists of two polymer networks:a chemically crosslinked primary network that is responsible for the permanent shape and a physically crosslinked secondary network that is used to fix the temporary shapes.The formation/melting transition of the secondary network serves as an effective mechanism for the double network hydrogel’s shape-memory effect.When the crosslinks in the secondary network are dissociated by applying an external stimulus,only the primary network is left to support the load.When the secondary network is re-formed by removing the stimulus,both the primary and secondary networks support the load.In the past,models have been developed for the constitutive behaviors of double network hydrogels,but the model of shape-memory double network hydrogels is still lacking.This work aims to build a constitutive model for the polyacrylamide-gelatin double network shape-memory hydrogel developed in our previous work.The model is first calibrated by experimental data of the double network shape-memory hydrogel under uniaxial loading and then employed to predict the shape-fixing performance of the hydrogel.The model is also implemented into a three-dimension finite element code and utilized to simulate the shape-memory behavior of the double network hydrogel with inhomogeneous deformations related to applications.展开更多
In the present research,enzyme encapsulated hydrogels（single gels and double network gels）and enzyme immobilized magnetic beads,which allow high-throughput screening,were fabricated and evaluated in terms of the pre...In the present research,enzyme encapsulated hydrogels（single gels and double network gels）and enzyme immobilized magnetic beads,which allow high-throughput screening,were fabricated and evaluated in terms of the preservation,precision, and repeatability of enzyme activity.The fabricated gels and magnetic beads were analyzed in a 96-well microassay plate.Trypsin was successfully encapsulated in both types of gels and immobilized to the magnetic beads.However,pepsin,either encapsulated in the gels or immobilized to the magnetic beads,could not react with its substrates.The adaptability to various enzymes （e.g.,trypsin,β-glucuronidase,and CYP1A1）in the single gels and magnetic beads was superior to that in double network gels.However,the soak out of the enzymes was observed in the single gels.The double network gels could encapsulate trypsin,whereas the fabrication of the other enzymes（e.g.β-glucuronidase,CYP1A1,and pepsin）failed because of the inactivation of the enzymes by acryl amide and ammonium peroxodisulfate,which are the components of the gel formulation. The enzyme reaction in the magnetic beads exhibited the highest efficiency among the three fabrication methods.Furthermore, the stability of the enzymes immobilized to the magnetic beads was better than that fabricated by the other methods,and the activities of trypsin andβ-glucuronidase did not decline for up to one week.In addition,in the magnetic beads,the activities of trypsin andβ-glucuronidase can be well repeated.Hence,although the adaptability of the double network gels to various enzymes is currently limited,the efficiency of the enzyme encapsulation can be improved by optimizing the formulation of acryl amide gels.展开更多
The double-network prepared with an in-situ monomer gel and a fast-crosslinked Cr(III) gel is introduced to develop a thixotropic and high-strength gel (THSG), which is found to have many advantages over the tradition...The double-network prepared with an in-situ monomer gel and a fast-crosslinked Cr(III) gel is introduced to develop a thixotropic and high-strength gel (THSG), which is found to have many advantages over the traditional gels. The THSG gel demonstrates remarkable thermal stability, and no syneresis is observed after 12 months with high salinity brine (95,500 mg/L). Moreover, the SEM and XRD results indicate that the gel is intercalated into the lamellar structures of Na-MMT, where the gel can form a uniform and compact structure. In addition, the THSG gel has an excellent swelling behavior, even in the high salinity brine. In the slim tube experiments, the THSG gel exhibits high rupture pressure and improves blocking capacity after being ruptured. The core flooding results show that a layer of gel filter cake is formed on the face of the fracture, which may be promoted by a high matrix permeability, a small aperture fracture, and a high injection rate. After the gel treatment, the fracture can be completely blocked by the THSG gel. It is found that a high incremental oil recovery (65.3%) can be achieved when the fracture was completely blocked, compared to 40.2% if the gel is ruptured. Although the swelling of ruptured gel can improve oil recovery, part of the injected brine may be channeled through the gel-filled fractures, resulting in a decrease in the sweep efficiency. Therefore, the improved blocking ability by gel swelling (e.g., in fresh water) may be less efficient to contribute to an enhancement of oil recovery. It is also found that the pressure gradient and residual resistance factor to water (Frrw) are higher if the matrix is less permeable, indicating that the fractured reservoir with lower matrix permeability may require a higher gel strength for treatment. The findings of this study may provide novel insights on designing robust double network gels for water shutoff in fractured reservoirs.展开更多
Double network(DN)hydrogels as one kind of tough gels have attracted extensive at-tention for their potential applications in biomedical and load-bearing fields.Herein,we import more functions like shape memory into t...Double network(DN)hydrogels as one kind of tough gels have attracted extensive at-tention for their potential applications in biomedical and load-bearing fields.Herein,we import more functions like shape memory into the conventional tough DN hydro-gel system.We synthesize the PEG-PDAC/P(AAm-co-AAc)DN hydrogels,of which the first network is a well-defined PEG(polyethylene glycol)network loaded with PDAC(poly(acryloyloxyethyltrimethyl ammonium chloride))strands,while the second network is formed by copolymerizing AAm(acrylamide)with AAc(acrylic acid)and cross-linker MBAA(N;N′-methylenebisacrylamide).The PEG-PDAC/P(AAm-co-AAc)DN gels exhibits high mechanical strength.The fracture stress and toughness of the DN gels reach up to 0.9 MPa and 3.8 MJ/m^3,respectively.Compared with the conventional double network hydrogels with neutral polymers as the soft and ductile second network,the PEG-PDAC/P(AAm-co-AAc)DN hydrogels use P(AAm-co-AAc),a weak polyelectrolyte,as the second network.The AAc units serve as the coordination points with Fe^3+ions and physically crosslink the second network,which realizes the shape memory property activated by the reducing ability of ascorbic acid.Our results indicate that the high mechanical strength and shape memory properties,probably the two most important characters related to the potential application of the hydrogels,can be introduced simultaneously into the DN hydrogels if the functional monomer has been integrated into the network of DN hydrogels smartly.展开更多
A conventional solid-state process was used to synthesize the double perovskite materials HoRCoMnO_(6)(R=Ho,Gd,Eu,Nd).The structural properties of the compounds were investigated using X-ray powder diffraction(XRD).Th...A conventional solid-state process was used to synthesize the double perovskite materials HoRCoMnO_(6)(R=Ho,Gd,Eu,Nd).The structural properties of the compounds were investigated using X-ray powder diffraction(XRD).The results revealed that Ho_(2)CoMnO_(6) crystallizes in a monoclinic structure with the P2_(1)/n space group.In contrast,the other compounds HoRCoMnO_(6)(R=Gd,Eu,or Nd) exhibit an orthorhombic structure with the Pnma space group.As a result,the average crystallite size also changes as a function of rare-earth element doping.This investigation reveals that the magnetic properties of the compounds studied are significantly dependent on the doping elements.The Curie temperature T_C,for example,increases from 80 to 118℃ with the ionic radii of rare earths increasing.Furthermore,the study of the magnetocaloric effect(MCE) shows that the maximum of the entropy variation(-ΔS_(M)^(max)) increases from 4.97 to 6.06 J/(kg·K) under a magnetic field of 5 T with substitution by rare-earth ions.To examine the efficiency of MCE materials,the relative cooling power(RCP) was evaluated and is found to increase with increment of rare-earth radius till 406.69 J/kg for Nd.The mean entropy variation with tempe rature(TEC) was also studied.Due to their significant magnetocaloric performance,HoRCoMnO_(6)(noted as HRCMO) compounds(with R=Ho,Gd,Eu or Nd) could be good candidates for low-temperature magnetic cooling applications.展开更多
Cooling system design applicable to more than one photovoltaic(PV)unit may be challenging due to the arrangement and geometry of the modules.Different cooling techniques are provided in this study to regulate the temp...Cooling system design applicable to more than one photovoltaic(PV)unit may be challenging due to the arrangement and geometry of the modules.Different cooling techniques are provided in this study to regulate the temperature of conductive panels that are arranged perpendicular to each other.The model uses two vented cavity systems and one L-shaped channel with ternary nanofluid enhanced non-uniform magnetic field.Their cooling performances and comparative results between different systems are provided.The finite element method is used to conduct a numerical analysis for a range of values of the following:the strength of themagnetic field(Hartmann number(Ha)between 0 and 50),the inclination of the magnetic field(γbetween 0 and 90),and the loading of nanoparticles in the base fluid(ϕbetween 0 and 0.03),taking into account both uniformand non-uniformmagnetic fields.For the L-shaped channel and vented cavities,vortex size is controlled by imposing magnetic field and adjusting its strength.Whether uniform or non-uniform magnetic field is applied affects the cooling performances for different cooling configurations.Temperature drops of the horizontal panel with different magnetic field strengths by using channel cooling,vented cavity-1 and vented cavity-2 systems for uniformmagnetic are 11℃,21.5℃,and 3℃when the reference case of Ha=0 is considered for the same cooling systems.However,they become 9.5℃,13.5℃,and 12.5℃when nonuniform magnetic field is used.In the presence of uniform magnetic field effects and changing its magnitude,the use of cooling channel in vented cavity-1 and vented cavity-2 systems results in temperature drops of 4℃,10.8℃,and 3.8℃for vertical panels.On the other hand,when non-uniform magnetic field effects are present,they become 0.5℃,2.1℃,and 9℃.For L-channel cooling,the average Nu for the horizontal panel is more affected byγ,andNu rises asγrises.With increasing nanoparticle loading of ternary nanofluid,the average panel surface temperature shows a linear drop.For the horizontal panel,the temperature declines for nanofluid at the highest loading are 4℃,10℃,and 12℃as compared to using only base fluid.The values of 5℃,7℃,and 11℃are obtained for the vertical panel.Different cooling systems’performance is estimated using artificial neural networks.The method captures the combined impact of applying non-uniformmagnetic field and nanofluid together on the cooling performancewhile accounting for varied cooling strategies for both panels.展开更多
Satellite and terrestrial cellular networks can be integrated together to achieve extended broad-band coverage for,e.g.,maritime communication sce-narios,in the upcoming sixth-generation(6G)era.To counter spectrum sca...Satellite and terrestrial cellular networks can be integrated together to achieve extended broad-band coverage for,e.g.,maritime communication sce-narios,in the upcoming sixth-generation(6G)era.To counter spectrum scarcity,collaborative spectrum sharing is considered for hybrid satellite-terrestrial networks(HSTNs)in this paper.With only slowly-varying large-scale channel state information(CSI),joint power and channel allocation is implemented for terrestrial mobile terminals(MTs)which share the same frequency band with the satellite MTs oppor-tunistically.Specially,strict quality service assurance is adopted for terrestrial MTs under the constraint of leakage interference to satellite MTs.With the tar-get of maximizing both the number of served terres-trial MTs and the average sum transmission rate,a double-target spectrum sharing problem is formulated.To solve the complicated mixed integer programming(MIP)problem efficiently,user-centric channel pools are introduced.Simulations demonstrate that the proposed spectrum sharing scheme could achieve a significant performance gain for the HSTN.展开更多
Layered double hydroxides(LDHs)are potential cathode materials for aqueous magnesium-ion batteries(AMIBs).However,the low capacity and sluggish kinetics significantly limit their electrochemical performance in AMIBs.H...Layered double hydroxides(LDHs)are potential cathode materials for aqueous magnesium-ion batteries(AMIBs).However,the low capacity and sluggish kinetics significantly limit their electrochemical performance in AMIBs.Herein,we find that oxygen vacancies can significantly boost the capacity,electrochemical kinetics,and structure stability of LDHs.The corresponding structure-performance relationship and energy storage mechanism are elaborated through exhaustive in/ex-situ experimental characterizations and density functional theory(DFT)calculations.Specially,in-situ Raman and DFT calculations reveal that oxygen vacancies elevate orbital energy of O 2p and electron density of O atoms,thereby enhancing the orbital hybridization of O 2p with Ni/Co 3d.This facilitates electron transfer between O and adjacent Ni/Co atoms and improves the covalency of Ni–O and Co–O bonds,which activates Ni/Co atoms to release more capacity and stabilizes the Ov-NiCo-LDH structure.Moreover,the distribution of relaxation times(DRT)and molecular dynamics(MD)simulations disclose that the enhanced d-p orbital hybridization optimizes the electronic structure of Ov-NiCo-LDH,which distinctly reduces the diffusion energy barriers of Mg^(2+)and improves the charge transfer kinetics of Ov-NiCo-LDH.Consequently,the assembled Ov-NiCo-LDH//active carbon(AC)and Ov-NiCo-LDH//perylenediimide(PTCDI)AMIBs can both deliver high specific discharge capacity(182.7 and 59.4 mAh g^(−1)at 0.5 A g^(−1),respectively)and long-term cycling stability(85.4%and 89.0%of capacity retentions after 2500 and 2400 cycles at 1.0 A g^(−1),respectively).In addition,the practical prospects for Ov-NiCo-LDH-based AMIBs have been demonstrated in different application scenarios.This work not only provides an effective strategy for obtaining high-performance cathodes of AMIBs,but also fundamentally elucidates the inherent mechanisms.展开更多
With the advancement of Vehicle-to-Everything(V2X)technology,efficient resource allocation in dynamic vehicular networks has become a critical challenge for achieving optimal performance.Existing methods suffer from h...With the advancement of Vehicle-to-Everything(V2X)technology,efficient resource allocation in dynamic vehicular networks has become a critical challenge for achieving optimal performance.Existing methods suffer from high computational complexity and decision latency under high-density traffic and heterogeneous network conditions.To address these challenges,this study presents an innovative framework that combines Graph Neural Networks(GNNs)with a Double Deep Q-Network(DDQN),utilizing dynamic graph structures and reinforcement learning.An adaptive neighbor sampling mechanism is introduced to dynamically select the most relevant neighbors based on interference levels and network topology,thereby improving decision accuracy and efficiency.Meanwhile,the framework models communication links as nodes and interference relationships as edges,effectively capturing the direct impact of interference on resource allocation while reducing computational complexity and preserving critical interaction information.Employing an aggregation mechanism based on the Graph Attention Network(GAT),it dynamically adjusts the neighbor sampling scope and performs attention-weighted aggregation based on node importance,ensuring more efficient and adaptive resource management.This design ensures reliable Vehicle-to-Vehicle(V2V)communication while maintaining high Vehicle-to-Infrastructure(V2I)throughput.The framework retains the global feature learning capabilities of GNNs and supports distributed network deployment,allowing vehicles to extract low-dimensional graph embeddings from local observations for real-time resource decisions.Experimental results demonstrate that the proposed method significantly reduces computational overhead,mitigates latency,and improves resource utilization efficiency in vehicular networks under complex traffic scenarios.This research not only provides a novel solution to resource allocation challenges in V2X networks but also advances the application of DDQN in intelligent transportation systems,offering substantial theoretical significance and practical value.展开更多
We present a gain adaptive tuning method for fiber Raman amplifier(FRA) using two-stage neural networks(NNs) and double weights updates. After training the connection weights of two-stage NNs separately in training ph...We present a gain adaptive tuning method for fiber Raman amplifier(FRA) using two-stage neural networks(NNs) and double weights updates. After training the connection weights of two-stage NNs separately in training phase, the connection weights of the unified NN are updated again in verification phase according to error between the predicted and target gains to eliminate the inherent error of the NNs. The simulation results show that the mean of root mean square error(RMSE) and maximum error of gains are 0.131 d B and 0.281 d B, respectively. It shows that the method can realize adaptive adjustment function of FRA gain with high accuracy.展开更多
Zn metal anode suffers from dendrite issues and passive byproducts,which severely plagues the practical application of aqueous Zn metal batteries.Herein,a polyzwitterionic cross-linked double network hydrogel electrol...Zn metal anode suffers from dendrite issues and passive byproducts,which severely plagues the practical application of aqueous Zn metal batteries.Herein,a polyzwitterionic cross-linked double network hydrogel electrolyte composed of physical crosslinking(hyaluronic acid)and chemical crosslinking(synthetic zwitterionic monomer copolymerized with acrylamide)is introduced to overcome these obstacles.On the one hand,highly hydrophilic physical network provides an energy dissipation channel to buffer stress and builds a H_(2)O-poor interface to avoid side reactions.On the other hand,the charged groups(sulfonic and imidazolyl)in chemical crosslinking structure build anion/cation transport channels to boost ions’kinetics migration and regulate the typical solvent structure[Zn(H_(2)O)_(6)]^(2+)to R-SO_(3)^(−)[Zn(H_(2)O)_(4)]^(2+),with uniform electric field distribution and significant resistance to dendrites and parasitic reactions.Based on the above functions,the symmetric zinc cell exhibits superior cycle stability for more than 420 h at a high current density of 5 mA·cm^(−2),and Zn||MnO_(2)full cell has a reversible specific capacity of 150 mAh·g^(−1)after 1000 cycles at 2 C with this hydrogel electrolyte.Furthermore,the pouch cell delivers impressive flexibility and cyclability for energy-storage applications.展开更多
The application of mathematical modeling to biological fluids is of utmost importance, as it has diverse applicationsin medicine. The peristaltic mechanism plays a crucial role in understanding numerous biological flo...The application of mathematical modeling to biological fluids is of utmost importance, as it has diverse applicationsin medicine. The peristaltic mechanism plays a crucial role in understanding numerous biological flows. In thispaper, we present a theoretical investigation of the double diffusion convection in the peristaltic transport of aPrandtl nanofluid through an asymmetric tapered channel under the combined action of thermal radiation andan induced magnetic field. The equations for the current flow scenario are developed, incorporating relevantassumptions, and considering the effect of viscous dissipation. The impact of thermal radiation and doublediffusion on public health is of particular interest. For instance, infrared radiation techniques have been used totreat various skin-related diseases and can also be employed as a measure of thermotherapy for some bones toenhance blood circulation, with radiation increasing blood flow by approximately 80%. To solve the governingequations, we employ a numerical method with the aid of symbolic software such as Mathematica and MATLAB.The velocity, magnetic force function, pressure rise, temperature, solute (species) concentration, and nanoparticlevolume fraction profiles are analytically derived and graphically displayed. The results outcomes are compared withthe findings of limiting situations for verification.展开更多
By integrating deep neural networks with reinforcement learning,the Double Deep Q Network(DDQN)algorithm overcomes the limitations of Q-learning in handling continuous spaces and is widely applied in the path planning...By integrating deep neural networks with reinforcement learning,the Double Deep Q Network(DDQN)algorithm overcomes the limitations of Q-learning in handling continuous spaces and is widely applied in the path planning of mobile robots.However,the traditional DDQN algorithm suffers from sparse rewards and inefficient utilization of high-quality data.Targeting those problems,an improved DDQN algorithm based on average Q-value estimation and reward redistribution was proposed.First,to enhance the precision of the target Q-value,the average of multiple previously learned Q-values from the target Q network is used to replace the single Q-value from the current target Q network.Next,a reward redistribution mechanism is designed to overcome the sparse reward problem by adjusting the final reward of each action using the round reward from trajectory information.Additionally,a reward-prioritized experience selection method is introduced,which ranks experience samples according to reward values to ensure frequent utilization of high-quality data.Finally,simulation experiments are conducted to verify the effectiveness of the proposed algorithm in fixed-position scenario and random environments.The experimental results show that compared to the traditional DDQN algorithm,the proposed algorithm achieves shorter average running time,higher average return and fewer average steps.The performance of the proposed algorithm is improved by 11.43%in the fixed scenario and 8.33%in random environments.It not only plans economic and safe paths but also significantly improves efficiency and generalization in path planning,making it suitable for widespread application in autonomous navigation and industrial automation.展开更多
With the rapid development ofmobile Internet,spatial crowdsourcing has becomemore andmore popular.Spatial crowdsourcing consists of many different types of applications,such as spatial crowd-sensing services.In terms ...With the rapid development ofmobile Internet,spatial crowdsourcing has becomemore andmore popular.Spatial crowdsourcing consists of many different types of applications,such as spatial crowd-sensing services.In terms of spatial crowd-sensing,it collects and analyzes traffic sensing data from clients like vehicles and traffic lights to construct intelligent traffic prediction models.Besides collecting sensing data,spatial crowdsourcing also includes spatial delivery services like DiDi and Uber.Appropriate task assignment and worker selection dominate the service quality for spatial crowdsourcing applications.Previous research conducted task assignments via traditional matching approaches or using simple network models.However,advanced mining methods are lacking to explore the relationship between workers,task publishers,and the spatio-temporal attributes in tasks.Therefore,in this paper,we propose a Deep Double Dueling Spatial-temporal Q Network(D3SQN)to adaptively learn the spatialtemporal relationship between task,task publishers,and workers in a dynamic environment to achieve optimal allocation.Specifically,D3SQNis revised through reinforcement learning by adding a spatial-temporal transformer that can estimate the expected state values and action advantages so as to improve the accuracy of task assignments.Extensive experiments are conducted over real data collected fromDiDi and ELM,and the simulation results verify the effectiveness of our proposed models.展开更多
基金supporting from Shanghai Pujiang Program(23PJ1400400)DHU startup grant,the Fundamental Research Funds for the Central Universities,DHU Distinguished Young Professor Program.
文摘The root system actively reacts to mechanical stimuli in its environment,transmitting mechanical signals to optimize the utilization of environmental resources.While the mechanical impedance created by the growth medium serves as the primary source of stimulation for the roots,extensive research has focused on the roots'response to static mechanical stimulation.However,the impact of dynamic mechanical stimulation on root phenotype remains underexplored.In this study,we utilized a low acyl gellan gum/polyacrylamide(GG/PAM)double network elastic hydrogel as the growth medium for rapeseed.We constructed a mechanical device to investigate the effects of reciprocating extrusion stimulation on the growth of the rapeseed root system.After three weeks of mechanical stimulation,the root system exhibited a significant increase in lateral roots.This branching enhanced the roots'anchoring and penetration into the hydrogel,thereby improving the root system's adaptability to its environment.Our findings offer valuable data and insights into the effects of reciprocating mechanical stimulation on root growth,providing a new way for engineering root phenotype.
基金financially supported by the National Natural Science Foundation of China(Nos.52120105007 and 52374062)the Innovation Fund Project for Graduate Students of China University of Petroleum(East China)supported by“the Fundamental Research Funds for the Central Universities”(23CX04047A)。
文摘A gel based on polyacrylamide,exhibiting delayed crosslinking characteristics,emerges as the preferred solution for mitigating degradation under conditions of high temperature and extended shear in ultralong wellbores.High viscosity/viscoelasticity of the fracturing fluid was required to maintain excellent proppant suspension properties before gelling.Taking into account both the cost and the potential damage to reservoirs,polymers with lower concentrations and molecular weights are generally preferred.In this work,the supramolecular action was integrated into the polymer,resulting in significant increases in the viscosity and viscoelasticity of the synthesized supramolecular polymer system.The double network gel,which is formed by the combination of the supramolecular polymer system and a small quantity of Zr-crosslinker,effectively resists temperature while minimizing permeability damage to the reservoir.The results indicate that the supramolecular polymer system with a molecular weight of(268—380)×10^(4)g/mol can achieve the same viscosity and viscoelasticity at 0.4 wt%due to the supramolecular interaction between polymers,compared to the 0.6 wt%traditional polymer(hydrolyzed polyacrylamide,molecular weight of 1078×10^(4)g/mol).The supramolecular polymer system possessed excellent proppant suspension properties with a 0.55 cm/min sedimentation rate at 0.4 wt%,whereas the0.6 wt%traditional polymer had a rate of 0.57 cm/min.In comparison to the traditional gel with a Zrcrosslinker concentration of 0.6 wt%and an elastic modulus of 7.77 Pa,the double network gel with a higher elastic modulus(9.00 Pa)could be formed only at 0.1 wt%Zr-crosslinker,which greatly reduced the amount of residue of the fluid after gel-breaking.The viscosity of the double network gel was66 m Pa s after 2 h shearing,whereas the traditional gel only reached 27 m Pa s.
基金Funded by the National Natural Science Foundation of China(No.51873167)the National Innovation and Entrepreneurship Training Program for College Students(No.226801001)。
文摘We developed a fluorescent double network hydrogel with ionic responsiveness and high mechanical properties for visual detection.The nanocomposite hydrogel of laponite and polyacrylamide serves as the first network,while the ionic cross-linked hydrogel of terbium ions and sodium alginate serves as the second network.The double-network structure,the introduction of nanoparticles and the reversible ionic crosslinked interactions confer high mechanical properties to the hydrogel.Terbium ions are not only used as the ionic cross-linked points,but also used as green emitters to endow hydrogels with fluorescent properties.On the basis of the “antenna effect” of terbium ions and the ion exchange interaction,the fluorescence of the hydrogels can make selective responses to various ions(such as organic acid radical ions,transition metal ions) in aqueous solutions,which enables a convenient strategy for visual detection toward ions.Consequently,the fluorescent double network hydrogel fabricated in this study is promising for use in the field of visual sensor detection.
基金supported by the National Natural Science Foundation of China(Grant No.12172125)the Science Foundation of Hunan Province(Grant No.2022JJ30119).
文摘Multi-wall carbon nanotube filled shape memory polymer composite(MWCNT/SMC)possessed enhanced modulus,strength,and electric conductivity,as well as excellent electrothermal shape memory properties,showing wide design scenarios and engineering application prospects.The thermoelectrically triggered shape memory process contains complex multi-physical mechanisms,especially when coupled with finite deformation rooted on micro-mechanisms.A multi-physical finite deformation model is necessary to get a deep understanding on the coupled electro-thermomechanical properties of electrothermal shape memory composites(ESMCs),beneficial to its design and wide application.Taking into consideration of micro-physical mechanisms of the MWCNTs interacting with double-chain networks,a finite deformation theoretical model is developed in this work based on two superimposed network chains of physically crosslinked network formed among MWCNTs and the chemically crosslinked network.An intact crosslinked chemical network is considered featuring with entropic-hyperelastic properties,superimposed with a physically crosslinked network where percolation theory is based on electric conductivity and electric-heating mechanisms.The model is calibrated by experiments and used for shape recoveries triggered by heating and electric fields.It captures the coupled electro-thermomechanical behavior of ESMCs and provides design guidelines for MWCNTs filled shape memory polymers.
基金financially supported by the National Natural Science Foundation of China(Nos.52073256,21404091 and 21404089)the Zhejiang Provincial Natural Science Foundation of China(No.LBY21E030001)。
文摘Hydrogels with good antifouling and mechanical properties as well as biocompatibility have great application potential in the field of biomedicine.In this paper,a newly double network(DN)hydrogel was prepared based on zwitterionic material sulfobetaine methacrylate(SBMA)and natural polysaccharide,sodium alginate(SA).The PSBMA network is covalently crosslinked while the SA network is ionically crosslinked by Ca^(2+).The hybrid crosslinked double network structure endows the DN hydrogel with excellent mechanical properties(E=0.19±0.01 MPa,σ=0.73±0.03 MPa),fast self-recovery ability as well as excellent fatigue resistance.Moreover,the results show that the PSBMA/SA-Ca^(2+)DN hydrogel is biocompatible and resists the absorption of non-specific proteins and adhesion of microorganisms,such as cells and algae,exhibiting outstanding antifouling properties.These unique characteristics of PSBMA/SA-Ca^(2+)DN hydrogel make it a promising candidate for biomedical application,such as artificial connective tissues,implantable devices,and underwater equipment.
基金supported by the National Natural Science Foundation of China(Nos.51573159 and 51273176)the Fundamental Research Funds for the Central Universities(No.2016QNA4032)
文摘Developing a low-cost and well-recyclable adsorbent with high adsorption capacity is greatly desirable in dye wastewater treatment. Here, we demonstrate a kind of novel tough and reusable hydrogel beads with quite high capacity of dye adsorption via incorporating mussel-bioinspired poly（L-DOPA） （PDOPA） into alginate/poly（acrylamide） double network （DN） hydrogels. The synthesized PDOPA nanoaggregates were introduced into the DN hydrogels by simple one-pot mixing with the monomers prior to polymerization. The fabricated hydrogel beads exhibited high mechanical strength and good elastic recovery due to the interpenetrating Ca2＋-alginate and poly（acrylamide） networks. It was shown that the beads exhibited relatively high dye adsorption capacity compared to other adsorbents reported in literature, and the introduction of PDOPA with an appropriate amount raised the adsorption capacity. It is believed that the addition of PDOPA and the matrix of double network architecture contributed synergistically to the high adsorption capacity of hydrogel beads. Moreover, the desorption of dyes could be easily realized via rinsing in acidic water and ethanol solution. The hydrogel beads remained the high adsorption capacity even after 5 times of adsorption and desorption cycles. This tough and stable hydrogel with high adsorption capacity may have potential in treatment of dye wastewater released by textile dyeing industry.
基金supported by the Air Force Office of Scientific Research under Award(Grant FA9550-19-1-0395)the National Science Foundation(Grant 1935154)。
文摘A shape-memory double network hydrogel consists of two polymer networks:a chemically crosslinked primary network that is responsible for the permanent shape and a physically crosslinked secondary network that is used to fix the temporary shapes.The formation/melting transition of the secondary network serves as an effective mechanism for the double network hydrogel’s shape-memory effect.When the crosslinks in the secondary network are dissociated by applying an external stimulus,only the primary network is left to support the load.When the secondary network is re-formed by removing the stimulus,both the primary and secondary networks support the load.In the past,models have been developed for the constitutive behaviors of double network hydrogels,but the model of shape-memory double network hydrogels is still lacking.This work aims to build a constitutive model for the polyacrylamide-gelatin double network shape-memory hydrogel developed in our previous work.The model is first calibrated by experimental data of the double network shape-memory hydrogel under uniaxial loading and then employed to predict the shape-fixing performance of the hydrogel.The model is also implemented into a three-dimension finite element code and utilized to simulate the shape-memory behavior of the double network hydrogel with inhomogeneous deformations related to applications.
基金The Global COE Program from the Ministry of Education,Science,Sports,and Culture of Japan.
文摘In the present research,enzyme encapsulated hydrogels（single gels and double network gels）and enzyme immobilized magnetic beads,which allow high-throughput screening,were fabricated and evaluated in terms of the preservation,precision, and repeatability of enzyme activity.The fabricated gels and magnetic beads were analyzed in a 96-well microassay plate.Trypsin was successfully encapsulated in both types of gels and immobilized to the magnetic beads.However,pepsin,either encapsulated in the gels or immobilized to the magnetic beads,could not react with its substrates.The adaptability to various enzymes （e.g.,trypsin,β-glucuronidase,and CYP1A1）in the single gels and magnetic beads was superior to that in double network gels.However,the soak out of the enzymes was observed in the single gels.The double network gels could encapsulate trypsin,whereas the fabrication of the other enzymes（e.g.β-glucuronidase,CYP1A1,and pepsin）failed because of the inactivation of the enzymes by acryl amide and ammonium peroxodisulfate,which are the components of the gel formulation. The enzyme reaction in the magnetic beads exhibited the highest efficiency among the three fabrication methods.Furthermore, the stability of the enzymes immobilized to the magnetic beads was better than that fabricated by the other methods,and the activities of trypsin andβ-glucuronidase did not decline for up to one week.In addition,in the magnetic beads,the activities of trypsin andβ-glucuronidase can be well repeated.Hence,although the adaptability of the double network gels to various enzymes is currently limited,the efficiency of the enzyme encapsulation can be improved by optimizing the formulation of acryl amide gels.
基金financial support from the Major Scientific and Technological Projects of CNPC under Grant(ZD2019-183-007)is gratefully acknowledge.
文摘The double-network prepared with an in-situ monomer gel and a fast-crosslinked Cr(III) gel is introduced to develop a thixotropic and high-strength gel (THSG), which is found to have many advantages over the traditional gels. The THSG gel demonstrates remarkable thermal stability, and no syneresis is observed after 12 months with high salinity brine (95,500 mg/L). Moreover, the SEM and XRD results indicate that the gel is intercalated into the lamellar structures of Na-MMT, where the gel can form a uniform and compact structure. In addition, the THSG gel has an excellent swelling behavior, even in the high salinity brine. In the slim tube experiments, the THSG gel exhibits high rupture pressure and improves blocking capacity after being ruptured. The core flooding results show that a layer of gel filter cake is formed on the face of the fracture, which may be promoted by a high matrix permeability, a small aperture fracture, and a high injection rate. After the gel treatment, the fracture can be completely blocked by the THSG gel. It is found that a high incremental oil recovery (65.3%) can be achieved when the fracture was completely blocked, compared to 40.2% if the gel is ruptured. Although the swelling of ruptured gel can improve oil recovery, part of the injected brine may be channeled through the gel-filled fractures, resulting in a decrease in the sweep efficiency. Therefore, the improved blocking ability by gel swelling (e.g., in fresh water) may be less efficient to contribute to an enhancement of oil recovery. It is also found that the pressure gradient and residual resistance factor to water (Frrw) are higher if the matrix is less permeable, indicating that the fractured reservoir with lower matrix permeability may require a higher gel strength for treatment. The findings of this study may provide novel insights on designing robust double network gels for water shutoff in fractured reservoirs.
基金supported by the National Natural Science Foundation of China (No.51273189)the National Science and Technology Major Project of the Ministry of Science and Technology of China (No.2016ZX05016),the National Science and Technology Major Project of the Ministry of Science and Technology of China (No.2016ZX05046)
文摘Double network(DN)hydrogels as one kind of tough gels have attracted extensive at-tention for their potential applications in biomedical and load-bearing fields.Herein,we import more functions like shape memory into the conventional tough DN hydro-gel system.We synthesize the PEG-PDAC/P(AAm-co-AAc)DN hydrogels,of which the first network is a well-defined PEG(polyethylene glycol)network loaded with PDAC(poly(acryloyloxyethyltrimethyl ammonium chloride))strands,while the second network is formed by copolymerizing AAm(acrylamide)with AAc(acrylic acid)and cross-linker MBAA(N;N′-methylenebisacrylamide).The PEG-PDAC/P(AAm-co-AAc)DN gels exhibits high mechanical strength.The fracture stress and toughness of the DN gels reach up to 0.9 MPa and 3.8 MJ/m^3,respectively.Compared with the conventional double network hydrogels with neutral polymers as the soft and ductile second network,the PEG-PDAC/P(AAm-co-AAc)DN hydrogels use P(AAm-co-AAc),a weak polyelectrolyte,as the second network.The AAc units serve as the coordination points with Fe^3+ions and physically crosslink the second network,which realizes the shape memory property activated by the reducing ability of ascorbic acid.Our results indicate that the high mechanical strength and shape memory properties,probably the two most important characters related to the potential application of the hydrogels,can be introduced simultaneously into the DN hydrogels if the functional monomer has been integrated into the network of DN hydrogels smartly.
文摘A conventional solid-state process was used to synthesize the double perovskite materials HoRCoMnO_(6)(R=Ho,Gd,Eu,Nd).The structural properties of the compounds were investigated using X-ray powder diffraction(XRD).The results revealed that Ho_(2)CoMnO_(6) crystallizes in a monoclinic structure with the P2_(1)/n space group.In contrast,the other compounds HoRCoMnO_(6)(R=Gd,Eu,or Nd) exhibit an orthorhombic structure with the Pnma space group.As a result,the average crystallite size also changes as a function of rare-earth element doping.This investigation reveals that the magnetic properties of the compounds studied are significantly dependent on the doping elements.The Curie temperature T_C,for example,increases from 80 to 118℃ with the ionic radii of rare earths increasing.Furthermore,the study of the magnetocaloric effect(MCE) shows that the maximum of the entropy variation(-ΔS_(M)^(max)) increases from 4.97 to 6.06 J/(kg·K) under a magnetic field of 5 T with substitution by rare-earth ions.To examine the efficiency of MCE materials,the relative cooling power(RCP) was evaluated and is found to increase with increment of rare-earth radius till 406.69 J/kg for Nd.The mean entropy variation with tempe rature(TEC) was also studied.Due to their significant magnetocaloric performance,HoRCoMnO_(6)(noted as HRCMO) compounds(with R=Ho,Gd,Eu or Nd) could be good candidates for low-temperature magnetic cooling applications.
基金funded by the Deanship of Scientific Research and Libraries,Princess Nourah bint Abdulrahman University,through the Program of Research Project Funding after Publication,grant No.(RPFAP-88-1445).
文摘Cooling system design applicable to more than one photovoltaic(PV)unit may be challenging due to the arrangement and geometry of the modules.Different cooling techniques are provided in this study to regulate the temperature of conductive panels that are arranged perpendicular to each other.The model uses two vented cavity systems and one L-shaped channel with ternary nanofluid enhanced non-uniform magnetic field.Their cooling performances and comparative results between different systems are provided.The finite element method is used to conduct a numerical analysis for a range of values of the following:the strength of themagnetic field(Hartmann number(Ha)between 0 and 50),the inclination of the magnetic field(γbetween 0 and 90),and the loading of nanoparticles in the base fluid(ϕbetween 0 and 0.03),taking into account both uniformand non-uniformmagnetic fields.For the L-shaped channel and vented cavities,vortex size is controlled by imposing magnetic field and adjusting its strength.Whether uniform or non-uniform magnetic field is applied affects the cooling performances for different cooling configurations.Temperature drops of the horizontal panel with different magnetic field strengths by using channel cooling,vented cavity-1 and vented cavity-2 systems for uniformmagnetic are 11℃,21.5℃,and 3℃when the reference case of Ha=0 is considered for the same cooling systems.However,they become 9.5℃,13.5℃,and 12.5℃when nonuniform magnetic field is used.In the presence of uniform magnetic field effects and changing its magnitude,the use of cooling channel in vented cavity-1 and vented cavity-2 systems results in temperature drops of 4℃,10.8℃,and 3.8℃for vertical panels.On the other hand,when non-uniform magnetic field effects are present,they become 0.5℃,2.1℃,and 9℃.For L-channel cooling,the average Nu for the horizontal panel is more affected byγ,andNu rises asγrises.With increasing nanoparticle loading of ternary nanofluid,the average panel surface temperature shows a linear drop.For the horizontal panel,the temperature declines for nanofluid at the highest loading are 4℃,10℃,and 12℃as compared to using only base fluid.The values of 5℃,7℃,and 11℃are obtained for the vertical panel.Different cooling systems’performance is estimated using artificial neural networks.The method captures the combined impact of applying non-uniformmagnetic field and nanofluid together on the cooling performancewhile accounting for varied cooling strategies for both panels.
基金supported in part by the National Natural Science Foundation of China under Grant 62425110 and Grant U22A2002in part by the National Key Research and Development Program of China under Grant 2020YFA0711301+2 种基金in part by the Leading Project of Minzu University of China under Grant 2023QNYL23in part by the Key Research and Development Project of Nantong(Special Project for Prospective Technology Innovation)under Grant GZ2024002in part by the Suzhou Science and Technology Project,and in part by the FAW Jiefang Automotive Co.,Ltd.
文摘Satellite and terrestrial cellular networks can be integrated together to achieve extended broad-band coverage for,e.g.,maritime communication sce-narios,in the upcoming sixth-generation(6G)era.To counter spectrum scarcity,collaborative spectrum sharing is considered for hybrid satellite-terrestrial networks(HSTNs)in this paper.With only slowly-varying large-scale channel state information(CSI),joint power and channel allocation is implemented for terrestrial mobile terminals(MTs)which share the same frequency band with the satellite MTs oppor-tunistically.Specially,strict quality service assurance is adopted for terrestrial MTs under the constraint of leakage interference to satellite MTs.With the tar-get of maximizing both the number of served terres-trial MTs and the average sum transmission rate,a double-target spectrum sharing problem is formulated.To solve the complicated mixed integer programming(MIP)problem efficiently,user-centric channel pools are introduced.Simulations demonstrate that the proposed spectrum sharing scheme could achieve a significant performance gain for the HSTN.
基金financial support of the National Natural Science Foundation of China (22379063)
文摘Layered double hydroxides(LDHs)are potential cathode materials for aqueous magnesium-ion batteries(AMIBs).However,the low capacity and sluggish kinetics significantly limit their electrochemical performance in AMIBs.Herein,we find that oxygen vacancies can significantly boost the capacity,electrochemical kinetics,and structure stability of LDHs.The corresponding structure-performance relationship and energy storage mechanism are elaborated through exhaustive in/ex-situ experimental characterizations and density functional theory(DFT)calculations.Specially,in-situ Raman and DFT calculations reveal that oxygen vacancies elevate orbital energy of O 2p and electron density of O atoms,thereby enhancing the orbital hybridization of O 2p with Ni/Co 3d.This facilitates electron transfer between O and adjacent Ni/Co atoms and improves the covalency of Ni–O and Co–O bonds,which activates Ni/Co atoms to release more capacity and stabilizes the Ov-NiCo-LDH structure.Moreover,the distribution of relaxation times(DRT)and molecular dynamics(MD)simulations disclose that the enhanced d-p orbital hybridization optimizes the electronic structure of Ov-NiCo-LDH,which distinctly reduces the diffusion energy barriers of Mg^(2+)and improves the charge transfer kinetics of Ov-NiCo-LDH.Consequently,the assembled Ov-NiCo-LDH//active carbon(AC)and Ov-NiCo-LDH//perylenediimide(PTCDI)AMIBs can both deliver high specific discharge capacity(182.7 and 59.4 mAh g^(−1)at 0.5 A g^(−1),respectively)and long-term cycling stability(85.4%and 89.0%of capacity retentions after 2500 and 2400 cycles at 1.0 A g^(−1),respectively).In addition,the practical prospects for Ov-NiCo-LDH-based AMIBs have been demonstrated in different application scenarios.This work not only provides an effective strategy for obtaining high-performance cathodes of AMIBs,but also fundamentally elucidates the inherent mechanisms.
基金Project ZR2023MF111 supported by Shandong Provincial Natural Science Foundation。
文摘With the advancement of Vehicle-to-Everything(V2X)technology,efficient resource allocation in dynamic vehicular networks has become a critical challenge for achieving optimal performance.Existing methods suffer from high computational complexity and decision latency under high-density traffic and heterogeneous network conditions.To address these challenges,this study presents an innovative framework that combines Graph Neural Networks(GNNs)with a Double Deep Q-Network(DDQN),utilizing dynamic graph structures and reinforcement learning.An adaptive neighbor sampling mechanism is introduced to dynamically select the most relevant neighbors based on interference levels and network topology,thereby improving decision accuracy and efficiency.Meanwhile,the framework models communication links as nodes and interference relationships as edges,effectively capturing the direct impact of interference on resource allocation while reducing computational complexity and preserving critical interaction information.Employing an aggregation mechanism based on the Graph Attention Network(GAT),it dynamically adjusts the neighbor sampling scope and performs attention-weighted aggregation based on node importance,ensuring more efficient and adaptive resource management.This design ensures reliable Vehicle-to-Vehicle(V2V)communication while maintaining high Vehicle-to-Infrastructure(V2I)throughput.The framework retains the global feature learning capabilities of GNNs and supports distributed network deployment,allowing vehicles to extract low-dimensional graph embeddings from local observations for real-time resource decisions.Experimental results demonstrate that the proposed method significantly reduces computational overhead,mitigates latency,and improves resource utilization efficiency in vehicular networks under complex traffic scenarios.This research not only provides a novel solution to resource allocation challenges in V2X networks but also advances the application of DDQN in intelligent transportation systems,offering substantial theoretical significance and practical value.
基金supported by the Natural Science Research Project of Colleges and Universities in Anhui Province (No.KJ2021A0479)the Science Research Program of Anhui University of Finance and Economics (No.ACKYC22082)。
文摘We present a gain adaptive tuning method for fiber Raman amplifier(FRA) using two-stage neural networks(NNs) and double weights updates. After training the connection weights of two-stage NNs separately in training phase, the connection weights of the unified NN are updated again in verification phase according to error between the predicted and target gains to eliminate the inherent error of the NNs. The simulation results show that the mean of root mean square error(RMSE) and maximum error of gains are 0.131 d B and 0.281 d B, respectively. It shows that the method can realize adaptive adjustment function of FRA gain with high accuracy.
基金the Science Technology and Innovation Team in University of Henan Province(No.24IRTSTHN002)the National Natural Science Foundation of China(No.22279121)China Postdoctoral Science Foundation(No.2022M712863),and DFT calculations were supported by the National Supercomputing Centre in Zhengzhou and the funding of Zhengzhou University.
文摘Zn metal anode suffers from dendrite issues and passive byproducts,which severely plagues the practical application of aqueous Zn metal batteries.Herein,a polyzwitterionic cross-linked double network hydrogel electrolyte composed of physical crosslinking(hyaluronic acid)and chemical crosslinking(synthetic zwitterionic monomer copolymerized with acrylamide)is introduced to overcome these obstacles.On the one hand,highly hydrophilic physical network provides an energy dissipation channel to buffer stress and builds a H_(2)O-poor interface to avoid side reactions.On the other hand,the charged groups(sulfonic and imidazolyl)in chemical crosslinking structure build anion/cation transport channels to boost ions’kinetics migration and regulate the typical solvent structure[Zn(H_(2)O)_(6)]^(2+)to R-SO_(3)^(−)[Zn(H_(2)O)_(4)]^(2+),with uniform electric field distribution and significant resistance to dendrites and parasitic reactions.Based on the above functions,the symmetric zinc cell exhibits superior cycle stability for more than 420 h at a high current density of 5 mA·cm^(−2),and Zn||MnO_(2)full cell has a reversible specific capacity of 150 mAh·g^(−1)after 1000 cycles at 2 C with this hydrogel electrolyte.Furthermore,the pouch cell delivers impressive flexibility and cyclability for energy-storage applications.
基金Institutional Fund Projects under No.(IFP-A-2022-2-5-24)by Ministry of Education and University of Hafr Al Batin,Saudi Arabia.
文摘The application of mathematical modeling to biological fluids is of utmost importance, as it has diverse applicationsin medicine. The peristaltic mechanism plays a crucial role in understanding numerous biological flows. In thispaper, we present a theoretical investigation of the double diffusion convection in the peristaltic transport of aPrandtl nanofluid through an asymmetric tapered channel under the combined action of thermal radiation andan induced magnetic field. The equations for the current flow scenario are developed, incorporating relevantassumptions, and considering the effect of viscous dissipation. The impact of thermal radiation and doublediffusion on public health is of particular interest. For instance, infrared radiation techniques have been used totreat various skin-related diseases and can also be employed as a measure of thermotherapy for some bones toenhance blood circulation, with radiation increasing blood flow by approximately 80%. To solve the governingequations, we employ a numerical method with the aid of symbolic software such as Mathematica and MATLAB.The velocity, magnetic force function, pressure rise, temperature, solute (species) concentration, and nanoparticlevolume fraction profiles are analytically derived and graphically displayed. The results outcomes are compared withthe findings of limiting situations for verification.
基金funded by National Natural Science Foundation of China(No.62063006)Guangxi Science and Technology Major Program(No.2022AA05002)+1 种基金Key Laboratory of AI and Information Processing(Hechi University),Education Department of Guangxi Zhuang Autonomous Region(No.2022GXZDSY003)Central Leading Local Science and Technology Development Fund Project of Wuzhou(No.202201001).
文摘By integrating deep neural networks with reinforcement learning,the Double Deep Q Network(DDQN)algorithm overcomes the limitations of Q-learning in handling continuous spaces and is widely applied in the path planning of mobile robots.However,the traditional DDQN algorithm suffers from sparse rewards and inefficient utilization of high-quality data.Targeting those problems,an improved DDQN algorithm based on average Q-value estimation and reward redistribution was proposed.First,to enhance the precision of the target Q-value,the average of multiple previously learned Q-values from the target Q network is used to replace the single Q-value from the current target Q network.Next,a reward redistribution mechanism is designed to overcome the sparse reward problem by adjusting the final reward of each action using the round reward from trajectory information.Additionally,a reward-prioritized experience selection method is introduced,which ranks experience samples according to reward values to ensure frequent utilization of high-quality data.Finally,simulation experiments are conducted to verify the effectiveness of the proposed algorithm in fixed-position scenario and random environments.The experimental results show that compared to the traditional DDQN algorithm,the proposed algorithm achieves shorter average running time,higher average return and fewer average steps.The performance of the proposed algorithm is improved by 11.43%in the fixed scenario and 8.33%in random environments.It not only plans economic and safe paths but also significantly improves efficiency and generalization in path planning,making it suitable for widespread application in autonomous navigation and industrial automation.
基金supported in part by the Pioneer and Leading Goose R&D Program of Zhejiang Province under Grant 2022C01083 (Dr.Yu Li,https://zjnsf.kjt.zj.gov.cn/)Pioneer and Leading Goose R&D Program of Zhejiang Province under Grant 2023C01217 (Dr.Yu Li,https://zjnsf.kjt.zj.gov.cn/).
文摘With the rapid development ofmobile Internet,spatial crowdsourcing has becomemore andmore popular.Spatial crowdsourcing consists of many different types of applications,such as spatial crowd-sensing services.In terms of spatial crowd-sensing,it collects and analyzes traffic sensing data from clients like vehicles and traffic lights to construct intelligent traffic prediction models.Besides collecting sensing data,spatial crowdsourcing also includes spatial delivery services like DiDi and Uber.Appropriate task assignment and worker selection dominate the service quality for spatial crowdsourcing applications.Previous research conducted task assignments via traditional matching approaches or using simple network models.However,advanced mining methods are lacking to explore the relationship between workers,task publishers,and the spatio-temporal attributes in tasks.Therefore,in this paper,we propose a Deep Double Dueling Spatial-temporal Q Network(D3SQN)to adaptively learn the spatialtemporal relationship between task,task publishers,and workers in a dynamic environment to achieve optimal allocation.Specifically,D3SQNis revised through reinforcement learning by adding a spatial-temporal transformer that can estimate the expected state values and action advantages so as to improve the accuracy of task assignments.Extensive experiments are conducted over real data collected fromDiDi and ELM,and the simulation results verify the effectiveness of our proposed models.
