Topology optimization of chiral metamaterials with application to underwater sound insulation

Chiral metamaterials have been proven to possess many appealing mechanical phenomena,such as negative Poisson's ratio,high-impact resistance,and energy absorption.This work extends the applications of chiral metamaterials to underwater sound insulation.Various chiral metamaterials with low acoustic impedance and proper stiffness are inversely designed using the topology optimization scheme.Low acoustic impedance enables the metamaterials to have a high and broadband sound transmission loss(STL),while proper stiffness guarantees its robust acoustic performance under a hydrostatic pressure.As proof-of-concept demonstrations,two specimens are fabricated and tested in a water-filled impedance tube.Experimental results show that,on average,over 95%incident sound energy can be isolated by the specimens in a broad frequency range from 1 k Hz to 5 k Hz,while the sound insulation performance keeps stable under a certain hydrostatic pressure.This work may provide new insights for chiral metamaterials into the underwater applications with sound insulation.

Integrated high-performance and accurate shaping technology of low-cost powder metallurgy titanium alloys: A comprehensive review

The practical engineering applications of powder metallurgy (PM) Ti alloys produced through cold compaction and pressure-less sintering are impeded by poor sintering densification, embrittlement caused by excessive O impurities, and severe sintering deforma-tion resulting from the use of heterogeneous powder mixtures. This review presents a summary of our previous work on addressing the above challenges. Initially, we proposed a novel strategy using reaction-induced liquid phases to enhance sintering densification. Near- complete density (relative density exceeding 99%) was achieved by applying the above strategy and newly developed sintering aids. By focusing on the O-induced embrittlement issue, we determined the onset dissolution temperature of oxide films in the Ti matrix. On the basis of this finding, we established a design criterion for effective O scavengers that require reaction with oxide films before their dissol-ution. Consequently, a ductile PM Ti alloy was successfully obtained by introducing 0.3wt% NdB6 as the O scavenger. Lastly, a powder- coating strategy was adopted to address the sintering deformation issue. The ultrafine size and shell-like distribution characteristics of coating particles ensured rapid dissolution and homogeneity in the Ti matrix, thereby facilitating linear shrinkage during sintering. As a result, geometrically complex Ti alloy parts with high dimensional accuracy were fabricated by using the coated powder. Our fundament-al findings and related technical achievements enabled the development of an integrated production technology for the high-performance and accurate shaping of low-cost PM Ti alloys. Additionally, the primary engineering applications and progress in the industrialization practice of our developed technology are introduced in this review.

Sustainable production of high-energy-density jet fuel via cycloaddition reactions

Developing an energy supply-chain based on renewable biomass holds great potential to build a low carbon society.High-energy-density(HED)jet fuel,featuring unique fused/strained cycloalkanes,is of great significance for volume-limited military aircrafts,as their high density and combustion heat can extend flight duration and increase the payload.Therefore,the exploration of biomass-based routes towards HED fuel has drawn much attention over the past decade.Cycloaddition reaction features rapid construction of various carbocycles in an atom-and step-economical fashion.This elegant strategy has been widely applied in the manufacture of sustainable HED fuel.Here we carefully summarize the progress achieved in this fascinating area and the review is categorized by the cycloaddition patterns including[4+2],[2+2],[4+4],and[2+1]cycloadditions.Besides,the energy densities of the as-prepared biofuels and petroleumbased fuels(conventional Jet-A and advanced JP-10)are also compared.This review will provide important insights into rational design of new HED fuel with different ring-types/sizes and inspire the chemists to turn those literature studies into practical applications in military field.

Energy-Efficient Traffic Offloading for RSMA-Based Hybrid Satellite Terrestrial Networks with Deep Reinforcement Learning

As the demands of massive connections and vast coverage rapidly grow in the next wireless communication networks, rate splitting multiple access(RSMA) is considered to be the new promising access scheme since it can provide higher efficiency with limited spectrum resources. In this paper, combining spectrum splitting with rate splitting, we propose to allocate resources with traffic offloading in hybrid satellite terrestrial networks. A novel deep reinforcement learning method is adopted to solve this challenging non-convex problem. However, the neverending learning process could prohibit its practical implementation. Therefore, we introduce the switch mechanism to avoid unnecessary learning. Additionally, the QoS constraint in the scheme can rule out unsuccessful transmission. The simulation results validates the energy efficiency performance and the convergence speed of the proposed algorithm.

On the generation of high-quality Nyquist pulses in mode-locked fiber lasers

Nyquist pulses have wide applications in many areas,from electronics to optics.Mode-locked lasers are ideal platforms to generate such pulses.However,how to generate high-quality Nyquist pulses in mode-locked lasers remains elusive.We address this problem by managing different physical effects in mode-locked fiber lasers through extensive numerical simulations.We find that net dispersion,linear loss,gain and filter shaping can affect the quality of Nyquist pulses significantly.We also demonstrate that Nyquist pulses experience similariton shaping due to the nonlinear attractor effect in the gain medium.Our work may contribute to the design of Nyquist pulse sources and enrich the understanding of pulse shaping dynamics in mode-locked lasers.

Impact of cooling rate on exfoliation corrosion resistance of a Li-containing 7xxx aluminum alloy

The impact of cooling rate after solution heat treatment on exfoliation corrosion resistance of a Li-containing 7xxx aluminum alloy was investigated by accelerated immersion and electrochemical impedance spectroscopy test,optical microscope,electron backscatter diffraction and scanning transmission electron microscope.With the decrease of cooling rate from 1700℃/s to 4℃/s,exfoliation corrosion resistance of the aged specimens decreases with rating changing from EA to EC and the maximum corrosion depth increasing from about 169.4μm to 632.1μm.Exfoliation corrosion tends to develop along grain boundaries in the specimens with cooling rates higher than about 31℃/s and along both grain boundaries and sub-grain boundaries in the specimens with lower cooling rates.The reason has been discussed based on the changes of the microstructure and microchemistry at grain boundaries and sub-grain boundaries due to slow cooling.

Autonomous Recommendation of Fault Detection Algorithms for Spacecraft

Dear Editor, This letter deals with the problem of algorithm recommendation for online fault detection of spacecraft. By transforming the time series data into distributions and introducing a distribution-aware measure, a principal method is designed for quantifying the detectabilities of fault detection algorithms over special datasets.

Automatic Generation of Artificial Space Weather Forecast Product Based on Sequence-to-sequence Model

Both analyzing a large amount of space weather observed data and alleviating personal experience bias are significant challenges in generating artificial space weather forecast products.With the use of natural language generation methods based on the sequence-to-sequence model,space weather forecast texts can be automatically generated.To conduct our generation tasks at a fine-grained level,a taxonomy of space weather phenomena based on descriptions is presented.Then,our MDH(Multi-Domain Hybrid)model is proposed for generating space weather summaries in two stages.This model is composed of three sequence-to-sequence-based deep neural network sub-models(one Bidirectional Auto-Regressive Transformers pre-trained model and two Transformer models).Then,to evaluate how well MDH performs,quality evaluation metrics based on two prevalent automatic metrics and our innovative human metric are presented.The comprehensive scores of the three summaries generating tasks on testing datasets are 70.87,93.50,and 92.69,respectively.The results suggest that MDH can generate space weather summaries with high accuracy and coherence,as well as suitable length,which can assist forecasters in generating high-quality space weather forecast products,despite the data being starved.

A novel“Snowflake”--rGO-CuO for ultrasonic degradation of rhodamine and methyl orange

Graphene-doped CuO(rGO-CuO)nanocomposites with flower shapes were prepared by an improved solvothermal method.The samples were characterized by X-ray diffraction,X-ray photoelectron spectroscopy and UV–visible spectroscopy.The active species in the degradation reaction of rGO-CuO composites under ultrasonic irradiation were detected by electron paramagnetic resonance.On the basis of comparative experiments,the photodegradation mechanisms of two typical dyes,Rhodamine B(Rh B)and methyl orange(MO),were proposed.The results demonstrated that the doped CuO could improve the degradation efficiency.The catalytic degradation efficiency of rGO-CuO(2:1)to rhodamine B(RhB)and methyl orange(MO)reached 90%and 87%respectively,which were 2.1 times and 4.4 times of the reduced graphene oxide.Through the first-principles and other theories,we give the reasons for the enhanced catalytic performance of rGO-CuO:combined with internal and external factors,rGO-CuO under ultrasound could produce more hole and active sites that could interact with the OH·in pollutant molecules to achieve degradation.The rGO-CuO nanocomposite has a simple preparation process and low price,and has a high efficiency of degrading water pollution products and no secondary pollution products.It has a low-cost and high-efficiency application prospect in water pollution industrial production and life.

Regeneration of copper catalysts mediated by molybdenum-based oxides

Cu catalysts,known for their unparalleled catalytic capabilities due to their unique electronic structure,have faced inherent challenges in maintaining long-term effectiveness under harsh hydrogenation conditions.Here,we demonstrate a molybdenum-mediated redispersion behavior of Cu under hightemperature oxidation conditions.The oxidized Cu nanoparticles with rich metal-support interfaces tend to dissolve into the MoO_(3)support upon heating to 600℃,which facilitates the subsequent regeneration in a reducing atmosphere.A similar redispersion phenomenon is observed for Cu nanoparticles supported on Zn O-modified MoO_(3).The modification of ZnO significantly improves the performance of the Cu catalyst for CO_(2)hydrogenation to methanol,with the high activity being well maintained after four repeated oxidation-reduction cycles.In situ spectroscopic and theoretical analyses suggest that the interaction involved in the formation of the copper molybdate-like compound is the driving force for the redispersion of Cu.This method is applicable to various Mo-based oxide supports,offering a practical strategy for the regeneration of sintered Cu particles in hydrogenation applications.

Stabilizing High-Nickel Cathodes via Interfacial Hydrogen Bonding Effects Using a Hydrofluoric Acid-Scavenging Separator

Nickel-rich layered Li transition metal oxides are the most promising cathode materials for high-energydensity Li-ion batteries.However,they exhibit rapid capacity degradation induced by transition metal dissolution and structural reconstruction,which are associated with hydrofluoric acid(HF)generation from lithium hexafluorophosphate decomposition.The potential for thermal runaway during the working process poses another challenge.Separators are promising components to alleviate the aforementioned obstacles.Herein,an ultrathin double-layered separator with a 10 lm polyimide(PI)basement and a 2 lm polyvinylidene difluoride(PVDF)coating layer is designed and fabricated by combining a nonsolvent induced phase inversion process and coating method.The PI skeleton provides good stability against potential thermal shrinkage,and the strong PI-PVDF bonding endows the composite separator with robust structural integrity;these characteristics jointly contribute to the extraordinary mechanical tolerance of the separator at elevated temperatures.Additionally,unique HF-scavenging effects are achieved with the formation of-CO…H-F hydrogen bonds for the abundant HF coordination sites provided by the imide ring;hence,the layered Ni-rich cathodes are protected from HF attack,which ultimately reduces transition metal dissolution and facilitates long-term cyclability of the Ni-rich cathodes.Li||NCM811 batteries(where“NCM”indicates LiNi_(x)Co_(y)Mn_(1-x-y)O_(2))with the proposed composite separator exhibit a 90.6%capacity retention after 400 cycles at room temperature and remain sustainable at 60℃with a 91.4%capacity retention after 200 cycles.By adopting a new perspective on separators,this study presents a feasible and promising strategy for suppressing capacity degradation and enabling the safe operation of Ni-rich cathode materials.

Effect of desorbed gas on microwave breakdown on vacuum side of dielectric window

The gas desorbed from the dielectric surface has a great influence on the characteristics of microwave breakdown on the vacuum side of the dielectric window. In this paper, the dielectric surface breakdown is described by using the electromagnetic particle-in-cell-Monte Carlo collision(PIC-MCC) model. The process of desorption of gas and its influence on the breakdown characteristics are studied. The simulation results show that, due to the accumulation of desorbed gas, the pressure near the dielectric surface increases in time, and the breakdown mechanism transitions from secondary electron multipactor to collision ionization. More and more electrons generated by collision ionization drift to the dielectric surface, so that the amplitude of self-organized normal electric field increases in time and sometimes points to the dielectric surface. Nevertheless, the number of secondary electrons emitted in each microwave cycle is approximately equal to the number of primary electrons. In the early and middle stages of breakdown, the attenuation of the microwave electric field near the dielectric surface is very small. However, the collision ionization causes a sharp increase in the number density of electrons,and the microwave electric field decays rapidly in the later stage of breakdown. Compared with the electromagnetic PIC-MCC simulation results, the mean energy and number of electrons obtained by the electrostatic PIC-MCC model are overestimated in the later stage of breakdown because it does not take into account the attenuation of microwave electric field. The pressure of the desorbed gas predicted by the electromagnetic PIC-MCC model is close to the measured value,when the number of gas atoms desorbed by an incident electron is taken as 0.4.

Physical mechanism of secondary-electron emission in Si wafers

CMOS-compatible RF/microwave devices,such as filters and amplifiers,have been widely used in wireless communication systems.However,secondary-electron emission phenomena often occur in RF/microwave devices based on silicon(Si)wafers,especially in the high-frequency range.In this paper,we have studied the major factors that influence the secondary-electron yield(SEY)in commercial Si wafers with different doping concentrations.We show that the SEY is suppressed as the doping concentration increases,corresponding to a relatively short effective escape depthλ.Meanwhile,the reduced narrow band gap is beneficial in suppressing the SEY,in which the absence of a shallow energy band below the conduction band will easily capture electrons,as revealed by first-principles calculations.Thus,the new physical mechanism combined with the effective escape depth and band gap can provide useful guidance for the design of integrated RF/microwave devices based on Si wafers.

Tuning microstructures of TC4 ELI to improve explosion resistance

A reasonable heat treatment process for TC4 ELI titanium alloy is crucial to tune microstructures to improve its explosion resistance.However,there is limited investigation on tuning microstructures of TC4 ELI to improve explosion resistance.Moreover,the current challenge is quantifying microstructural changes'effects on explosion resistance and incorporating microstructural changes into finite element models.This work aims to tune microstructures to improve explosion resistance and elucidate their anti-explosion mechanism,and find a suitable method to incorporate microstructural changes into finite element models.In this work,we systematically study the deformation and failure characteristics of TC4 ELI plates with varying microstructures using an air explosion test and LS-DYNA finite element modeling.The Johnson-Cook(JC)constitutive parameters are used to quantify the effects of microstructural changes on explosion resistance and incorporate microstructural changes into finite element models.Because of the heat treatment,one plate has equiaxed microstructure and the other has bimodal microstructure.The convex of the plate after the explosion has a quadratic relationship with the charge mass,and the simulation results demonstrate high reliability,with the error less than 17.5%.Therefore,it is feasible to obtain corresponding JC constitutive parameters based on the differences in microstructures and mechanical properties and characterize the effects of microstructural changes on explosion resistance.The bimodal target exhibits excellent deformation resistance.The response of bimodal microstructure to the shock wave may be more intense under explosive loading.The well-coordinated structure of the bimodal target enhances its resistance to deformation.

A Single-Layer Piezoelectric Composite Separator for Durable Operation of Li Metal Anode at High Rates

Piezoelectric ceramic and polymeric separators have been proposed to effectively regulate Li deposition and suppress dendrite growth,but such separators still fail to satisfactorily support durable operation of lithium metal batteries owing to the fragile ceramic layer or low-piezoelectricity polymer as employed.Herein,by combining PVDF-HFP and ferroelectric BaTiO_(3),we develop a homogeneous,single-layer composite separator with strong piezoelectric effects to inhibit dendrite growth while maintaining high mechanical strength.As squeezed by local protrusion,the polarized PVDF-HFP/BaTiO_(3)composite separator generates a local voltage to suppress the local-intensified electric field and further deconcentrate regional lithium-ion flux to retard lithium deposition on the protrusion,hence enabling a smoother and more compact lithium deposition morphology than the unpoled composite separator and the pure PVDF-HFP separator,especially at high rates.Remarkably,the homogeneous incorporation of BaTiO_(3)highly improves the piezoelectric performances of the separator with residual polarization of 0.086 pC cm^(-2)after polarization treatment,four times that of the pure PVDF-HFP separator,and simultaneously increases the transference number of lithium-ion from 0.45 to 0.57.Beneficial from the prominent piezoelectric mechanism,the polarized PVDF-HFP/BaTiO_(3)composite separator enables stable cyclic performances of Li||LiFePO_(4)cells for 400 cycles at 2 C(1 C=170 mA g^(-1))with a capacity retention above 99%,and for 600 cycles at 5 C with a capacity retention over 85%.

Improving the energy efficiency of surface dielectric barrier discharge devices for plasma nitric oxide conversion utilizing active flow control

Improving energy efficiency in plasma NO removal is a critical issue.When the surface dielectric barrier discharge(SDBD)device is considered as a combination of multiple plasma actuators,the induced plasma aerodynamic effect cannot be ignored,which can affect the mass transfer,then affect the chemical reactions.Five SDBD devices with different electrode arrangements are studied for NO conversion.They correspond to different flow patterns.We find that the energy efficiency in an SDBD device with a common structure(Type 1)is 28%lower than that in SDBD devices with a special arrangement(Types 2–5).Two reasons may explain the results.First,fewer active species are produced in Type 1 because the development of discharge is hindered by the mutually exclusive electric field forces caused by the symmetrically distributed charged particles.Second,the plasma wind induced by the plasma actuator can enhance the mass and heat transfer.The mixing of reactants and products is better in Types 2–5 than Type 1 due to higher turbulence kinetic energy.

Demonstration of multi-pass amplification of 46.9 nm laser pumped by capillary discharge

Using a plane–plane resonator composed of silicon carbide mirrors,we achieve for the first time multi-pass amplification of a 46.9 nm laser pumped by capillary discharge.In terms of the temporal characteristics,for an initial argon pressure of 17 Pa,triple-pass amplification of the laser is obtained at a delay time between the pre-pulse and the main pulse currents of 40s,and quadruple-pass amplification is obtained at a delay time of 50s.The experimental results show that the gain duration of the plasma column is more than 6 ns.In terms of spatial characteristics,the spot of the output laser has a reduced full width at half maximum divergence compared with that from a laser without a resonator.

Deep Learning Accelerates the Discovery of Two- Dimensional Catalysts for Hydrogen Evolution Reaction

Two-dimensional materials with active sites are expected to replace platinum as large-scale hydrogen production catalysts.However,the rapid discovery of excellent two-dimensional hydrogen evolution reaction catalysts is seriously hindered due to the long experiment cycle and the huge cost of high-throughput calculations of adsorption energies.Considering that the traditional regression models cannot consider all the potential sites on the surface of catalysts,we use a deep learning method with crystal graph convolutional neural networks to accelerate the discovery of high-performance two-dimensional hydrogen evolution reaction catalysts from two-dimensional materials database,with the prediction accuracy as high as 95.2%.The proposed method considers all active sites,screens out 38 high performance catalysts from 6,531 two-dimensional materials,predicts their adsorption energies at different active sites,and determines the potential strongest adsorption sites.The prediction accuracy of the two-dimensional hydrogen evolution reaction catalysts screening strategy proposed in this work is at the density-functional-theory level,but the prediction speed is 10.19 years ahead of the high-throughput screening,demonstrating the capability of crystal graph convolutional neural networks-deep learning method for efficiently discovering high-performance new structures over a wide catalytic materials space.

A reconfigurable dynamic Bayesian network for digital twin modeling of structures with multiple damage modes

Dynamic Bayesian networks(DBNs)are commonly employed for structural digital twin modeling.At present,most researches only consider single damage mode tracking.It is not sufficient for a reusable spacecraft as various damage modes may occur during its service life.A reconfigurable DBN method is proposed in this paper.The structure of the DBN can be updated dynamically to describe the interactions between different damages.Two common damages(fatigue and bolt loosening)for a spacecraft structure are considered in a numerical example.The results show that the reconfigurable DBN can accurately predict the acceleration phenomenon of crack growth caused by bolt loosening while the DBN with time-invariant structure cannot,even with enough updates.The definition of interaction coefficients makes the reconfigurable DBN easy to track multiple damages and be extended to more complex problems.The method also has a good physical interpretability as the reconfiguration of DBN corresponds to a specific mechanism.Satisfactory predictions do not require precise knowledge of reconfiguration conditions,making the method more practical.

Effect of magnetic nanoparticles on magnetic field homogeneity

The mechanism of magnetic nanoparticles(MNPs)affecting magnetic field uniformity is studied in this work.The spatial distribution of MNPs in liquid is simulated based on Monte Carlo method.The induced field of the single MNP is combined with the magnetic field distribution of magnetofluid.In the simulation,magnetic field uniformity is described by a statistical distribution.As the chemical shift(CS)and full width at half maximum(FWHM)of magnetic resonance(MR)spectrum can reflect the uniformity of magnetic field,the simulation is verified by spectrum experiment.Simulation and measurement results prove that the CS and FWHM of the MR spectrum are basically positively correlated with the concentration of MNPs and negatively correlated with the temperature.The research results can explain how MNPs play a role in MR by affecting the uniform magnetic field,which is of great significance in improving the temperature measurement accuracy of magnetic nanothermometers and the spatial resolution of magnetic particle imaging.