Chemical Scissors Tailored Nano‑Tellurium with High‑Entropy Morphology for Efficient Foam‑Hydrogel‑Based Solar Photothermal Evaporators

The development of tellurium(Te)-based semiconductor nanomaterials for efficient light-to-heat conversion may offer an effective means of harvesting sunlight to address global energy concerns.However,the nanosized Te(nano-Te)materials reported to date suffer from a series of drawbacks,including limited light absorption and a lack of surface structures.Herein,we report the preparation of nano-Te by electrochemical exfoliation using an electrolyzable room-temperature ionic liquid.Anions,cations,and their corresponding electrolytic products acting as chemical scissors can precisely intercalate and functionalize bulk Te.The resulting nano-Te has high morphological entropy,rich surface functional groups,and broad light absorption.We also constructed foam hydrogels based on poly(vinyl alcohol)/nano-Te,which achieved an evaporation rate and energy efficiency of 4.11 kg m^(−2)h^(−1)and 128%,respectively,under 1 sun irradiation.Furthermore,the evaporation rate was maintained in the range 2.5-3.0 kg m^(−2)h^(−1)outdoors under 0.5-1.0 sun,providing highly efficient evaporation under low light conditions.

Spin-orbit torque effect in silicon-based sputtered Mn_(3)Sn film

Noncollinear antiferromagnet Mn_(3)Sn has shown remarkable efficiency in charge-spin conversion,a novel magnetic spin Hall effect,and a stable topological antiferromagnetic state,which has resulted in great interest from researchers in the field of spin-orbit torque.Current research has primarily focused on the spin-orbit torque effect of epitaxially grown noncollinear antiferromagnet Mn_(3)Sn films.However,this method is not suitable for large-scale industrial preparation.In this study,amorphous Mn_(3)Sn films and Mn_(3)Sn/Py heterostructures were prepared using magnetron sputtering on silicon substrates.The spin-torque ferromagnetic resonance measurement demonstrated that only the conventional spin-orbit torque effect generated by in-plane polarized spin currents existed in the Mn_(3)Sn/Py heterostructure,with a spin-orbit torque efficiency of 0.016.Additionally,we prepared the perpendicular magnetized Mn_(3)Sn/CoTb heterostructure based on amorphous Mn_(3)Sn film,where the spin-orbit torque driven perpendicular magnetization switching was achieved with a lower critical switching current density(3.9×10^(7)A/cm^(2))compared to Ta/CoTb heterostructure.This research reveals the spin-orbit torque effect of amorphous Mn_(3)Sn films and establishes a foundation for further advancement in the practical application of Mn_(3)Sn materials in spintronic devices.

Large Room-Temperature Magnetoresistance in van der Waals Ferromagnet/Semiconductor Junctions

A magnetic tunnel junction(MTJ)is the core component in memory technologies,such as the magnetic random-access memory,magnetic sensors and programmable logic devices.In particular,MTJs based on twodimensional van der Waals(vd W)heterostructures offer unprecedented opportunities for low power consumption and miniaturization of spintronic devices.However,their operation at room temperature remains a challenge.Here,we report a large tunnel magnetoresistance(TMR)of up to 85%at room temperature(T=300 K)in vdW MTJs based on a thin(<10 nm)semiconductor spacer WSe_(2)layer embedded between two Fe_(3)GaTe_(2e)lectrodes with intrinsic above-room-temperature ferromagnetism.The TMR in the MTJ increases with decreasing temperature up to 164%at T=10 K.The demonstration of TMR in ultra-thin MTJs at room temperature opens a realistic and promising route for next-generation spintronic applications beyond the current state of the art.

Analysis of vibration attenuation characteristics of large thickness carbon fiber composite laminates

The vibration attenuation and damping characteristics of carbon fiber reinforced composite laminates with different thicknesses were investigated by hammering experiments under free boundary constraints in different directions.The dynamic signal testing and analysis system is applied to collect and analyze the vibration signals of the composite specimens,and combine the self-spectrum analysis and logarithmic decay method to identify the fundamental frequencies of different specimens and calculate the damping ratios of different directions of the specimens.The results showed that the overall stiffness of the specimen increased with the increase of the specimen thickness,and when the thickness of the sample increases from 24mm to 32mm,the fundamental frequency increases by 35.1%,the vibration showed the same vibration attenuation and energy dissipation characteristics in the 0°and 90°directions of the specimen,compared with the specimen in the 45°direction,which was less likely to be excited and had poorer vibration attenuation ability,while the upper and lower surfaces of the same specimen showed slightly different attenuation characteristics to the vibration,the maximum difference of damping capacity between top and bottom surfaces of CFRP plates is about 70%.

Effect of expansion waves on cowl shock wave and boundary layer interaction in hypersonic inlet

The interaction of cowl shock wave and boundary layer has a crucial effect on the stability,operability and performance of hypersonic inlets.Many studies on inhibiting the sep-aration and managing the strength of the interaction of the shock wave and boundary layer with expansion corner have been conducted.However,the expansion waves near the circular arc shoulder to effectively control the interaction and cowl shock arrangement is little investigated.Therefore,the interaction of the cowl shock wave and boundary layer under thefluence of the expansion waves is studied by inviscid and viscous numerical simulations.The results reveal that the expansion waves have an important impact on the interaction between the cowl shock wave and boundary layer and the strength of shock wave,and that there are four types of inter-action processes with the change of the relative impingement positions of cowl shock wave.The expansion waves have a different influence on the shock wave and boundary layer inter-action at different incident points.When the incident point of the cowl shock wave goes far downstream from the end of the circular arc shoulder,the influence of expansion waves is weakened,and the magnitude of separation zone increases.However,when the expansion waves are applied to the interaction of the cowl shock wave and boundary layer on the circular arc shoulder,the separation can be effectively controlled.In particular,while the expansion waves interact with the shock wave and boundary layer in the back half of the circular arc shoulder,the separation is best inhibited.Compared with the upstream and downstream inci-dent points,the scale of separation area in the optimal control region is reduced by 65.3%at most.Furthermore,the total pressure recovery coefficientfirst increases and then decreases when the cowl moves from upstream to downstream,and the total pressure recovery coefficient reaches the maximum value of 68.36%at the incident position of cowl shock wave d Z 8.09d0.ª2024 The Authors.Publishing services by Elsevier B.V.on behalf of KeAi Communications Co.Ltd.

A deep learning-based approach for flow field prediction in a dual-mode combustor

Accurate acquisition of the distribution offlow parameters inside the supersonic combustor is of great significance for hypersonicflight control.It is an interesting attempt to introduce a data-driven model to a supersonic combustor forflowfield prediction.This paper proposes a novel method for predicting theflowfield in a dual-mode combustor.Aflowfield prediction convolutional neural network with multiple branches is built.Numerical investiga-tions for a strut variable geometry combustor have been conducted to obtainflowfield data for training the network as aflowfield prediction model.Richflowfield data are obtained by changing the equivalent ratio,incomingflow condition and geometry of the supersonic combustor.The Mach number distribution can be obtained from the trainedflowfield predic-tion model using the combustor wall pressure as input with high accuracy.The accuracy offlowfield prediction is discussed in several aspects.Further,the combustion mode detection is im-plemented on the predictionflowfield.ª2024 The Authors.Publishing services by Elsevier B.V.on behalf of KeAi Communications Co.Ltd.

A deep learning approach for velocity field prediction in a scramjet isolator from Schlieren images

Accurate measurements of physical parameters in a scramjet isolator are very important to promote the design and optimization of the isolator and even the scramjet.In a ground experiment,limited by the inherent characteristics of measurement technology and equipment,it is a big challenge to obtain the velocity field inside an isolator.In this study,a deep learning approach was introduced to combine data obtained from ground experiments and numerical simulations,and a velocity field prediction model was developed for obtaining the velocity field inside an isolator based on experimental Schlieren images.The velocity field prediction model was designed with convolutional neural networks as the main structure.Ground experiments of a scramjet isolator under continuous Mach number variation were carried out,and Schlieren images of the flow field inside the isolator were collected.Numerical simulations of the isolator were also carried out,and the velocity fields inside the isolator under various Mach numbers were obtained.The velocity field prediction model was trained using flow field datasets containing experimental Schlieren images and velocity field,and the mapping relationship between the experimental Schlieren images and the predicted velocity field was successfully established.