Proton exchange membrane water electrolyzer(PEMWE)represents a highly promising technology for renewable hydrogen generation,urgently demanding low-cost,efficient,and robust anode oxygen evolution reaction(OER)electro...Proton exchange membrane water electrolyzer(PEMWE)represents a highly promising technology for renewable hydrogen generation,urgently demanding low-cost,efficient,and robust anode oxygen evolution reaction(OER)electrocatalysts in acidic media.Over the past decade(mainly from 2016 onwards),low-Ir/Ru perovskite oxides have emerged as promising candidate materials for acidic OER electrocatalysis owing to their flexible element compositions and crystal structures,which can evidently reduce the noble-metal content and meanwhile significantly promote electrocatalytic performance.In this review,the current research progress in low-Ir/Ru perovskite oxides for acidic OER electrocatalysis is comprehensively summarized.Initially,we present a brief introduction to general issues relevant to acidic OER catalyzed by low-Ir/Ru perovskite oxides,such as the actual active species,OER mechanisms,inverse activity-stability relationship,and performance evaluation metrics.Subsequently,we present a thorough overview of various low-Ir/Ru perovskite oxides for acidic OER electrocatalysis,including single perovskites,double perovskites,triple perovskites,quadruple perovskites,Ruddlesden-Popper perovskites,and other complex perovskite-derived oxides,with emphasis on the intrinsic factors contributing to their exceptional performance and structure-property-performance correlation.Finally,remaining challenges and some promising insights to inspire future studies in this exciting field are provided.展开更多
This paper reports the use of integrated computational alloy design,coupled with a rapid printability screening method,to downselect from a total of 70000 datasets in design space to five candidates in the first step,...This paper reports the use of integrated computational alloy design,coupled with a rapid printability screening method,to downselect from a total of 70000 datasets in design space to five candidates in the first step,and then from five to one in the second step.The new Ni-base superalloy with compositions of Ni-5.03Al-2.69Co-5.63Cr-0.04Hf-1.91Mo-2.36Re-3.32Ta-0.57Ti-8.46W-0.05C-0.019B exhibits an optimal balance of density(8.82 g/cm2),printability(freezing range of 107℃),thermal stability(γ′-volume fraction of 50.7%at 980℃and low M_(d)value)and creep(rupture time of 612 h at 980℃/120 MPa).The micro-hardness varies mildly from 417.2±18.5 to 434.7±14.6 HV,suggesting good phase stability.This is substantiated by microstructure observations,which revealed the absence of a topologically close-packed phase.Machine-learning tools of the artificial neural network(ANN),random forest,and support vector regression,respectively,were used to predict creep rupture time.The ANN algorithm achieves the highest accuracy in predicting creep life.By recognising the“black box”nature of the ANN,interpretability analysis was conducted using the local interpretable model-agnostic method.The analysis supports that the ANN model truly learned meaningful functional relationships,and thus is judged as reliable.Feature correlation evaluation outcome emphasises the importance of incorporating microstructure-related input features.展开更多
The optimization of hole transport layer(HTL)is crucial for achieving high efficiency and stability in inverted perovskite solar cells(PSCs)due to its role in facilitating hole transport and passivating the perovskite...The optimization of hole transport layer(HTL)is crucial for achieving high efficiency and stability in inverted perovskite solar cells(PSCs)due to its role in facilitating hole transport and passivating the perovskite bottom interface.While self-assembled monolayers(SAMs)are commonly used for this purpose,the inherent limitations of a single SAM,such as fixed energy levels and rigid structure,restrict their adaptability for different perovskite components and further efficiency enhancement.Here,we demonstrate a stepwise deposition method for SAM-based HTLs to address this issue.We regulated the energy level gradient by depositing two SAMs with distinct energy levels,while the interactions between the phosphate groups in the SAMs and perovskite effectively reduce defect density at the bottom interface of the perovskite film.The as-fabricated PSCs achieved enhanced efficiency and stability with PCEs of 25.7% and 24.0% for rigid and flexible PSCs,respectively;these devices maintain 90% of their initial PCE after 500 h of maximum power point tracking,and retain 98% of their initial PCE after 4,000 bending cycles,representing one of the most stable flexible PSCs reported to date.展开更多
Fatigue properties of materials by Additive Manufacturing(AM) depend on many factors such as AM processing parameter, microstructure, residual stress, surface roughness, porosities, post-treatments, etc. Their evaluat...Fatigue properties of materials by Additive Manufacturing(AM) depend on many factors such as AM processing parameter, microstructure, residual stress, surface roughness, porosities, post-treatments, etc. Their evaluation inevitably requires these factors combined as many as possible, thus resulting in low efficiency and high cost. In recent years, their assessment by leveraging the power of Machine Learning(ML) has gained increasing attentions. A comprehensive overview on the state-of-the-art progress of applying ML strategies to predict fatigue properties of AM materials, as well as their dependence on AM processing and post-processing parameters such as laser power, scanning speed, layer height, hatch distance, built direction, post-heat temperature,etc., were presented. A few attempts in employing Feedforward Neural Network(FNN), Convolutional Neural Network(CNN), Adaptive Network-Based Fuzzy Inference System(ANFIS), Support Vector Machine(SVM) and Random Forest(RF) to predict fatigue life and RF to predict fatigue crack growth rate are summarized. The ML models for predicting AM materials' fatigue properties are found intrinsically similar to the commonly used ones, but are modified to involve AM features. Finally, an outlook for challenges(i.e., small dataset, multifarious features,overfitting, low interpretability, and unable extension from AM material data to structure life) and potential solutions for the ML prediction of AM materials' fatigue properties is provided.展开更多
Flexoelectricity is a two-way coupling effect between the strain gradient and electric field that exists in all dielectrics,regardless of point group symmetry.However,the high-order derivatives of displacements involv...Flexoelectricity is a two-way coupling effect between the strain gradient and electric field that exists in all dielectrics,regardless of point group symmetry.However,the high-order derivatives of displacements involved in the strain gradient pose challenges in solving electromechanical coupling problems incorporating the flexoelectric effect.In this study,we formulate a phase-field model for ferroelectric materials considering the flexoelectric effect.A four-node quadrilateral element with 20 degrees of freedom is constructed without introducing high-order shape functions.The microstructure evolution of domains is described by an independent order parameter,namely the spontaneous polarization governed by the time-dependent Ginzburg–Landau theory.The model is developed based on a thermodynamic framework,in which a set of microforces is introduced to construct the constitutive relation and evolution equation.For the flexoelectric part of electric enthalpy,the strain gradient is determined by interpolating the mechanical strain at the node via the values of Gaussian integration points in the isoparametric space.The model is shown to be capable of reproducing the classic analytical solution of dielectric materials incorporating the flexoelectric contribution.The model is verified by duplicating some typical phenomena in flexoelectricity in cylindrical tubes and truncated pyramids.A comparison is made between the polarization distribution in dielectrics and ferroelectrics.The model can reproduce the solution to the boundary value problem of the cylindrical flexoelectric tube,and demonstrate domain twisting at domain walls in ferroelectrics considering the flexoelectric effect.展开更多
The CoCrFeMnNi high-entropy alloys(HEAs)with a(face-centered cubic) FCC structure has garnered considerable attention for its exceptional ductility and strain hardening ability.However,its yield strength is insufficie...The CoCrFeMnNi high-entropy alloys(HEAs)with a(face-centered cubic) FCC structure has garnered considerable attention for its exceptional ductility and strain hardening ability.However,its yield strength is insufficient for structural applications.In this study,strengthening mechanisms in these HEAs were investigated to gain insight into the mechanical properties according to alloy powder size.Moreover,we present a novel approach to achieve both high strength and high ductility through the creation of a bimodal structure consisting of both coarse and fine grains via gas atomization and spark plasma sintering processes.A bimodally structured HEA prepared with a mass ratio of 2:8 between coarse particles(75-106 μm) and fine particles(≤25 μm)yielded optimal results,with a strength of 491.95 MPa and elongation of 19.64%.This strength value represents an~41% increase compared with the sample that displayed a fine single microstructure(347.08 MPa for yield strength).The strength enhancement was attributed to the prevention of plastic deformation initiation from the fine particles during deformation.This innovative approach to the creation of HEAs with bimodal structures shows promise for various applications,such as structural components that require a combination of high strength and high ductility.展开更多
Electromagnetic Spectrum(EMS)recognition is vital in spectrum control,interference location,electronic countermeasures,etc.However,samples of high-value targets are incredibly scarce,even single,and are easily overwhe...Electromagnetic Spectrum(EMS)recognition is vital in spectrum control,interference location,electronic countermeasures,etc.However,samples of high-value targets are incredibly scarce,even single,and are easily overwhelmed by noise and numerous low-value targets,resulting in poor recognition accuracy using traditional methods.Furthermore,the great similarity between samples from the same manufacturer,model,and batch,makes Specific Emitter Identification(SEI)with the EMS especially challenging.Based on the powerful extension and extraction ability of the Fractional Fourier Transform(FrFT)for detailed features,this paper proposes a novel algorithm for the EMS recognition under a single-sample condition.The proposed method constructs a feature matrix FrFT-M from the results of the FrFT under specific orders for each sample.Then,the most relevant item,obtained by analyzing the correlations among FrFT-Ms between the unidentified sample and known samples,determines the optimal recognition.Three simple tests are conducted,including two simulations considering fifteen basic waveforms and six typical radar signals,and one experiment using STM32 microcontroller boards.The detection results of simulated and experimental data show that the accuracies of all three cases are higher than 86%,even for samples of the same model.Our method is promising and may have significant value in other fields.展开更多
SnTe has received considerable attention as an environmentally friendly alternative to the representative thermoelectric material of PbTe.However,excessive hole carrier concentration in SnTe results in an extremely lo...SnTe has received considerable attention as an environmentally friendly alternative to the representative thermoelectric material of PbTe.However,excessive hole carrier concentration in SnTe results in an extremely low Seebeck coefficient and high thermal conductivity,which makes it exhibit relatively inferior thermoelectric properties.In this work,the thermoelectric performance of p-type SnTe is enhanced through regulating its energy band structures and reducing its electronic thermal conductivity by combining Bi doping with CdSe alloying.First,the carrier concentration of SnTe is successfully suppressed via Bi doping,which significantly decreases the electronic thermal conductivity.Then,the convergence and flattening of the valence bands by alloying CdSe effectively improves the effective mass of SnTe while restraining its carrier mobility.Finally,a maximum figure of merit(ZT) of~ 0.87 at 823 K and an average ZT of~ 0.51 at 300-823 K have been achieved in Sn_(0.96)Bi_(0.04)Te-5%CdSe.Our results indicate that decreasing the electronic thermal conductivity is an effective means of improving the performance of thermoelectric materials with a high carrier concentration.展开更多
As one of the core modules for air traffic flow management,Air Traffic Flow Prediction(ATFP)in the Multi-Airport System(MAS)is a prerequisite for demand and capacity balance in the complex meteorological environment.D...As one of the core modules for air traffic flow management,Air Traffic Flow Prediction(ATFP)in the Multi-Airport System(MAS)is a prerequisite for demand and capacity balance in the complex meteorological environment.Due to the challenge of implicit interaction mechanism among traffic flow,airspace capacity and weather impact,the Weather-aware ATFP(Wa-ATFP)is still a nontrivial issue.In this paper,a novel Multi-faceted Spatio-Temporal Graph Convolutional Network(MSTGCN)is proposed to address the Wa-ATFP within the complex operations of MAS.Firstly,a spatio-temporal graph is constructed with three different nodes,including airport,route,and fix to describe the topology structure of MAS.Secondly,a weather-aware multi-faceted fusion module is proposed to integrate the feature of air traffic flow and the auxiliary features of capacity and weather,which can effectively address the complex impact of severe weather,e.g.,thunderstorms.Thirdly,to capture the latent connections of nodes,an adaptive graph connection constructor is designed.The experimental results with the real-world operational dataset in Guangdong-Hong Kong-Macao Greater Bay Area,China,validate that the proposed approach outperforms the state-of-the-art machine-learning and deep-learning based baseline approaches in performance.展开更多
Biomimetic materials that use natural wisdom to solve practical problems are developing rapidly.The trend for systematic biomimicry is towards in-situ characterization of naturalcreatures with high spatial resolutions...Biomimetic materials that use natural wisdom to solve practical problems are developing rapidly.The trend for systematic biomimicry is towards in-situ characterization of naturalcreatures with high spatial resolutions.Furthermore,rapid reconstruction of digital twin models with the same complex features as the prototype is indispensable.However,it faces bottlenecks and limits in fast characterization and fabrication,precise parameter optimization,geometricdeviations control,and quality prediction.To solve these challenges,here,we demonstrate astate-of-the-art method taking advantage of micro-computed tomography and three-dimensional printing for the fast characterization of the pitcher plant Nepenthes x ventrata and fabrication of its biomimetic model to obtain a superior drainage controller with multiscale structures withprecise surface morphology optimization and geometric deviation control.Thefilm-rupture-based drainage dynamic and mechanisms are characterized by x-ray and high-speed videography,which determines the crucial structures for unique directionaldrainage.Then the optimized artificial pitchers are further developed into sustained drainage devices with novel applications,such as detection,reaction,and smoke control.展开更多
Single crystal(SX)superalloys are required for full-operating-temperature mechanical properties.How-ever,the quest for intermediate temperature(IT)resistance often encounters a perplexing phenomenon:anomalous yielding...Single crystal(SX)superalloys are required for full-operating-temperature mechanical properties.How-ever,the quest for intermediate temperature(IT)resistance often encounters a perplexing phenomenon:anomalous yielding behavior coupled with an unexpected loss of ductility.This study delved into the tensile behavior of a[111]-oriented SX superalloy from room temperature(RT)to 1150℃,uncover-ing temperature-dependent tensile mechanisms where the interplay among phases and deferent de-fects governs plastic deformation.Desirable high strength-ductility properties were observed at IT,show-casing comparable strength with increased ductility.Microstructural evidences show that the primary strengthening effects stem from coupled interface boundary strengthening and anti-phase boundary(APB)strengthening,while the plasticity arises from planer defects transitioning from the stacking fault(SF)withinγphase at small strains,to superlattice SFs,ultimately to the erasure of superlattice SFs,leaving cutting dislocation pairs inγʹphase.Energy analysis of APB and SF,along with adherence to Schmid laws,reinforce the plausibility of such intricate defect interactions.The strength-ductility balance can be ascribed to the collective effect of preferentially generated dislocations and prompt formation of SF.This strategy of sequential defects’competition provides a new route for solving the strength-ductility trade-offof alloys.展开更多
Flight delay prediction has attracted great interest in civil aviation community due to its significant role in airline planning,flight scheduling,airport operation,and passenger service.Flight delay is affected by nu...Flight delay prediction has attracted great interest in civil aviation community due to its significant role in airline planning,flight scheduling,airport operation,and passenger service.Flight delay is affected by numerous factors and irregularly propagates in air transportation networks owing to flight connectivity,which brings critical challenges to accurate flight delay prediction.In recent years,Graph Convolutional Networks(GCNs)have become popular in flight delay prediction due to the advantage in extracting complicated relationships.However,most of the existing GCN-based methods have failed to effectively capture the spatial-temporal information in flight delay prediction.In this paper,a Geographical and Operational Graph Convolutional Network(GOGCN)is proposed for multi-airport flight delay prediction.The GOGCN is a GCN-based spatial-temporal model that improves node feature representation ability with geographical and operational spatial-temporal interactions in a graph.Specifically,an operational aggregator is designed to extract global operational information based on the graph structure,while a geographical aggregator is developed to capture the similar nature among spatially close airports.Extensive experiments on a real-world dataset demonstrate that the proposed approach outperforms the state-of-the-art methods with a satisfying accuracy improvement.展开更多
Reversible proton ceramic electrochemical cell(R-PCEC)is regarded as the most promising energy conversion device,which can realize efficient mutual conversion of electrical and chemical energy and to solve the problem...Reversible proton ceramic electrochemical cell(R-PCEC)is regarded as the most promising energy conversion device,which can realize efficient mutual conversion of electrical and chemical energy and to solve the problem of large-scale energy storage.However,the development of robust electrodes with high catalytic activity is the main bottleneck for the commercialization of R-PCECs.Here,a novel type of high-entropy perovskite oxide consisting of six equimolar metals in the A-site,Pr_(1/6)La_(1/6)Nd_(1/6)Ba_(1/6)Sr_(1/6)Ca_(1/6)CoO_(3−δ)(PLN-BSCC),is reported as a high-performance bifunctional air electrode for R-PCEC.By harnessing the unique functionalities of multiple ele-ments,high-entropy perovskite oxide can be anticipated to accelerate reaction rates in both fuel cell and electrolysis modes.Especially,an R-PCEC utilizing the PLNBSCC air electrode achieves exceptional electrochemical performances,demonstrating a peak power density of 1.21 W cm^(−2)for the fuel cell,while simultaneously obtaining an astonishing current density of−1.95 A cm^(−2)at an electrolysis voltage of 1.3 V and a temperature of 600℃.The significantly enhanced electrochemical performance and durability of the PLNBSCC air electrode is attributed mainly to the high electrons/ions conductivity,fast hydration reactivity and high configurational entropy.This research explores to a new avenue to develop optimally active and stable air electrodes for R-PCECs.展开更多
The maneuvering time on the ground accounts for 10%–30%of their flight time,and it always exceeds 50%for short-haul aircraft when the ground traffic is congested.Aircraft also contribute significantly to emissions,fu...The maneuvering time on the ground accounts for 10%–30%of their flight time,and it always exceeds 50%for short-haul aircraft when the ground traffic is congested.Aircraft also contribute significantly to emissions,fuel burn,and noise when taxiing on the ground at airports.There is an urgent need to reduce aircraft taxiing time on the ground.However,it is too expensive for airports and aircraft carriers to build and maintain more runways,and it is space-limited to tow the aircraft fast using tractors.Autonomous drive capability is currently the best solution for aircraft,which can save the maneuver time for aircraft.An idea is proposed that the wheels are driven by APU-powered(auxiliary power unit)motors,APU is working on its efficient point;consequently,the emissions,fuel burn,and noise will be reduced significantly.For Front-wheel drive aircraft,the front wheel must provide longitudinal force to tow the plane forward and lateral force to help the aircraft make a turn.Forward traction effects the aircraft’s maximum turning ability,which is difficult to be modeled to guide the controller design.Deep reinforcement learning provides a powerful tool to help us design controllers for black-box models;however,the models of related works are always simplified,fixed,or not easily modified,but that is what we care about most.Only with complex models can the trained controller be intelligent.High-fidelity models that can easily modified are necessary for aircraft ground maneuver controller design.This paper focuses on the maneuvering problem of front-wheel drive aircraft,a high-fidelity aircraft taxiing dynamic model is established,including the 6-DOF airframe,landing gears,and nonlinear tire force model.A deep reinforcement learning based controller was designed to improve the maneuver performance of front-wheel drive aircraft.It is proved that in some conditions,the DRL based controller outperformed conventional look-ahead controllers.展开更多
Nb-doped TiAl alloys exhibit excellent mechanical properties at high temperatures,and the underlying mechanism and optimal doping amount remain elusive.Molecular dynamics simulation is helpful to clarify these problem...Nb-doped TiAl alloys exhibit excellent mechanical properties at high temperatures,and the underlying mechanism and optimal doping amount remain elusive.Molecular dynamics simulation is helpful to clarify these problems,but most of the existing interatomic potentials are limited to the Ti-Al binary system and lack interatomic potentials for doped alloys.Here,an intera-tomic potential of Nb-Al-Ti ternary systems based on the modified embedded-atom method was developed.The ternary potential can accurately predict the structure and thermodynamic properties of the Nb-Al-Ti system.The potential shows that the optimal Nb content for high-temperature strength-ductility synergy of TiAl single crystals is 8%,consistent with the amount of miracle synthesis of TiAl single crystals.Tensile simulations further show that the developed potential can make an effective prediction at high temperatures,indicating the potential for the development and applications of high-temperature Nb-Al-Ti ternary systems.展开更多
Motor-pump assembly is the core component of the Aerospace Electro-hydrostatic Actuator(EHA).Thus,the design of the motor pump can be very challenging under conditions of high speed and wide pressure range,especially ...Motor-pump assembly is the core component of the Aerospace Electro-hydrostatic Actuator(EHA).Thus,the design of the motor pump can be very challenging under conditions of high speed and wide pressure range,especially in particular working mediums.Our ultimate goal is to pursue better flow characteristics under a wide range of working conditions.In this paper,we built a sub-model of the main friction interfaces and a model of single-shaft coaxial motor-pump assembly adopting the method of hierarchical modeling.The experimental investigation of the output characteristics was mainly carried out in a phosphate ester medium environment.Then,the flow characteristics were compared and analyzed with the simulation results.Results indicated that the flow characteristics of the motor-pump assembly could be accurately simulated by the model and quite severe in a low speed and high-pressure environment.展开更多
To improve the power density and simplify the seal structure,the Wet-Type Permanent Magnet Synchronous Motor(WTPMSM)technique has been applied to aerospace Electro-Hydrostatic Actuators(EHA).In a WTPMSM,the stator and...To improve the power density and simplify the seal structure,the Wet-Type Permanent Magnet Synchronous Motor(WTPMSM)technique has been applied to aerospace Electro-Hydrostatic Actuators(EHA).In a WTPMSM,the stator and the rotor are both immersed in the aviation hydraulic oil.Although the heat dissipation performance of the WTPMSM can be enhanced,the aviation hydraulic oil will cost an extra oil frictional loss in the narrow airgap of the WTPMSM.This paper proposes an accurate oil frictional loss model for the WTPMSM,in which the wide speed range(0–20 kr/min)and the narrowness of the airgap(0.5–1.5 mm)are its features.Firstly,the mechanism of the oil frictional loss in the airgap of the WTPMSM is revealed.Then an accurate oil frictional loss model is proposed considering the nonlinear influence caused by the Taylor vortex.Furthermore,the influence of motor dimensions on oil frictional loss is analyzed.Finally,the proposed oil frictional loss model is verified by experiments,which provides a guideline for engineers to follow in the WTPMSM design.展开更多
(γ’+β)two-phase Ni-Al is a promising high-temperature protective coating material used on Ni-base superalloys since it has good interfacial compatibility with superalloys due to the low Al content compared to singl...(γ’+β)two-phase Ni-Al is a promising high-temperature protective coating material used on Ni-base superalloys since it has good interfacial compatibility with superalloys due to the low Al content compared to single-phaseβ-NiA l.In this paper,we aim to improve the oxidation resistance,whereby Ni-34Al-0.1Dy,a(γ’+β)two-phase Ni-Al alloy,was treated by laser shock processing(LSP)and the oxidation behavior at 1150℃ was investigated.The results showed that after oxidation,Al_(2)O_(3)scale formed on the originalβphase of the untreated alloy with a small grain size(200-800 nm),while for the LSP-treated samples,the scale grown on the originalβphase was dominantly composed of larger Al_(2)O_(3)grains with a size of 2-3μm.The distinction was attributed to the promotion ofθ-Al_(2)O_(3)toα-Al_(2)O_(3)transformation induced by the LSP,because the dislocation density,as well as surface roughness,were increased during LSP treatment which can provide heterogeneous nucleation sites forα-Al_(2)O_(3).In addition,the larger-size Al_(2)O_(3)particles,derived from the direct conversion of needle-likeθ-Al_(2)O_(3)in the initial oxidation stage,could rapidly overspread the wholeβphase surface thus reducing the scale growth rate.展开更多
Zero-field single-beam atomic magnetometers with transverse parametric modulation for ultra-weak magnetic field detection have attracted widespread attention recently.In this study,we present a comprehensive response ...Zero-field single-beam atomic magnetometers with transverse parametric modulation for ultra-weak magnetic field detection have attracted widespread attention recently.In this study,we present a comprehensive response model and propose a modification method of conventional first harmonic response by introducing the second harmonic correction.The proposed modification method gives improvement in dynamic range and reduction of linearity error.Additionally,our modification method shows suppression of response instability caused by optical intensity and frequency fluctuations.An atomic magnetometer with single-beam configuration is built to compare the performance between our proposed method and the conventional method.The results indicate that our method’s magnetic field response signal achieves a 5-fold expansion of dynamic range from 2 nT to 10 nT,with the linearity error decreased from 5%to 1%.Under the fluctuations of 5%for optical intensity and±15 GHz detuning of frequency,the proposed modification method maintains intensityrelated instability less than 1%and frequency-related instability less than 8%while the conventional method suffers 15%and 38%,respectively.Our method is promising for future high-sensitive and long-term stable optically pumped atomic sensors.展开更多
Thermoelectric materials have drawn extensive interest due to the direct conversion between electricity and heat,however,it is usually a time-consuming process for applying traditional“sequential”meth-ods to grow ma...Thermoelectric materials have drawn extensive interest due to the direct conversion between electricity and heat,however,it is usually a time-consuming process for applying traditional“sequential”meth-ods to grow materials and investigate their properties,especially for thermoelectric films that typically require fine microstructure control.High-throughput experimental approaches can effectively accelerate materials development,but the methods for high-throughput screening of the microstructures require further study.In this work,a combinatorial high-throughput optimization solution of material properties is proposed for the parallel screening and optimizing of composition and microstructure,which involves two distinctive types of high-throughput fabrication approaches for thin films,along with a new portable multiple discrete masks based high-throughput preparation platform.Thus,Bi_(2)Te_(3-x)Se_(x)thin film library with 196 throughputs for locating the optimized composition is obtained in one growth cycle.In addition,another thin film library composed of 31 materials with traceable process parameters is built to further investigate the relationship between microstructure,process,and thermoelectric performance.Through high-throughput screening,the Bi_(2)Te_(2.9)Se_(0.1)film with(00l)orientation is prepared with a peak zT value of 1.303 at 353 K along with a high average zT value of 1.047 in the interval from 313 to 523 K.This method can be also extended to the discovery of other functional thin films with a rapid combinatorial screening of the composition and structure to accelerate material optimization.展开更多
基金supported by the Natural Science Foundation for Young Scholars of Jiangsu Province(No.BK20220879)the National Natural Science Foundation of China(No.22209072 and No.22479075)+1 种基金the Open Research Fund of Guangdong Advanced Carbon Materials Co.,Ltd(No.Kargen-2024B0801)the Jiangsu Specially-Appointed Professors and National Natural Science Fund of China for Excellent Young Scientists Fund Program(Overseas)。
文摘Proton exchange membrane water electrolyzer(PEMWE)represents a highly promising technology for renewable hydrogen generation,urgently demanding low-cost,efficient,and robust anode oxygen evolution reaction(OER)electrocatalysts in acidic media.Over the past decade(mainly from 2016 onwards),low-Ir/Ru perovskite oxides have emerged as promising candidate materials for acidic OER electrocatalysis owing to their flexible element compositions and crystal structures,which can evidently reduce the noble-metal content and meanwhile significantly promote electrocatalytic performance.In this review,the current research progress in low-Ir/Ru perovskite oxides for acidic OER electrocatalysis is comprehensively summarized.Initially,we present a brief introduction to general issues relevant to acidic OER catalyzed by low-Ir/Ru perovskite oxides,such as the actual active species,OER mechanisms,inverse activity-stability relationship,and performance evaluation metrics.Subsequently,we present a thorough overview of various low-Ir/Ru perovskite oxides for acidic OER electrocatalysis,including single perovskites,double perovskites,triple perovskites,quadruple perovskites,Ruddlesden-Popper perovskites,and other complex perovskite-derived oxides,with emphasis on the intrinsic factors contributing to their exceptional performance and structure-property-performance correlation.Finally,remaining challenges and some promising insights to inspire future studies in this exciting field are provided.
基金financial support from the UK's Engineering and Physical Sciences Research Council,EPSRC First Grant Scheme EP/P025978/1Early Career Fellowship Scheme EP/R043973/1financial support from the National Natural Science Foundation of China(No.52071006).
文摘This paper reports the use of integrated computational alloy design,coupled with a rapid printability screening method,to downselect from a total of 70000 datasets in design space to five candidates in the first step,and then from five to one in the second step.The new Ni-base superalloy with compositions of Ni-5.03Al-2.69Co-5.63Cr-0.04Hf-1.91Mo-2.36Re-3.32Ta-0.57Ti-8.46W-0.05C-0.019B exhibits an optimal balance of density(8.82 g/cm2),printability(freezing range of 107℃),thermal stability(γ′-volume fraction of 50.7%at 980℃and low M_(d)value)and creep(rupture time of 612 h at 980℃/120 MPa).The micro-hardness varies mildly from 417.2±18.5 to 434.7±14.6 HV,suggesting good phase stability.This is substantiated by microstructure observations,which revealed the absence of a topologically close-packed phase.Machine-learning tools of the artificial neural network(ANN),random forest,and support vector regression,respectively,were used to predict creep rupture time.The ANN algorithm achieves the highest accuracy in predicting creep life.By recognising the“black box”nature of the ANN,interpretability analysis was conducted using the local interpretable model-agnostic method.The analysis supports that the ANN model truly learned meaningful functional relationships,and thus is judged as reliable.Feature correlation evaluation outcome emphasises the importance of incorporating microstructure-related input features.
基金supported by the National Natural Science Foundation of China(22305119,12204234)the Natural Science Foundation of Jiangsu Province(BK20220878)+3 种基金the Fundamental Research Funds for the Central Universities(NS2023059)the China Postdoctoral Science Foundation(2022TQ0157,2023M741695)the Liaoning University Talent Introduction Research Startup Project(d295000048)the Center for Microscopy and Analysis of Nanjing University of Aeronautics and Astronautics for characterization support。
文摘The optimization of hole transport layer(HTL)is crucial for achieving high efficiency and stability in inverted perovskite solar cells(PSCs)due to its role in facilitating hole transport and passivating the perovskite bottom interface.While self-assembled monolayers(SAMs)are commonly used for this purpose,the inherent limitations of a single SAM,such as fixed energy levels and rigid structure,restrict their adaptability for different perovskite components and further efficiency enhancement.Here,we demonstrate a stepwise deposition method for SAM-based HTLs to address this issue.We regulated the energy level gradient by depositing two SAMs with distinct energy levels,while the interactions between the phosphate groups in the SAMs and perovskite effectively reduce defect density at the bottom interface of the perovskite film.The as-fabricated PSCs achieved enhanced efficiency and stability with PCEs of 25.7% and 24.0% for rigid and flexible PSCs,respectively;these devices maintain 90% of their initial PCE after 500 h of maximum power point tracking,and retain 98% of their initial PCE after 4,000 bending cycles,representing one of the most stable flexible PSCs reported to date.
基金the support from the National Science and Technology Major Project, China (No. J2019IV-0014-0082)the National Key Research and Development Program of China (No. 2022YFB4600700)+1 种基金the National Overseas Youth Talents Program, China, the Research Fund of State Key Laboratory of Mechanics and Control for Aerospace Structures, China (No. MCMS-I-0422K01)a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions, China。
文摘Fatigue properties of materials by Additive Manufacturing(AM) depend on many factors such as AM processing parameter, microstructure, residual stress, surface roughness, porosities, post-treatments, etc. Their evaluation inevitably requires these factors combined as many as possible, thus resulting in low efficiency and high cost. In recent years, their assessment by leveraging the power of Machine Learning(ML) has gained increasing attentions. A comprehensive overview on the state-of-the-art progress of applying ML strategies to predict fatigue properties of AM materials, as well as their dependence on AM processing and post-processing parameters such as laser power, scanning speed, layer height, hatch distance, built direction, post-heat temperature,etc., were presented. A few attempts in employing Feedforward Neural Network(FNN), Convolutional Neural Network(CNN), Adaptive Network-Based Fuzzy Inference System(ANFIS), Support Vector Machine(SVM) and Random Forest(RF) to predict fatigue life and RF to predict fatigue crack growth rate are summarized. The ML models for predicting AM materials' fatigue properties are found intrinsically similar to the commonly used ones, but are modified to involve AM features. Finally, an outlook for challenges(i.e., small dataset, multifarious features,overfitting, low interpretability, and unable extension from AM material data to structure life) and potential solutions for the ML prediction of AM materials' fatigue properties is provided.
基金funded by the National Natural Science Foundation of China(Grant No.12272020)Beijing Natural Science Foundation(Grant No.JQ21001)+1 种基金S.W.acknowledges support from the Fundamental Research Funds for the Central Universities(Grant No.YWF-23-SDHK-L-019)M.Y.acknowledges support from the National Natural Science Foundation of China(Grant Nos.12302134,12272173,and 11902150).
文摘Flexoelectricity is a two-way coupling effect between the strain gradient and electric field that exists in all dielectrics,regardless of point group symmetry.However,the high-order derivatives of displacements involved in the strain gradient pose challenges in solving electromechanical coupling problems incorporating the flexoelectric effect.In this study,we formulate a phase-field model for ferroelectric materials considering the flexoelectric effect.A four-node quadrilateral element with 20 degrees of freedom is constructed without introducing high-order shape functions.The microstructure evolution of domains is described by an independent order parameter,namely the spontaneous polarization governed by the time-dependent Ginzburg–Landau theory.The model is developed based on a thermodynamic framework,in which a set of microforces is introduced to construct the constitutive relation and evolution equation.For the flexoelectric part of electric enthalpy,the strain gradient is determined by interpolating the mechanical strain at the node via the values of Gaussian integration points in the isoparametric space.The model is shown to be capable of reproducing the classic analytical solution of dielectric materials incorporating the flexoelectric contribution.The model is verified by duplicating some typical phenomena in flexoelectricity in cylindrical tubes and truncated pyramids.A comparison is made between the polarization distribution in dielectrics and ferroelectrics.The model can reproduce the solution to the boundary value problem of the cylindrical flexoelectric tube,and demonstrate domain twisting at domain walls in ferroelectrics considering the flexoelectric effect.
基金financially supported by the Ministry of Trade,Industry&Energy (MOTIE,Korea)(No.20011520)Korea Institute of Energy Technology Evaluation and Planning (KETEP)(No.20217510100020)the Commercialization Promotion Agency for R&D Outcomes (COMPA)(No.1711175258)。
文摘The CoCrFeMnNi high-entropy alloys(HEAs)with a(face-centered cubic) FCC structure has garnered considerable attention for its exceptional ductility and strain hardening ability.However,its yield strength is insufficient for structural applications.In this study,strengthening mechanisms in these HEAs were investigated to gain insight into the mechanical properties according to alloy powder size.Moreover,we present a novel approach to achieve both high strength and high ductility through the creation of a bimodal structure consisting of both coarse and fine grains via gas atomization and spark plasma sintering processes.A bimodally structured HEA prepared with a mass ratio of 2:8 between coarse particles(75-106 μm) and fine particles(≤25 μm)yielded optimal results,with a strength of 491.95 MPa and elongation of 19.64%.This strength value represents an~41% increase compared with the sample that displayed a fine single microstructure(347.08 MPa for yield strength).The strength enhancement was attributed to the prevention of plastic deformation initiation from the fine particles during deformation.This innovative approach to the creation of HEAs with bimodal structures shows promise for various applications,such as structural components that require a combination of high strength and high ductility.
基金supported in part by the National Natural Science Foundation of China(No.62293495)。
文摘Electromagnetic Spectrum(EMS)recognition is vital in spectrum control,interference location,electronic countermeasures,etc.However,samples of high-value targets are incredibly scarce,even single,and are easily overwhelmed by noise and numerous low-value targets,resulting in poor recognition accuracy using traditional methods.Furthermore,the great similarity between samples from the same manufacturer,model,and batch,makes Specific Emitter Identification(SEI)with the EMS especially challenging.Based on the powerful extension and extraction ability of the Fractional Fourier Transform(FrFT)for detailed features,this paper proposes a novel algorithm for the EMS recognition under a single-sample condition.The proposed method constructs a feature matrix FrFT-M from the results of the FrFT under specific orders for each sample.Then,the most relevant item,obtained by analyzing the correlations among FrFT-Ms between the unidentified sample and known samples,determines the optimal recognition.Three simple tests are conducted,including two simulations considering fifteen basic waveforms and six typical radar signals,and one experiment using STM32 microcontroller boards.The detection results of simulated and experimental data show that the accuracies of all three cases are higher than 86%,even for samples of the same model.Our method is promising and may have significant value in other fields.
基金financially supported by the National Natural Science Foundation of China (Nos.52102234 and 51972094)the High-level Talents Research Initiation Project of Hebei University (No.521000981421)Hebei Province Introduced Overseas Student Funding Project (No.C20210313)。
文摘SnTe has received considerable attention as an environmentally friendly alternative to the representative thermoelectric material of PbTe.However,excessive hole carrier concentration in SnTe results in an extremely low Seebeck coefficient and high thermal conductivity,which makes it exhibit relatively inferior thermoelectric properties.In this work,the thermoelectric performance of p-type SnTe is enhanced through regulating its energy band structures and reducing its electronic thermal conductivity by combining Bi doping with CdSe alloying.First,the carrier concentration of SnTe is successfully suppressed via Bi doping,which significantly decreases the electronic thermal conductivity.Then,the convergence and flattening of the valence bands by alloying CdSe effectively improves the effective mass of SnTe while restraining its carrier mobility.Finally,a maximum figure of merit(ZT) of~ 0.87 at 823 K and an average ZT of~ 0.51 at 300-823 K have been achieved in Sn_(0.96)Bi_(0.04)Te-5%CdSe.Our results indicate that decreasing the electronic thermal conductivity is an effective means of improving the performance of thermoelectric materials with a high carrier concentration.
基金supported by the National Key Research and Development Program of China(No.2022YFB2602402)the National Natural Science Foundation of China(Nos.U2033215 and U2133210).
文摘As one of the core modules for air traffic flow management,Air Traffic Flow Prediction(ATFP)in the Multi-Airport System(MAS)is a prerequisite for demand and capacity balance in the complex meteorological environment.Due to the challenge of implicit interaction mechanism among traffic flow,airspace capacity and weather impact,the Weather-aware ATFP(Wa-ATFP)is still a nontrivial issue.In this paper,a novel Multi-faceted Spatio-Temporal Graph Convolutional Network(MSTGCN)is proposed to address the Wa-ATFP within the complex operations of MAS.Firstly,a spatio-temporal graph is constructed with three different nodes,including airport,route,and fix to describe the topology structure of MAS.Secondly,a weather-aware multi-faceted fusion module is proposed to integrate the feature of air traffic flow and the auxiliary features of capacity and weather,which can effectively address the complex impact of severe weather,e.g.,thunderstorms.Thirdly,to capture the latent connections of nodes,an adaptive graph connection constructor is designed.The experimental results with the real-world operational dataset in Guangdong-Hong Kong-Macao Greater Bay Area,China,validate that the proposed approach outperforms the state-of-the-art machine-learning and deep-learning based baseline approaches in performance.
基金provided by the National sKey R&D Program of China(2021YFA0716701)the National Natural Science Foundation of China(22005014,.22275007,22102204)+1 种基金Beihang University’s Young Talents(No.KG16164901)Open Foundation of the State Key Laboratory of Precision Measuring Technology and Instruments(No.pilab2106)。
文摘Biomimetic materials that use natural wisdom to solve practical problems are developing rapidly.The trend for systematic biomimicry is towards in-situ characterization of naturalcreatures with high spatial resolutions.Furthermore,rapid reconstruction of digital twin models with the same complex features as the prototype is indispensable.However,it faces bottlenecks and limits in fast characterization and fabrication,precise parameter optimization,geometricdeviations control,and quality prediction.To solve these challenges,here,we demonstrate astate-of-the-art method taking advantage of micro-computed tomography and three-dimensional printing for the fast characterization of the pitcher plant Nepenthes x ventrata and fabrication of its biomimetic model to obtain a superior drainage controller with multiscale structures withprecise surface morphology optimization and geometric deviation control.Thefilm-rupture-based drainage dynamic and mechanisms are characterized by x-ray and high-speed videography,which determines the crucial structures for unique directionaldrainage.Then the optimized artificial pitchers are further developed into sustained drainage devices with novel applications,such as detection,reaction,and smoke control.
基金sponsored by the National Natural Science Foundations of China(Nos.52101116,52301126,and 92360302)the Science Center for Gas Turbine Project(Nos.P2022-A-I-001-001 and P2022-A-Ⅰ-002-002)+2 种基金the National Science and Technology Major Project(No.2019-Ⅵ-0016-0131)the Beijing Nova Program(No.20230484318)the Key R&D Program of Zhejiang(No.2024SSYS0076).
文摘Single crystal(SX)superalloys are required for full-operating-temperature mechanical properties.How-ever,the quest for intermediate temperature(IT)resistance often encounters a perplexing phenomenon:anomalous yielding behavior coupled with an unexpected loss of ductility.This study delved into the tensile behavior of a[111]-oriented SX superalloy from room temperature(RT)to 1150℃,uncover-ing temperature-dependent tensile mechanisms where the interplay among phases and deferent de-fects governs plastic deformation.Desirable high strength-ductility properties were observed at IT,show-casing comparable strength with increased ductility.Microstructural evidences show that the primary strengthening effects stem from coupled interface boundary strengthening and anti-phase boundary(APB)strengthening,while the plasticity arises from planer defects transitioning from the stacking fault(SF)withinγphase at small strains,to superlattice SFs,ultimately to the erasure of superlattice SFs,leaving cutting dislocation pairs inγʹphase.Energy analysis of APB and SF,along with adherence to Schmid laws,reinforce the plausibility of such intricate defect interactions.The strength-ductility balance can be ascribed to the collective effect of preferentially generated dislocations and prompt formation of SF.This strategy of sequential defects’competition provides a new route for solving the strength-ductility trade-offof alloys.
基金supported by the National Natural Science Foundation of China(Nos.71731001,U2133210,and U2033215,61822102)。
文摘Flight delay prediction has attracted great interest in civil aviation community due to its significant role in airline planning,flight scheduling,airport operation,and passenger service.Flight delay is affected by numerous factors and irregularly propagates in air transportation networks owing to flight connectivity,which brings critical challenges to accurate flight delay prediction.In recent years,Graph Convolutional Networks(GCNs)have become popular in flight delay prediction due to the advantage in extracting complicated relationships.However,most of the existing GCN-based methods have failed to effectively capture the spatial-temporal information in flight delay prediction.In this paper,a Geographical and Operational Graph Convolutional Network(GOGCN)is proposed for multi-airport flight delay prediction.The GOGCN is a GCN-based spatial-temporal model that improves node feature representation ability with geographical and operational spatial-temporal interactions in a graph.Specifically,an operational aggregator is designed to extract global operational information based on the graph structure,while a geographical aggregator is developed to capture the similar nature among spatially close airports.Extensive experiments on a real-world dataset demonstrate that the proposed approach outperforms the state-of-the-art methods with a satisfying accuracy improvement.
基金The work was supported by National Natural Science Foundation of China(21878158 and 21706129)State Key Laboratory of Clean Energy Utilization(Open Fund Project No.ZJUCEU2021001)Natural Science Foundation of Jiangsu Province(BK20221312).
文摘Reversible proton ceramic electrochemical cell(R-PCEC)is regarded as the most promising energy conversion device,which can realize efficient mutual conversion of electrical and chemical energy and to solve the problem of large-scale energy storage.However,the development of robust electrodes with high catalytic activity is the main bottleneck for the commercialization of R-PCECs.Here,a novel type of high-entropy perovskite oxide consisting of six equimolar metals in the A-site,Pr_(1/6)La_(1/6)Nd_(1/6)Ba_(1/6)Sr_(1/6)Ca_(1/6)CoO_(3−δ)(PLN-BSCC),is reported as a high-performance bifunctional air electrode for R-PCEC.By harnessing the unique functionalities of multiple ele-ments,high-entropy perovskite oxide can be anticipated to accelerate reaction rates in both fuel cell and electrolysis modes.Especially,an R-PCEC utilizing the PLNBSCC air electrode achieves exceptional electrochemical performances,demonstrating a peak power density of 1.21 W cm^(−2)for the fuel cell,while simultaneously obtaining an astonishing current density of−1.95 A cm^(−2)at an electrolysis voltage of 1.3 V and a temperature of 600℃.The significantly enhanced electrochemical performance and durability of the PLNBSCC air electrode is attributed mainly to the high electrons/ions conductivity,fast hydration reactivity and high configurational entropy.This research explores to a new avenue to develop optimally active and stable air electrodes for R-PCECs.
基金Funded by National Natural Science Foundation of China(No.51775014)Open Foundation of the State Key Laboratory of Fluid Power and Mechatronic Systems of China(No.GZKF-202010)+1 种基金National Key R&D Program of China(No.2019YFB2004503)the Science and Technology on Aircraft Control Laboratory of China。
文摘The maneuvering time on the ground accounts for 10%–30%of their flight time,and it always exceeds 50%for short-haul aircraft when the ground traffic is congested.Aircraft also contribute significantly to emissions,fuel burn,and noise when taxiing on the ground at airports.There is an urgent need to reduce aircraft taxiing time on the ground.However,it is too expensive for airports and aircraft carriers to build and maintain more runways,and it is space-limited to tow the aircraft fast using tractors.Autonomous drive capability is currently the best solution for aircraft,which can save the maneuver time for aircraft.An idea is proposed that the wheels are driven by APU-powered(auxiliary power unit)motors,APU is working on its efficient point;consequently,the emissions,fuel burn,and noise will be reduced significantly.For Front-wheel drive aircraft,the front wheel must provide longitudinal force to tow the plane forward and lateral force to help the aircraft make a turn.Forward traction effects the aircraft’s maximum turning ability,which is difficult to be modeled to guide the controller design.Deep reinforcement learning provides a powerful tool to help us design controllers for black-box models;however,the models of related works are always simplified,fixed,or not easily modified,but that is what we care about most.Only with complex models can the trained controller be intelligent.High-fidelity models that can easily modified are necessary for aircraft ground maneuver controller design.This paper focuses on the maneuvering problem of front-wheel drive aircraft,a high-fidelity aircraft taxiing dynamic model is established,including the 6-DOF airframe,landing gears,and nonlinear tire force model.A deep reinforcement learning based controller was designed to improve the maneuver performance of front-wheel drive aircraft.It is proved that in some conditions,the DRL based controller outperformed conventional look-ahead controllers.
基金the National Key Research and Development Program of China(Grant No.2019YF40705400)National Natural Science Foundation of China(Grant Nos.51535005,51731006,and 51771093)+2 种基金the Research Fund of State Key Laboratory of Mechanics and Control of Me-chanical Structures(Grant Nos.MCMS-I-0418K01,MCMS-I-0419K01)the Fundamental Research Funds for the Central Universities(Grant Nos.NZ2020001,NC2018001,NP2019301,NJ20I 9002,and 30919011295)the Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions.
文摘Nb-doped TiAl alloys exhibit excellent mechanical properties at high temperatures,and the underlying mechanism and optimal doping amount remain elusive.Molecular dynamics simulation is helpful to clarify these problems,but most of the existing interatomic potentials are limited to the Ti-Al binary system and lack interatomic potentials for doped alloys.Here,an intera-tomic potential of Nb-Al-Ti ternary systems based on the modified embedded-atom method was developed.The ternary potential can accurately predict the structure and thermodynamic properties of the Nb-Al-Ti system.The potential shows that the optimal Nb content for high-temperature strength-ductility synergy of TiAl single crystals is 8%,consistent with the amount of miracle synthesis of TiAl single crystals.Tensile simulations further show that the developed potential can make an effective prediction at high temperatures,indicating the potential for the development and applications of high-temperature Nb-Al-Ti ternary systems.
基金This study was co-supported by the Chinese Civil Aircraft Project(No.MJ-2017-S49)China Postdoctoral Science Foundation(No.2021M700331).
文摘Motor-pump assembly is the core component of the Aerospace Electro-hydrostatic Actuator(EHA).Thus,the design of the motor pump can be very challenging under conditions of high speed and wide pressure range,especially in particular working mediums.Our ultimate goal is to pursue better flow characteristics under a wide range of working conditions.In this paper,we built a sub-model of the main friction interfaces and a model of single-shaft coaxial motor-pump assembly adopting the method of hierarchical modeling.The experimental investigation of the output characteristics was mainly carried out in a phosphate ester medium environment.Then,the flow characteristics were compared and analyzed with the simulation results.Results indicated that the flow characteristics of the motor-pump assembly could be accurately simulated by the model and quite severe in a low speed and high-pressure environment.
基金This work was supported in part by National Natural Science Foundation of China(Nos.52177028 and U2141226)in part by Major Program of the National Natural Science Foundation of China(No.51890882)in part by Aeronautical Science Foundation of China(No.201907051002).
文摘To improve the power density and simplify the seal structure,the Wet-Type Permanent Magnet Synchronous Motor(WTPMSM)technique has been applied to aerospace Electro-Hydrostatic Actuators(EHA).In a WTPMSM,the stator and the rotor are both immersed in the aviation hydraulic oil.Although the heat dissipation performance of the WTPMSM can be enhanced,the aviation hydraulic oil will cost an extra oil frictional loss in the narrow airgap of the WTPMSM.This paper proposes an accurate oil frictional loss model for the WTPMSM,in which the wide speed range(0–20 kr/min)and the narrowness of the airgap(0.5–1.5 mm)are its features.Firstly,the mechanism of the oil frictional loss in the airgap of the WTPMSM is revealed.Then an accurate oil frictional loss model is proposed considering the nonlinear influence caused by the Taylor vortex.Furthermore,the influence of motor dimensions on oil frictional loss is analyzed.Finally,the proposed oil frictional loss model is verified by experiments,which provides a guideline for engineers to follow in the WTPMSM design.
基金financially supported by the National Natural Science Foundation of China(Grant No.51901011)the National Science and Technology Major Project(Grant Nos.2017-Ⅵ-0002-0072 and 2017-VII-0007-0100)+1 种基金the Fundamental Research Funds for Central Universities(Grant No.YWF-21-BJ-J-1034)the support from Youth Talent Support Program of Beihang University。
文摘(γ’+β)two-phase Ni-Al is a promising high-temperature protective coating material used on Ni-base superalloys since it has good interfacial compatibility with superalloys due to the low Al content compared to single-phaseβ-NiA l.In this paper,we aim to improve the oxidation resistance,whereby Ni-34Al-0.1Dy,a(γ’+β)two-phase Ni-Al alloy,was treated by laser shock processing(LSP)and the oxidation behavior at 1150℃ was investigated.The results showed that after oxidation,Al_(2)O_(3)scale formed on the originalβphase of the untreated alloy with a small grain size(200-800 nm),while for the LSP-treated samples,the scale grown on the originalβphase was dominantly composed of larger Al_(2)O_(3)grains with a size of 2-3μm.The distinction was attributed to the promotion ofθ-Al_(2)O_(3)toα-Al_(2)O_(3)transformation induced by the LSP,because the dislocation density,as well as surface roughness,were increased during LSP treatment which can provide heterogeneous nucleation sites forα-Al_(2)O_(3).In addition,the larger-size Al_(2)O_(3)particles,derived from the direct conversion of needle-likeθ-Al_(2)O_(3)in the initial oxidation stage,could rapidly overspread the wholeβphase surface thus reducing the scale growth rate.
基金Project supported by the National Key R&D Program of China(Grant No.2018YFB2002405)the National Natural Science Foundation of China(Grant No.61903013)。
文摘Zero-field single-beam atomic magnetometers with transverse parametric modulation for ultra-weak magnetic field detection have attracted widespread attention recently.In this study,we present a comprehensive response model and propose a modification method of conventional first harmonic response by introducing the second harmonic correction.The proposed modification method gives improvement in dynamic range and reduction of linearity error.Additionally,our modification method shows suppression of response instability caused by optical intensity and frequency fluctuations.An atomic magnetometer with single-beam configuration is built to compare the performance between our proposed method and the conventional method.The results indicate that our method’s magnetic field response signal achieves a 5-fold expansion of dynamic range from 2 nT to 10 nT,with the linearity error decreased from 5%to 1%.Under the fluctuations of 5%for optical intensity and±15 GHz detuning of frequency,the proposed modification method maintains intensityrelated instability less than 1%and frequency-related instability less than 8%while the conventional method suffers 15%and 38%,respectively.Our method is promising for future high-sensitive and long-term stable optically pumped atomic sensors.
基金the National Key R&D Program of China(Grant No.2018YFA0702100)the National Natural Science Foundation of China(Grant No.U21A2079)+2 种基金the Beijing Natural Sci-ence Foundation(Grant No.2182032)the Zhejiang Provincial Key R&D Program of China(Grant Nos.2021C01026 and 2021C05002)and the Leading Innovative and Entrepreneur Team Introduction Program of Zhejiang(No.2020R01007).
文摘Thermoelectric materials have drawn extensive interest due to the direct conversion between electricity and heat,however,it is usually a time-consuming process for applying traditional“sequential”meth-ods to grow materials and investigate their properties,especially for thermoelectric films that typically require fine microstructure control.High-throughput experimental approaches can effectively accelerate materials development,but the methods for high-throughput screening of the microstructures require further study.In this work,a combinatorial high-throughput optimization solution of material properties is proposed for the parallel screening and optimizing of composition and microstructure,which involves two distinctive types of high-throughput fabrication approaches for thin films,along with a new portable multiple discrete masks based high-throughput preparation platform.Thus,Bi_(2)Te_(3-x)Se_(x)thin film library with 196 throughputs for locating the optimized composition is obtained in one growth cycle.In addition,another thin film library composed of 31 materials with traceable process parameters is built to further investigate the relationship between microstructure,process,and thermoelectric performance.Through high-throughput screening,the Bi_(2)Te_(2.9)Se_(0.1)film with(00l)orientation is prepared with a peak zT value of 1.303 at 353 K along with a high average zT value of 1.047 in the interval from 313 to 523 K.This method can be also extended to the discovery of other functional thin films with a rapid combinatorial screening of the composition and structure to accelerate material optimization.
