Single-Event Upsets(SEUs)in the space radiation environment pose a serious threat to the reliability of satellite-borne intelligent systems.Traditional fault-tolerance methods such as Triple Modu-lar Redundancy(TMR)and periodic scrubbing face challenges including excessive resource overhead and high power consumption.This paper presents a lightweight fault-tolerance method based on Adaptive Boosting-based Fault-Tolerance Method(AB-FTM)to address SEU vulnerabilities in convolutional neu-ral networks.The proposed approach constructs a heterogeneous ensemble architecture comprising three weak models(ResNet20,ResNet32,ResNet44)and integrated with a dynamic weight adjustment mecha-nism.By integrating a dynamic weight adjustment mechanism,the method not only significantly re-duces the parameter scale(achieving an 18.2%reduction compared to ResNet110)but also enhances classification accuracy,robustness,and fault tolerance.Experimental validation on datasets including CI-FAR-10,MNIST,EuroSAT,and Galaxy10 DECals demonstrates that when 0.032 ‰ of parameters are affected by single-event upsets,the proposed method improves classification accuracy by 53.25%,63.49%,57.67%,and 47.43%respectively compared to the TMR-based ResNet110,significantly outperforming traditional triple modular redundancy solutions.This approach provides a novel solution for future space science satellites employing satellite-borne intelligent systems,balancing reliability,lightweight design,and computational efficiency.
The Chang'E-7 orbiter is expected to carry the Wide-band InfraRed Imaging Spectrometer(WIRIS),which will acquire high spectral resolution images and thermal emission data of the lunar sur-face across a broad spectral range from the visible to longwave infrared(0.45～10 µm).These data will support scientific investigations into lunar surface mineral composition,thermal environment,and water/hydroxyl detection.Compared to previous lunar orbital hyperspectral instruments,WIRIS en-hances quantitative retrieval capabilities for key spectral features such as the Christiansen Feature(CF)of silicate minerals and molecular water.Building upon the design of the Tianwen-1 Mars Mineralogical Spectrometer,WIRIS extends its spectral coverage into the mid-to long-wave infrared range(3.3～10 μm),and incorporates simultaneous temperature measurements to reduce thermal correction uncer-tainties in the 3 μm water/hydroxyl absorption region.This study addresses the quantitative calibration requirements of the newly extended spectral range by proposing spectral,radiometric,and geometric cali-bration methods tailored for the mid-to long-wave infrared bands.Based on calibration experiments,the sources of error and associated uncertainties are analyzed.The results provide essential methodological and technical support for accurate physical parameter retrieval and scientific application of WIRIS mid-to long-wave infrared data.
The marine gravity field is a crucial physical field of the Earth system,with shipborne and satellite altimetry-derived gravity data serving as the primary sources for its high-resolution modeling.However,shipborne gravity data is sparsely and unevenly distributed globally,while single altimetry-de-rived gravity models exhibit accuracy limitations or incomplete coverage in specific regions.This study utilized high-density shipborne gravity data from the Japan Agency for Marine-Earth Science and Tech-nology(JAMSTEC)in the western Pacific Ocean(120°E-170°E,0°-50°N).Based on the latest ver-sions of two major global altimetry-derived gravity field models,DTU21 and SIOv32.1,it establishes cor-relations between the gravity model errors verified by shipborne gravity and water depths from SRTM15v2.4 model.Through weighted fusion and special processing for polar regions,a global 1'×1'gridded marine gravity anomaly model,FUSION_V1.0,was generated.This model includes longitude,latitude,and gravity anomaly variables,covering the global ocean(90°S-90°N,180°W-180°E)and adopting the simplest and most widely used geographic coordinate system(i.e.,equiangular projection),stored in NetCDF format for compatibility with mainstream scientific software.This dataset can pro-vide high-quality foundational data for seafloor topography recovery,marine geophysical research,and related space science applications.
As a key parameter of the ionosphere,the critical frequency of the F2 layer of the iono-sphere(f0F2)is of great significance for ensuring the stable operation of systems such as high-frequency radar and short-wave communication.This paper proposes a short-term forecasting method for the iono-spheric f0F2 based on deep learning.By using the Bidirectional Long Short-term Memory model with at-tention mechanism(BiLSTM-Attention)algorithm and combining the observed values of the ionosphe-ric f0F2 at the ionosonde station for the previous 7 days,Universal Time(UT),solar activity index,and geomagnetic activity index as inputs,the forecasting of the ionospheric f0F2 in the Chinese region is real-ized.The results of the comparative analysis of the model show that:The forecasting errors for low-lati-tude stations were significantly higher than those for mid-latitude stations.The BiLSTM-Attention mod-el demonstrated superior performance,followed by the Long Short-Term Memory(LSTM)model.Com-pared to the International Reference Ionosphere(IRI)model,the BiLSTM-Attention model achieved a 44.2％reduction in Root Mean Square Error(RMSE),47％decrease in Mean Absolute Error(MAE),and 21.3％improvement in the Coefficient of Determination(R2).During geomagnetic storms,the BiLSTM-Attention model successfully captured the negative storm effects(characterized by f0F2 depletion)in China's regional ionosphere,showing excellent consistency with observational data.However,even when operating in storm mode,the IRI model still exhibited noticeable deviations between predicted and observed f0F2 values.As the forecasting window extended from 1 hour to 24 hours,the model errors showed a systematic increasing trend:RMSE rose from 0.99 MHz to 2.05 MHz,MAE increased from 0.69 MHz to 1.57 MHz,while R2 decreased from 0.93 to 0.75.Relevant research provides high-precision iono-spheric parameter forecasting support for space weather warning and short-wave communication system optimization.
Driven by the continuous progress in lunar exploration,teleoperated robotic arms require highly safe,accurate,and transparent control strategies to handle uncertain and unstructured environ-ments during lunar base construction.Humanoid variable impedance control ensures both safe environ-mental interaction and high-precision tracking,providing a robust solution for human-robot collabora-tion.This study investigates a teleoperation strategy that maps human impedance parameters onto a re-mote robotic arm to meet the interactive demands of lunar tasks.By integrating four-channel surface ElectroMyoGraphy(sEMG)signals with an upper limb mechanics model(built upon Hill's model and kinematics),a real-time identification system for human end-effector stiffness is established.Unlike con-ventional methods,this strategy incorporates personalized physical parameters to enhance the generaliza-tion of humanoid impedance control.Furthermore,force and visual feedback are utilized to improve in-formation transparency and leverage natural neural reflexes for adaptive impedance adjustment.Finally,experimental results on a lunar truss assembly platform demonstrate that the proposed humanoid vari-able impedance control significantly outperforms traditional teleoperation schemes.
The Chang'E-7 mission carries a Lunar Penetrating Radar(LPR)for investigating lunar shallow subsurface structures.To ensure the validity of the acquired data and improve the accuracy and consistency of its interpretation,this study presents a comprehensive calibration framework suitable for space-grade penetrating radar systems,incorporating full-system gain calibration and system transfer function calibration,among others.Applying this methodology,the lunar radar system was rigorously calibrated,clarifying the optimal parameter configuration for its in-orbit operation.Under this parame-ter setting,all performance metrics of the radar system meet the design requirements:the system gains of the Low-Frequency(LF)and High-Frequency(HF)channels are 171.02 dB and 169.70 dB,respective-ly,fulfilling the detection depth requirements of 400 m and 40 m.The acquired Time-Varying Gain(TVG)curve and system transfer function,validated through simulated lunar regolith experiments,can provide effective calibration baselines for scientific data obtained during lunar surface exploration.This calibration scheme can serve as a technical reference for the calibration of radar systems in future deep-space exploration missions.
The magnetic fluxgate sensor exhibits a significant temperature effect in its practical appli-cations.This paper presents an in-depth analysis of the working principles of both open-loop and closed-loop measurement circuits commonly used with magnetic fluxgate sensors.Based on this theoretical foundation,the study focuses on how the sensor's intrinsic characteristics vary with temperature under open-loop conditions.The objective is to provide experimental evidence that can guide the design and optimization of temperature drift suppression techniques in closed-loop configurations.By building upon the fundamental operational principles of the magnetic fluxgate sensor,the paper derives and compares the circuit transfer functions for both open-loop and closed-loop measurement systems.It is demonstra-ted that the error sources present in open-loop measurements are more directly reflective of the sensor's own performance characteristics,as they are not masked by feedback mechanisms inherent in closed-loop designs.To achieve accurate and reliable open-loop signal detection,a dual-operational amplifier(dual-op-amp)bandpass filter was employed to isolate the second harmonic signal,followed by phase-locked amplification to precisely measure both the amplitude and phase of the open-loop output.Performance temperature tests were designed based on the distinct behaviors of different sensor parameters under thermal variation.Experimental results obtained over a temperature range from-40℃to+80℃show that the zero-point drift of the magnetic fluxgate sensor remains within±0.5 nT,while the phase shift reaches up to 60°.Additionally,the open-loop gain varies by approximately±5％,and the noise level fluctuates between 4～7 pT·Hz1/2 at 1 Hz.Although the signal phase is the only parameter that under-goes a substantial change in open-loop measurements,the phase-sensitive demodulation mechanism in closed-loop systems is highly responsive to such variations.Consequently,the observed phase drift has been experimentally verified to result in significant zero-point drift in closed-loop measurements.
Currently,there are relatively few spaceborne methods for detecting near-space atmospher-ic wind fields,and the Fabry-Perot Interferometer(FPI)is one of the more important and widely used detection techniques.To address the gap in China's space-based FPI wind sensing capabilities,the Na-tional Space Science Center developed a spaceborne FPI wind interferometer.This paper mainly intro-duces this instrument's optical design,structural design,thermal control design,optical simulation,and result analysis.First,the optical design is discussed based on the wideband detection requirements,and the imaging system's image quality is evaluated.Then,based on optical simulation data,wind speed in-version and accuracy analysis of the spaceborne FPI instrument are conducted.The wind speed errors at the 557.7 nm and 762.0 nm bands are-1.722 m·s-1 and-2.3672 m·s-1,respectively,indicating that the spaceborne instrument design meets the wind measurement requirements.Then,the key points of the in-strument's structural design and the thermal control solution for the imaging part are presented,along with a translational filter switching device driven by a trapezoidal lead screw and a micro gear stepping motor or micro linear motor.The paper also explores the relationship between the temperature control accuracy of the instrument's core components(the etalon)and wind measurement errors.A combined active and passive design is adopted to minimize the impact of temperature fluctuations on the results,which is verified with simulation results.
The lunar pole's water ice is essential for understanding the Moon's evolution and building future lunar research station.Nevertheless,existing orbital remote-sensing missions and returned sam-ples remain insufficient to resolve the key unknowns of polar water,including its occurrence modes(e.g.,adsorbed water/hydroxyl,pore-filling ice,or ice-cemented regolith),its abundance and vertical variabili-ty,and its potential origin and evolutionary pathways.To address this gap,the Chang'E-7 mini-flying probe will carry the Lunar soil Water molecule Analyser(LUWA)to conduct in-situ detection of water ice at the permanently shadowed region for the first time.This paper describes the compositional struc-ture of LUWA and the detection approach,comprising drilling,sampling,sealing,heating and analysis.We detail the calibration parameters,apparatus,and procedures for its three core analytical modules:the Tunable Diode Laser Absorption Spectrometer(TDLAS),the Time-of-Flight Mass Spectrometer(TOF-MS),and the Differential optical Absorption Spectrometer(DAS).The operational chain is de-signed to release water through thermal extraction,quantify water content with high sensitivity across a wide dynamic range,and enable the determination of D/H isotopic signatures.A systematic ground cali-bration methodology and a unified calibration framework are established for three functional modules dedicated to water measurement.The framework defines calibration objectives,procedures,and trace-ability pathways to characterize module response functions,assess background and temperature-depen-dent effects,verify detection limits and linearity,and evaluate accuracy and repeatability,thereby sup-porting robust conversion from raw observables to calibrated water-content and isotope products in flight.In parallel,a dedicated lunar in-situ exploration test platform is developed to replicate LUWA's full operational workflow using lunar regolith simulants,including drilling,sampling,sealing,heating,and analysis.Integrated tests validate key performance metrics and the measurement workflow,provid-ing crucial technical support for interpreting Chang'E-7 LUWA data and for assessing the abundance and occurrence of water ice in lunar soil within PSRs.
The bidirectional Medium-Energy Proton Detector(MEPD)onboard the lunar surface exploration subsystem of the Chang'E-7 lander represents the first-ever implementation of dual-direction medium-energy proton measurements on the Moon.It is capable of providing spectral data of upward-and downward-directed medium-energy protons in the range of 0.03～30 MeV,offering crucial support for modeling the lunar particle radiation environment and for radiation protection in future crewed lunar missions.The unique challenges of ground calibration for the MEPD were addressed in this study.An electron accelerator was employed to achieve proton-equivalent energy calibration,while the full energy range was validated by analyzing the deposited energy of penetrating high-energy protons.In ad-dition,the suppression capability against electron contamination was quantitatively evaluated through a combined approach of accelerator experiments and numerical simulations.The results show that the detector's energy calibration deviation is better than 3%,its electron-rejection efficiency exceeds 94%for energies at or below 1.4 MeV,and the average geometric factors of the upward-and downward-facing detectors are 0.053 cm-2·sr-1 and 0.3041 cm-2·sr-1,respectively.These calibration results provide a reliable foundation for in-orbit data inversion.Furthermore,the established calibration and simulation framework offers valuable reference for the future calibration of lunar and deep-space charged-particle detectors.
Accurate observation of sea surface wind fields is essential for tropical cyclone forecasting and meteorological hazard mitigation.The HY-2 series microwave scatterometer continuously measures Ku-band ocean surface winds.However,its current wind speed retrieval algorithm struggles in high wind conditions and systematically underestimates speeds during extreme events such as typhoons.To ad-dress this bias,this study utilized the HY-2 wind speed data of nine tropical cyclones between 2021 and 2022 as the data source.The Stepped Frequency Microwave Radiometer(SFMR)wind speed measure-ments served as the ground truth.A modeling dataset was constructed by resampling the SFMR refer-ence data to match the 25 km spatial resolution of the HY-2 scatterometer,followed by spatiotemporal matching within a two-hour time window.The matched dataset was then randomly divided into a train-ing set and a testing set at a 7∶3 ratio.Subsequently,the Broad Learning System(BLS)was employed to conduct the regression analysis and develop a high-wind-speed correction model.BLS employs a shal-low,flat architecture in which input features are expanded into"enhanced nodes",avoiding the deep stacks typical of conventional neural networks.This structure reduces computational cost and acceler-ates convergence while maintaining predictive performance.Validation results demonstrate that the cor-rected HY-2 wind speeds achieved a Root Mean Square Error(RMSE)of 4.47 m·s-1,representing a 35%improvement compared to the uncorrected data.For wind speeds exceeding 25 m·s-1,the corrected RMSE reached 6.76 m·s-1,marking significant enhancements over the original values of 13.27 m·s-1.Additionally,a comparative analysis using Typhoon Chanthu(in 2021)as a case study revealed that the corrected HY-2C maximum wind speed increased from 22.09 m·s-1 to 32.73 m·s-1,closely matching wind fields retrieved by Synthetic Aperture Radar(SAR).Further validation through wind speed profile comparisons confirmed the effectiveness of the proposed model.These results demonstrate that our correction framework markedly improves extreme-wind retrieval accuracy,yielding bias-corrected HY-2 products that are more reliable for applications,such as storm surge simulation and typhoon track forecasting.
In response to the performance impact of long cable signal transmission between the search coil and the preamplifier circuit,this paper establishes for the first time a circuit equivalent model of Search Coil-Cable-Preamplifier Circuit.Through simulation analysis and experimental verification,the influence of cable length on the frequency distribution of sensor noise is revealed.Theoretical analysis in-dicates that cable length has limited impact on sensor sensitivity,but significantly increases the noise level in the high-frequency band(>1 kHz).Based on a prototype search coil magnetometer with a tar-get specification of 10～1000 Hz bandwidth and 30 fT·Hz1/2(1 kHz)noise,the variation law of noise with cable length is validated.Experimental results show that as the cable length increases from 3 m to 39 m,the noise corner frequency shifts forward from 7.5 kHz to 2 kHz,while the high-frequency noise at 10 kHz increases by a factor of six.The study finds that an increase in cable length has a significant im-pact on the noise of inductive magnetometers,specifically manifested as a slight improvement in low-fre-quency noise and a sharp deterioration in high-frequency noise.Although cable length has a notable ef-fect on inductive magnetometers,its influence can be predicted and mitigated through theoretical model-ing incorporating cable parameters.This research provides critical parameter basis for the engineering implementation of search coil magnetometers in space exploration scenarios requiring long-cable applica-tions.
The lunar surface becomes charged under the influence of solar wind and sunlight,and the potential differences on the surface form an electric field environment of various scales,which is the main mechanism for material transfer on the lunar surface.The electric field probe of Chang'E-7 will,for the first time,conduct in-situ electric field detection on the lunar surface.This paper introduces the design and results of the physical verification test of the probe in plasma environment based on the qualifica-tion model of the electric field probe.The basic principle of the electric field probe is the plasma electric probe principle.By clamping the probe current at a specific value,the potential of the probe can be de-termined according to the plasma V-I characteristic curve.The potential difference between different probes is the potential difference formed by the electric field environment on the plasma environment.Whether the probe can measure the plasma V-I characteristic curve is the key to the success of the probe design.With the help of a ground low-energy plasma simulation device,this test was carried out,and fixed current drive and scanning current measurement were conducted.The test results show that the electric field probe of Chang'E-7 can correctly reflect the plasma environment inside the simulation device and obtain a stable V-I characteristic curve.This proves that the electric field probe can achieve the function of obtaining the plasma potential by driving the probe current when working on the lunar surface,and the physical characteristics of the probe have been fully verified through the test.
The Low-Energy Ion Analyzer(LEIA)and Low-Energy Electron Analyzer(LEEA),inte-gral components of the Chang'E-7 lander's lunar surface environment detection system,conduct in-situ measurements of low-energy charged particles(0.001～30 keV)to elucidate solar wind-regolith inter-action mechanisms,investigate microstructure evolution in the lunar near-surface plasma environment,and support space-environment assessment for future lunar research stations.Employing identical hemispherical electrostatic analyzers with asymmetric electrostatic deflectors,both analyzers achieve wide-field detection(90°×360° FOV),broad energy coverage,and voltage-controlled variable geometric factors.Ground calibration using standard plasma beam sources confirmed compliance with mission requirements:energy resolution<15%(ΔE/E),dynamic flux range spanning seven orders of magnitude,and angular resolution<15°×22.5°,collectively enabling comprehensive characterization of lunar surface plasma phenomena.
Due to the inherent limitations of current remote sensing techniques,the actual occurrence and accurate abundance of water ice in lunar regolith cannot be directly identified,making in-situ verifi-cation urgently necessary.The Chang'E-7 mission of China's Lunar Exploration Program plans to con-duct water ice detection at the lunar south pole,where an in-situ micro-sampling device mounted on the rover will perform quantitative collection of lunar regolith for the volatiles in-situ measurement instru-ment.However,the uncertainty of lunar surface conditions leads to considerable dispersion in sampling mass.Moreover,water ice sublimation loss caused by tool-soil temperature difference and mechanical in-teractions during sampling will further reduce the detection accuracy.To ensure the reliability of detec-tion data from the volatiles measurement instrument,this paper proposes calibration methods for sam-pling mass and water ice loss.Icy lunar regolith simulant is prepared via vapor deposition during sam-pling,and sampling mass calibration experiments are carried out using a self-developed calibration de-vice.Preliminary results show that sampling mass varies significantly with regolith particle size distribu-tion.Further research will be conducted on the physical mechanism of icy lunar regolith sampling under multi-factor coupling conditions.This study aims to provide a high-confidence physical response parame-ter spectrum for accurate interpretation and scientific analysis of Chang'E-7 in-orbit data.
The ocean surface dynamic parameters reflect important air-sea interaction processes,such as the material and energy balance,and climate change.Under spaceborne measurement conditions,it is necessary to study the echo Doppler spectrum characteristics formed by the high operating speed of the satellite in conjunction with the sea surface dynamic parameters.In this paper,a time-varying dynamic sea surface model is established via the existing linear random superposition theory to simulate ocean surfaces.Based on the satellite parameters defined by the Ocean Surface Current multiscale Observation Mission(OSCOM),this work derives echo Doppler spectra involving different wind parameter effects un-der medium-incidence-angle Bragg scattering conditions.As wind speed increases,the sea surface rough-ness and root mean square height increase accordingly,resulting in the stronger backscatter modulation,and the echo Doppler shift increases significantly.When observed along the track,the echo Doppler cen-troid of the Doppler spectrum with wind direction is slightly asymmetric at the downwind and upwind,and reaches a minimum at 90° wind direction.The analysis results of the wind fetch show that when the wind speed is 10 m·s-1 and the length of wind fetch increases from a-10 km-developing wave to a fully-developed wave,the velocity of the sea surface increases,and the tilt modulation of the long wave increases,resulting in the Doppler shift increases,and the estimated Doppler centroid difference is 0.56 m·s-1.Finally,this study considers the contribution of breaking waves to the backscatter and analyzes the influence of both the Doppler centroid and velocity estimation.Analysis of echo Doppler spectrum under the condition of wave breaking shows that when the wind speed is 10 m·s-1 and the observation azimuth is the same as the wind direction,the Doppler centroid offset is about 71.4 Hz,re-sulting in a deviation of about 0.3 m·s-1 for the radial velocity estimation compared with the case with-out considering the breaking waves.
Equatorial Plasma Bubbles(EPBs)are large-scale depletion structures characterized by sig-nificantly reduced electron density,which frequently emerge in the low-latitude ionosphere during post-sunset hours.These dynamic plasma irregularities play a crucial role in space weather phenomena,as their evolution can induce severe amplitude and phase scintillations in radio signals,leading to disrup-tions in satellite communications,global navigation systems,and radar operations.Given their substan-tial impact on technological systems,accurate prediction of EPB evolution has become a critical chal-lenge in both space physics research and operational space weather forecasting.To address this chal-lenge,this study introduces a novel data-driven approach for EPB evolution prediction by leveraging the SimVP(Simpler yet Better Video Prediction)framework,an advanced deep learning architecture de-signed for spatiotemporal sequence forecasting.The proposed model learns the complex nonlinear dynam-ics of EPB structures from historical airglow image sequences,capturing both their morphological trans-formations and drift patterns.Through extensive experimentation,we systematically evaluate the influ-ence of key parameters—including time resolution,input/output sequence length,and environmental noise—on prediction performance.Our findings demonstrate that an optimal configuration with a 3 min temporal resolution and a 6-frame input/output structure achieves superior predictive accuracy,as evi-denced by high Structural Similarity(SSIM=0.989)and Peak Signal-to-Noise Ratio(PSNR=34.704)metrics.Further analysis reveals that the spatial complexity of EPB structures,such as bifurcation events and irregular boundary deformations,significantly affects prediction fidelity,whereas the impact of light pollution—a common issue in ground-based airglow observations—is comparatively minor.The model proposed in this paper demonstrates robust cross-station applicability.Beyond forecasting,the model also exhibits potential for reconstructing corrupted airglow data,offering a computational solu-tion to enhance observational datasets affected by atmospheric or instrumental noise.This work not on-ly establishes a robust,machine learning-based tool for EPB evolution analysis but also contributes to the broader development of Artificial Intelligence(AI)applications in space weather modeling and iono-spheric research.
The temperature field during solidification has an important influence on the microstruc-ture and properties of the material.Due to the difference of heat convection in space and ground envi-ronment,natural convection driven by gravity plays an important role in heat transfer in ground envi-ronment.However,in space,the microgravity environment almost eliminates the influence of gravity-dominated natural convection,which will lead to certain differences in the heat transfer characteristics between space and ground,resulting in differences in the temperature field distribution in the material experimental furnace.As a result,the temperature field obtained on the ground is different from that in space under the same temperature control conditions,thus affecting the equivalence of experimental conditions between space and ground materials.The heat transfer characteristics obtained from ground experiments cannot be directly applied to space experiments.This mismatch has a major impact on the space materials experiments.In order to obtain the heat transfer characteristics under microgravity conditions,a three-dimensional numerical model of heat transfer in the high temperature material experi-mental rack of the space station is established.In the modeling process,reasonable simplification is carried out according to the actual physical conditions,some minor heat transfer factors which have little influence on the overall temperature field are ignored.The temperature field simulation of the ground experiment and the space experiment was carried out respectively,and the temperature distribu-tion of the sample box was obtained.The temperature obtained by simulation was compared with the measured temperature.Through comprehensive analysis of the changes of heat transfer parameters in the space microgravity environment and the normal gravity environment on the ground,the heat transfer law similar to the space condition was obtained.The research results provide a new way to predict the space temperature field distribution based on the ground experiment results of high temperature mate-rials experiment rack and have important guiding significance for the future research of space materials.
