Properties and Characteristics of Regolith-Based Materials for Extraterrestrial Construction

The construction of extraterrestrial bases has become a new goal in the active exploration of deep space.Among the construction techniques,in situ resource-based construction is one of the most promising because of its good sustainability and acceptable economic cost,triggering the development of various types of extraterrestrial construction materials.A comprehensive survey and comparison of materials from the perspective of performance was conducted to provide suggestions for material selection and optimization.Thirteen types of typical construction materials are discussed in terms of their reliability and applicability in extreme extraterrestrial environment.Mechanical,thermal and optical,and radiation-shielding properties are considered.The influencing factors and optimization methods for these properties are analyzed.From the perspective of material properties,the existing challenges lie in the comprehensive,long-term,and real characterization of regolith-based construction materials.Correspondingly,the suggested future directions include the application of high-throughput characterization methods,accelerated durability tests,and conducting extraterrestrial experiments.

Characterization, preparation, and reuse of metallic powders for laser powder bed fusion: a review

Laser powder bed fusion(L-PBF) has attracted significant attention in both the industry and academic fields since its inception, providing unprecedented advantages to fabricate complex-shaped metallic components. The printing quality and performance of L-PBF alloys are infuenced by numerous variables consisting of feedstock powders, manufacturing process,and post-treatment. As the starting materials, metallic powders play a critical role in infuencing the fabrication cost, printing consistency, and properties. Given their deterministic roles, the present review aims to retrospect the recent progress on metallic powders for L-PBF including characterization, preparation, and reuse. The powder characterization mainly serves for printing consistency while powder preparation and reuse are introduced to reduce the fabrication costs.Various powder characterization and preparation methods are presented in the beginning by analyzing the measurement principles, advantages, and limitations. Subsequently, the effect of powder reuse on the powder characteristics and mechanical performance of L-PBF parts is analyzed, focusing on steels, nickel-based superalloys, titanium and titanium alloys, and aluminum alloys. The evolution trends of powders and L-PBF parts vary depending on specific alloy systems, which makes the proposal of a unified reuse protocol infeasible. Finally,perspectives are presented to cater to the increased applications of L-PBF technologies for future investigations. The present state-of-the-art work can pave the way for the broad industrial applications of L-PBF by enhancing printing consistency and reducing the total costs from the perspective of powders.

Three novel umami peptides derived from the alcohol extract of the Pacific oyster(Crassostrea gigas):identification,characterizations and interactions with T1R1/T1R3 taste receptors

Oyster(Crassostrea gigas),the main ingredient of oyster sauce,has a strong umami taste.In this study,three potential umami peptides,FLNQDEEAR(FR-9),FNKEE(FE-5),and EEFLK(EK-5),were identified and screened from the alcoholic extracts of the oyster using nano-HPLC-MS/MS analysis,i Umami-Scoring Card Method(i Umami-SCM)database and molecular docking(MD).Sensory evaluation and electronic tongue analysis were further used to confirm their tastes.The threshold of the three peptides ranged from 0.38 to 0.55 mg/m L.MD with umami receptors T1R1/T1R3 indicated that the electrostatic interaction and hydrogen bond interaction were the main forces involved.Besides,the Phe592 and Gln853 of T1R3 were the primary docking site for MD and played an important role in umami intensity.Peptides with two Glu residues at the terminus had stronger umami,especially at the C-terminus.These results contribute to the understanding of umami peptides in oysters and the interaction mechanism between umami peptides and umami receptors.

Subsurface multi-physical characterization of mountain excavation and city construction in loess plateau with a fiber-optic sensing system

Mountain excavation and city construction(MECC)projects being launched in the Loess Plateau in China involve the creation of large-scale artificial land.Understanding the subsurface evolution characteristics of the artificial land is essential,yet challenging.Here,we use an improved fiber-optic monitoring system for its subsurface multi-physical characterization.The system enables us to gather spatiotemporal distribution of various parameters,including strata deformation,temperature,and moisture.Yan’an New District was selected as a case study to conduct refined in-situ monitoring through a 77 m-deep borehole and a 30 m-long trench.Findings reveal that the ground settlement involves both the deformation of the filling loess and the underlying intact loess.Notably,the filling loess exhibits a stronger creep capability compared to underlying intact loess.The deformation along the profile is unevenly distributed,with a positive correlation with soil moisture.Water accumulation has been observed at the interface between the filling loess and the underlying intact loess,leading to a significant deformation.Moreover,the temperature and moisture in the filling loess have reached a new equilibrium state,with their depths influenced by atmospheric conditions measuring at 31 m and 26 m,respectively.The refined investigation allows us to identify critical layers that matter the sustainable development of newly created urban areas,and provide improved insights into the evolution mechanisms of land creation.

Characterization of the structural details of residual austenite in the weld metal of a 9Cr1MoNbV welded rotor

The existence of residual austenite in weld metal plays an important role in determining the properties and dimensional accuracy of welded rotors. An effective corrosive agent and the metallographic etching process were developed to clearly reveal the characteristics of residual austenite in the weld metal of a 9Cr1MoNbV welded rotor. Moreover, the details of the distribution, shape, length, length-to-width ratio, and the content of residual austenite were systematically characterized using the Image-Pro Plus image analysis software. The results revealed that the area fraction of residual austenite was approximately 6.3% in the observed weld seam; the average area, length, and length-to-width ratio of dispersed residual austenite were quantitatively evaluated to be （5.5 ± 0.1）μm2, （5.0 ± 0.1）μm, and （2.2 ± 0.1）, re-spectively. The newly developed corrosive agent and etching method offer an appropriate approach to characterize residual austenite in the weld metal of welded rotors in detail.

Development of in situ characterization techniques in molecular beam epitaxy

Ex situ characterization techniques in molecular beam epitaxy(MBE)have inherent limitations,such as being prone to sample contamination and unstable surfaces during sample transfer from the MBE chamber.In recent years,the need for improved accuracy and reliability in measurement has driven the increasing adoption of in situ characterization techniques.These techniques,such as reflection high-energy electron diffraction,scanning tunneling microscopy,and X-ray photoelectron spectroscopy,allow direct observation of film growth processes in real time without exposing the sample to air,hence offering insights into the growth mechanisms of epitaxial films with controlled properties.By combining multiple in situ characterization techniques with MBE,researchers can better understand film growth processes,realizing novel materials with customized properties and extensive applications.This review aims to overview the benefits and achievements of in situ characterization techniques in MBE and their applications for material science research.In addition,through further analysis of these techniques regarding their challenges and potential solutions,particularly highlighting the assistance of machine learning to correlate in situ characterization with other material information,we hope to provide a guideline for future efforts in the development of novel monitoring and control schemes for MBE growth processes with improved material properties.

Genome-wide identification,characterization and functional prediction of the SRS gene family in sesame(Sesamum indicum L.)

Sesame(Sesamum indicum L.)is an ancient oilseed crop of the Pedaliaceae family with high oil content and potential health benefits.SHI RELATED SEQUENCE(SRS)proteins are the transcription factors(TFs)specific to plants that contain RING-like zinc finger domain and are associated with the regulation of several physiological and biochemical processes.They also play vital roles in plant growth and development such as root formation,leaf development,floral development,hormone biosynthesis,signal transduction,and biotic and abiotic stress responses.Nevertheless,the SRS gene family was not reported in sesame yet.In this study,identification,molecular characterization,phylogenetic relationship,cis-acting regulatory elements,protein-protein interaction,syntenic relationship,duplication events and expression pattern of SRS genes were analyzed in S.indicum.We identified total six SiSRS genes on seven different linkage groups in the S.indicum genome by comparing with the other species,including the model plant Arabidopsis thaliana.The SiSRS genes showed variation in their structure like2–5 exons and 1–4 introns.Like other species,SiSRS proteins also contained‘RING-like zinc finger'and‘LRP1'domains.Then,the SiSRS genes were clustered into subclasses via phylogenetic analysis with proteins of S.indicum,A.thaliana,and some other plant species.The cis-acting regulatory elements analysis revealed that the promoter region of SiSRS4(SIN_1011561)showed the highest 13 and 16 elements for light-and phytohormone-responses whereas,SiSRS1(SIN_1015187)showed the highest 15 elements for stress-response.The ABREs,or ABA-responsive elements,were found in a maximum of 8 copies in the SiSRS3(SIN 1009100).Moreover,the available RNA-seq based expression of SiSRS genes revealed variation in expression patterns between stress-treated and non-treated samples,especially in drought and salinity conditions in.S.indicum.Two SiSRS genes like SiSRS1(SIN_1015187)and SiSRS5(SIN_1021065),also exhibited variable expression patterns between control vs PEG-treated sesame root samples and three SiSRS genes,including SiSRS1(SIN_1015187),SiSRS2(SIN_1003328)and SiSRS5(SIN_1021065)were responsive to salinity treatments.The present outcomes will encourage more research into the gene expression and functionality analysis of SiSRS genes in S.indicum and other related species.

Detailed characterization of polycapillary focusing x-ray lenses by a charge-coupled device detector and a pinhole

A method to measure the detailed performance of polycapillary x-ray optics by a pinhole and charge coupled device(CCD)detector was proposed in this study.The pinhole was located between the x-ray source and the polycapillary x-ray optics to determine the illuminating region of the incident x-ray beam on the input side of the optics.The CCD detector placed downstream of the polycapillary x-ray optics ensured that the incident x-ray beam controlled by the pinhole irradiated a specific region of the input surface of the optics.The intensity of the output beam of the polycapillary x-ray optics was obtained from the far-field image of the output beam of the optics captured by CCD detector.As an application example,the focal spot size,gain in power density,transmission efficiency,and beam divergence of different parts of a polycapillary focusing x-ray lenses(PFXRL)were measured by a pinhole and CCD detector.Three pinholes with diameters of 500,1000,and 2000μm were used to adjust the diameter of the incident x-ray beam illuminating the PFXRL from 500μm to the entire surface of the input side of the PFXRL.The focal spot size of the PFXRL,gain in power density,transmission efficiency,and beam divergence ranged from 27.1μm to 34.6μm,400 to 3460,26.70%to 5.38%,and 16.8 mrad to 84.86 mrad,respectively.

Effect of Co on Solidification Characteristics and Microstructural Transformation of Non-equilibrium Solidified Cu-Ni Alloys

Non-equilibrium solidification structures of Cu55Ni45 and Cu55Ni43Co2 alloys were prepared by the molten glass purification cycle superheating method.The variation of the recalescence phenomenon with the degree of undercooling in the rapid solidification process was investigated using an infrared thermometer.The addition of the Co element affected the evolution of the recalescence phenomenon in Cu-Ni alloys.The images of the solid-liquid interface migration during the rapid solidification of supercooled melts were captured by using a high-speed camera.The solidification rate of Cu-Ni alloys,with the addition of Co elements,was explored.Finally,the grain refinement structure with low supercooling was characterised using electron backscatter diffraction(EBSD).The effect of Co on the microstructural evolution during nonequilibrium solidification of Cu-Ni alloys under conditions of small supercooling is investigated by comparing the microstructures of Cu55Ni45 and Cu55Ni43Co2 alloys.The experimental results show that the addition of a small amount of Co weakens the recalescence behaviour of the Cu55Ni45 alloy and significantly reduces the thermal strain in the rapid solidification phase.In the rapid solidification phase,the thermal strain is greatly reduced,and there is a significant increase in the characteristic undercooling degree.Furthermore,the addition of Co and the reduction of Cu not only result in a lower solidification rate of the alloy,but also contribute to the homogenisation of the grain size.

Instance Segmentation of Characters Recognized in Palmyrene Aramaic Inscriptions

This study presents a single-class and multi-class instance segmentation approach applied to ancient Palmyrene inscriptions,employing two state-of-the-art deep learning algorithms,namely YOLOv8 and Roboflow 3.0.The goal is to contribute to the preservation and understanding of historical texts,showcasing the potential of modern deep learning methods in archaeological research.Our research culminates in several key findings and scientific contributions.We comprehensively compare the performance of YOLOv8 and Roboflow 3.0 in the context of Palmyrene character segmentation—this comparative analysis mainly focuses on the strengths and weaknesses of each algorithm in this context.We also created and annotated an extensive dataset of Palmyrene inscriptions,a crucial resource for further research in the field.The dataset serves for training and evaluating the segmentation models.We employ comparative evaluation metrics to quantitatively assess the segmentation results,ensuring the reliability and reproducibility of our findings and we present custom visualization tools for predicted segmentation masks.Our study advances the state of the art in semi-automatic reading of Palmyrene inscriptions and establishes a benchmark for future research.The availability of the Palmyrene dataset and the insights into algorithm performance contribute to the broader understanding of historical text analysis.

Influences of polymorphism of packed particles on bulk characterizations in fluidization realm

The characterization of a particle ensemble(rather than a single particle) is of paramount significance to various particle technologies and has long been a fundamental subject in the fluidization realm. However, many of such bulk characterizations as loosely-packed density(ρbl), minimum fluidization velocity(Umf), sphericity(φ), discharge rate through orifice(q), angle of repose(β), and segregation index(S),were found to be poorly reproducible, making the reported results seldom comparable. Since these bulk characterizations started from the packed state of particles, such poor reproducibility was ascribed to the polymorphism of packed particles in this work. We observed that in the fluidized bed, the settled/packed state of particles varied monotonously with the settling rate(a) from complete fluidization to zero. This phenomenon confirmed the polymorphic characteristic of packed particles and further enabled us to systematically disclose/clarify its influences on the aforementioned bulk characterizations. Such influences could be comprehensively and intuitively reflected by the impacts induced by a. With the decrease of a, ρbl, φ and q first increased, then decreased, and finally leveled off while Umfand β showed an opposite trend. On the other hand, S first increased and then remained invariant. As per these findings and definitions of these bulk characterizations, benchmarks were indicated to unify the selection of settled state among future scholars and further make their outcomes become fairly comparable. Additionally, most packed states of the particle ensemble were proved to be metastable with their formation and behavior being identical to those of the amorphous state.

Preparation and characterization of pH-responsive metal-polyphenol structure coated nanoparticles

In this paper,tannic acid(TA)and Fe~(3+)were added to form a layer of metal-polyphenol network structure on the surface of the nanoparticles which were fabricated by zein and carbon quantum dots(CQDs)encapsulating phlorotannins(PTN).pH-Responsive nanoparticles were prepared successfully(zein-PTN-CQDs-Fe-~Ⅲ).Further,the formation of composite nanoparticles was confirmed by a series of characterization methods.The zeta-potential and Fourier transform infrared spectroscopy data proved that electrostatic interaction and hydrogen bonding are dominant forces to form nanoparticles.The encapsulation efficiency(EE)revealed that metal-polyphenol network structure could improve the EE of PTN.Thermogravimetric analysis and differential scanning calorimetry experiment indicated the thermal stability of zein-PTN-CQDs-Fe~Ⅲnanoparticles increased because of metal-polyphenol network structure.The pH-responsive nanoparticles greatly increased the release rate of active substances and achieved targeted release.

Test for the deep:magnetic loading characterization of elastomers under extreme hydrostatic pressures

Soft robot incarnates its unique advantages in deep-sea exploration,but grapples with high hydrostatic pressure’s unpredictable impact on its mechanical performances.In our previous work,a self-powered soft robot showed excellent work performance in the Mariana Trench at a depth of 11000 m,yet experienced notable degradation in deforming capability.Here,we propose a magnetic loading method for characterizing elastomer’s mechanical properties under extremely high hydrostatic pressure of up to 120 MPa.This method facilitates remote loading and enables in-situ observation,so that the dimensions and deformation at high hydrostatic pressure are obtained and used for calculations.The results reveal that the Young’s modulus of Polydimethylsiloxane(PDMS)monotonously increases with pressure.It is found that the relative increase in Young’s modulus is determined by its initial value,which is 8% for an initial Young’s modulus of 2200 kPa and 38% for 660 kPa.The relation between initial Young’s modulus and relevant increase can be fitted by an exponential function.The bulk modulus of PDMS is about 1.4 GPa at 20℃ and is barely affected by hydrostatic pressure.The method can quantify alterations in the mechanical properties of elastomers induced by hydrostatic pressure,and provide guidance for the design of soft robots which serve in extreme pressure environment.

Mechanical heterogeneity characterization of coal materials based on nano-indentation experiments

To investigate the complex macro-mechanical properties of coal from a micro-mechanical perspective,we have conducted a series of micro-mechanical experiments on coal using a nano-indentation instrument.These experiments were conducted under both dynamic and static loading conditions,allowing us to gather the micro-mechanical parameters of coal for further analysis of its micro-mechanical heterogeneity using the box counting statistical method and the Weibull model.The research findings indicate that the load–displacement curves of the coal mass under the two different loading modes exhibit noticeable discreteness.This can be attributed to the stress concentration phenomenon caused by variations in the mechanical properties of the micro-units during the loading process of the coal mass.Consequently,there are significant fluctuations in the micro-mechanical parameters of the coal mass.Moreover,the mechanical heterogeneity of the coal at the nanoscale was confirmed based on the calculation results of the standard deviation coefficient and Weibull modulus of the coal body’s micromechanical parameters.These results reveal the influence of microstructural defects and minerals on the uniformity of the stress field distribution within the loaded coal body,as well as on the ductility characteristics of the micro-defect structure.Furthermore,there is a pronounced heterogeneity in the micromechanical parameters.Furthermore,we have established a relationship between the macro and micro elastic modulus of coal by applying the Mori-Tanaka homogenization method.This relationship holds great significance for revealing the micro-mechanical failure mechanism of coal.

Machine learning in metal-ion battery research: Advancing material prediction, characterization, and status evaluation

Metal-ion batteries(MIBs),including alkali metal-ion(Li^(+),Na^(+),and K^(3)),multi-valent metal-ion(Zn^(2+),Mg^(2+),and Al^(3+)),metal-air,and metal-sulfur batteries,play an indispensable role in electrochemical energy storage.However,the performance of MIBs is significantly influenced by numerous variables,resulting in multi-dimensional and long-term challenges in the field of battery research and performance enhancement.Machine learning(ML),with its capability to solve intricate tasks and perform robust data processing,is now catalyzing a revolutionary transformation in the development of MIB materials and devices.In this review,we summarize the utilization of ML algorithms that have expedited research on MIBs over the past five years.We present an extensive overview of existing algorithms,elucidating their details,advantages,and limitations in various applications,which encompass electrode screening,material property prediction,electrolyte formulation design,electrode material characterization,manufacturing parameter optimization,and real-time battery status monitoring.Finally,we propose potential solutions and future directions for the application of ML in advancing MIB development.

Optimised CNN Architectures for Handwritten Arabic Character Recognition

Handwritten character recognition is considered challenging compared with machine-printed characters due to the different human writing styles.Arabic is morphologically rich,and its characters have a high similarity.The Arabic language includes 28 characters.Each character has up to four shapes according to its location in the word(at the beginning,middle,end,and isolated).This paper proposed 12 CNN architectures for recognizing handwritten Arabic characters.The proposed architectures were derived from the popular CNN architectures,such as VGG,ResNet,and Inception,to make them applicable to recognizing character-size images.The experimental results on three well-known datasets showed that the proposed architectures significantly enhanced the recognition rate compared to the baseline models.The experiments showed that data augmentation improved the models’accuracies on all tested datasets.The proposed model outperformed most of the existing approaches.The best achieved results were 93.05%,98.30%,and 96.88%on the HIJJA,AHCD,and AIA9K datasets.

Recent progress about transmission electron microscopy characterizations on lithium-ion batteries

With the rapid development of portable electronics,new energy vehicles,and smart grids,ion batteries are becoming one of the most widely used energy storage devices,while the safety concern of ion batteries has always been an urgent problem to be solved.To develop a safety-guaranteed battery,the characterization of the internal structure is indispensable,where electron microscopy plays a crucial role.Based on this,this paper summarizes the application of transmission electron microscopy(TEM)in battery safety,further concludes and analyzes the aspects of dendrite growth and solid electrolyte interface(SEI)formation that affect the safety of ion batteries,and emphasizes the importance of electron microscopy in battery safety research and the potential of these techniques to promote the future development of this field.These advanced electron microscopy techniques and their prospects are also discussed.

Characterization and identification towards dynamic-based electrical modeling of lithium-ion batteries

Lithium-ion batteries are widely recognized as a crucial enabling technology for the advancement of electric vehicles and energy storage systems in the grid.The design of battery state estimation and control algorithms in battery management systems is usually based on battery models,which interpret crucial battery dynamics through the utilization of mathematical functions.Therefore,the investigation of battery dynamics with the purpose of battery system identification has garnered considerable attention in the realm of battery research.Characterization methods in terms of linear and nonlinear response of lithium-ion batteries have emerged as a prominent area of study in this field.This review has undertaken an analysis and discussion of characterization methods,with a particular focus on the motivation of battery system identification.Specifically,this work encompasses the incorporation of frequency domain nonlinear characterization methods and dynamics-based battery electrical models.The aim of this study is to establish a connection between the characterization and identification of battery systems for researchers and engineers specialized in the field of batteries,with the intention of promoting the advancement of efficient battery technology for real-world applications.

A review of in-situ high-temperature characterizations for understanding the processes in metallurgical engineering

For the rational manipulation of the production quality of high-temperature metallurgical engineering,there are many challenges in understanding the processes involved because of the black box chemical/electrochemical reactors.To overcome this issue,various in-situ characterization methods have been recently developed to analyze the interactions between the composition,microstructure,and solid-liquid interface of high-temperature electrochemical electrodes and molten salts.In this review,recent progress of in-situ hightemperature characterization techniques is discussed to summarize the advances in understanding the processes in metallurgical engineering.In-situ high-temperature technologies and analytical methods mainly include synchrotron X-ray diffraction(s-XRD),laser scanning confocal microscopy,and X-ray computed microtomography(X-rayμ-CT),which are important platforms for analyzing the structure and morphology of the electrodes to reveal the complexity and variability of their interfaces.In addition,laser-induced breakdown spectroscopy,high-temperature Raman spectroscopy,and ultraviolet-visible absorption spectroscopy provide microscale characterizations of the composition and structure of molten salts.More importantly,the combination of X-rayμ-CT and s-XRD techniques enables the investigation of the chemical reaction mechanisms at the two-phase interface.Therefore,these in-situ methods are essential for analyzing the chemical/electrochemical kinetics of high-temperature reaction processes and establishing the theoretical principles for the efficient and stable operation of chemical/electrochemical metallurgical processes.

Bio-soft matter derived from traditional Chinese medicine:Characterizations of hierarchical structure,assembly mechanism,and beyond

Structural and functional explorations on bio-soft matter such as micelles,vesicles,nanoparticles,aggregates or polymers derived from traditional Chinese medicine(TCM)has emerged as a new topic in the field of TCM.The discovery of such cross-scaled bio-soft matter may provide a unique perspective for unraveling the new effective material basis of TCM as well as developing innovative medicine and biomaterials.Despite the rapid rise of TCM-derived bio-soft matter,their hierarchical structure and assembly mechanism must be unambiguously probed for a further in-depth understanding of their pharmacological activity.In this review,the current emerged TCM-derived bio-soft matter assembled from either small molecules or macromolecules is introduced,and particularly the unambiguous elucidation of their hierarchical structure and assembly mechanism with combined electron microscopic and spectroscopic techniques is depicted.The pros and cons of each technique are also discussed.The future challenges and perspective of TCM-derived bio-soft matter are outlined,particularly the requirement for their precise in situ structural determination is highlighted.