Recent advances of metal vacancies in energy and environmental catalysis:Synthesis,characterization,and roles

With the ongoing depletion of fossil fuels,energy and environmental issues have become increasingly critical,necessitating the search for effective solutions.Catalysis,being one of the hallmarks of modern industry,offers a promising avenue for researchers.However,the question of how to significantly enhance the performance of catalysts has gradually drawn the attention of scholars.Defect engineering,a commonly employed and effective approach to improve catalyst activity,has become a significant research focus in the catalysis field in recent years.Nonmetal vacancies have received extensive attention due to their simple form.Consequently,exploration of metal vacancies has remained stagnant for a considerable period,resulting in a scarcity of comprehensive reviews on this topic.Therefore,based on the latest research findings,this paper summarizes and consolidates the construction strategies for metal vacancies,characterization techniques,and their roles in typical energy and environmental catalytic reactions.Additionally,it outlines potential challenges in the future,aiming to provide valuable references for researchers interested in investigating metal vacancies.

Characterization of Physico-Chemical Changes of Lignin Obtained under Different Conditions of Enzymatic Hydrolysis on an Industrial Scale

Research-based on lignin as a bioproduct has grown due to its high availability,reactivity,physicochemical sta-bility,and abundance of different aromatic units.Lignin consists of various functional groups,which can react in various chemical reactions and serve as a raw material in various processes to obtain multiple products.These characteristics make lignin suitable for synthesizing products from natural raw materials,replacing fossil ones.Due to a high aromatic variety and complex structural arrangement,lignin isolation and fractionation are still challenging.The aim and novelty of this work was the modification of severity and enzymatic hydrolysis proce-dure on an industrial pre-treatment to improve by-products of birch processing as a raw material for the potential production of different products.Lignin from birch wood enzymatic hydrolysis was obtained and marked accord-ingly:HS(high severity),MS(medium severity),and LS(low severity)lignin.Samples were characterized by ash content,analytical pyrolysis,solubility,and viscosity.HS lignin was characterized by a relatively high carbohy-drate content(16%)and lower lignin content(77%).Meanwhile,LS lignin showed increased lignin content(83%)and reduced carbohydrate content(9%).It can be concluded that the delignification process greatly influ-ences the properties of the obtained lignin.HS lignin resulted in a lower polydispersity index(PDI)and more condensed structure,while LS lignin showed a higher PDI but a lower content of carbohydrates.Therefore,look-ing for a golden middle way is necessary whilefinding the conditions according to the usefield.

Multiparameter generalized universal characters and multiparameter generalized B-type universal characters

We construct the quantum fields presentation of the generalized universal character and the generalized B-type universal character,and by acting the quantum fields presentations to the constant 1,the generating functions are derived.Furthermore,we introduce two integrable systems known as the generalized UC(GUC)hierarchy and the generalized Btype UC(GBUC)hierarchy satisfied by the generalized universal character and the generalized B-type universal character,respectively.Based on infinite sequences of complex numbers,we further establish the multiparameter generalized universal character and the multiparameter generalized B-type universal character,which have been proved to be solutions of the GUC hierarchy and the GBUC hierarchy,respectively.

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.

Thermomechanical Characterization of Three Soils of Abeche in Chad

The study carried out concerns the valorization of agricultural waste for the development of biosourced materials that can be used as insulation in homes. This article is devoted to the influence of gum arabic on the mechanical and thermal properties of clay soils in the town of Abéché. The mechanical tests were carried out using the CBR press equipped with two devices (bending device and compression device). Thermal property such as thermal conductivity was determined by the hot wire method and thermal resistance was derived by calculation. Thus, the tests were carried out on test pieces made from a mixture of clay and gum arabic in solution. The experimental program includes seven formulations (0%, 2%, 4%, 6%, 8%, 10% and 12%). The results obtained showed that the best flexural and compressive strengths are obtained by using gum arabic with a rate of 8% and a maximum stress of 4.3 MPa. In addition, the thermal results also showed that the thermal conductivity decreases when the percentage of gum arabic increases, which makes it possible to increase the thermal resistance, thus confirming the capacity of gum arabic to provide thermal insulation.

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.

Enhancing constitutive description and workability characterization of Mg alloy during hot deformation using machine learning-based Arrhenius-type model

Hot deformation is a commonly employed processing technique to enhance the ductility and workability of Mg alloy.However,the hot deformation of Mg alloy is highly sensitive to factors such as temperature,strain rate,and strain,leading to complex flow behavior and an exceptionally narrow processing window for Mg alloy.To overcome the shortcomings of the conventional Arrhenius-type(AT)model,this study developed machine learning-based Arrhenius-type(ML-AT)models by combining the genetic algorithm(GA),particle swarm optimization(PSO),and artificial neural network(ANN).Results indicated that when describing the flow behavior of the AQ80 alloy,the PSO-ANN-AT model demonstrates the most prominent prediction accuracy and generalization ability among all ML-AT and AT models.Moreover,an activation energy-processing(AEP)map was established using the reconstructed flow stress and activation energy fields based on the PSO-ANN-AT model.Experimental validations revealed that this AEP map exhibits superior predictive capability for microstructure evolution compared to the one established by the traditional interpolation methods,ultimately contributing to the precise determination of the optimum processing window.These findings provide fresh insights into the accurate constitutive description and workability characterization of Mg alloy during hot deformation.

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.

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.

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.

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.