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.

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.

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.

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.

Characterization of alpine meadow surface crack and its correlation with root-soil properties

Quantifying surface cracks in alpine meadows is a prerequisite and a key aspect in the study of grassland crack development.Crack characterization indices are crucial for the quantitative characterization of complex cracks,serving as vital factors in assessing the degree of cracking and the development morphology.So far,research on evaluating the degree of grassland degradation through crack characterization indices is rare,especially the quantitative analysis of the development of surface cracks in alpine meadows is relatively scarce.Therefore,based on the phenomenon of surface cracking during the degradation of alpine meadows in some regions of the Qinghai-Tibet Plateau,we selected the alpine meadow in the Huangcheng Mongolian Township,Menyuan Hui Autonomous County,Qinghai Province,China as the study area,used unmanned aerial vehicle(UAV)sensing technology to acquire low-altitude images of alpine meadow surface cracks at different degrees of degradation(light,medium,and heavy degradation),and analyzed the representative metrics characterizing the degree of crack development by interpreting the crack length,length density,branch angle,and burrow(rat hole)distribution density and combining them with in situ crack width and depth measurements.Finally,the correlations between the crack characterization indices and the soil and root parameters of sample plots at different degrees of degradation in the study area were analyzed using the grey relation analysis.The results revealed that with the increase of degradation,the physical and chemical properties of soil and the mechanical properties of root-soil composite changed significantly,the vegetation coverage reduced,and the root system aggregated in the surface layer of alpine meadow.As the degree of degradation increased,the fracture morphology developed from"linear"to"dendritic",and eventually to a complex and irregular"polygonal"pattern.The crack length,width,depth,and length density were identified as the crack characterization indices via analysis of variance.The results of grey relation analysis also revealed that the crack length,width,depth,and length density were all highly correlated with root length density,and as the degradation of alpine meadows intensified,the underground biomass increased dramatically,forming a dense layer of grass felt,which has a significant impact on the formation and expansion of cracks.

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.

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.

Roughness characterization and shearing dislocation failure for rock-backfill interface

Shearing dislocation is a common failure type for rock–backfill interfaces because of backfill sedimentation and rock strata movement in backfill mining goaf.This paper designed a test method for rock–backfill shearing dislocation.Using digital image techno-logy and three-dimensional(3D)laser morphology scanning techniques,a set of 3D models with rough joint surfaces was established.Further,the mechanical behavior of rock–backfill shearing dislocation was investigated using a direct shear test.The effects of interface roughness on the shear–displacement curve and failure characteristics of rock–backfill specimens were considered.The 3D fractal dimen-sion,profile line joint roughness coefficient(JRC),profile line two-dimensional fractal dimension,and the surface curvature of the frac-tures were obtained.The correlation characterization of surface roughness was then analyzed,and the shear strength could be measured and calculated using JRC.The results showed the following:there were three failure threshold value points in rock–backfill shearing dis-location:30%–50%displacement before the peak,70%–90%displacement before the peak,and 100%displacement before the peak to post-peak,which could be a sign for rock–backfill shearing dislocation failure.The surface JRC could be used to judge the rock–backfill shearing dislocation failure,including post-peak sliding,uniform variations,and gradient change,corresponding to rock–backfill disloca-tion failure on the field site.The research reveals the damage mechanism for rock–backfill complexes based on the free joint surface,fills the gap of existing shearing theoretical systems for isomerism complexes,and provides a theoretical basis for the prevention and control of possible disasters in backfill mining.

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.

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.

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.

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.

Structural characterization of three acidic polysaccharides from Opuntia dillenii Haw.fruits and their protective effect against hydrogen peroxide-induced oxidative stress in Huh-7 cells

Three novel acidic polysaccharide fractions(OFPP-1,OFPP-2,OFPP-3)with different m olecular weights(803.7,555.1 and 414.5 k Da)were isolated from the peeled Opuntia dillenii Haw.fruits by alkali-extraction,graded alcohol precipitation and column chromatography.Structural analysis indicated that OFPPs were pectic polysaccharides consisting of rhamnose,arabinose and galactose residues.The backbone of OFPP-1 consisted of a repeating unit→6-α-D-Galp A-(1→2)-α-L-Rhap-(1→with T-α-D-Galp A-(1→6)-α-D-Galp A-(1→4)-α-D-Glcp-(1→,T-β-D-Xylp-(1→6)-α-D-Galp A-(1→4)-α-D-Glcp-(1→or T-α-D-Galp A-(1→3)-α-L-Araf-(1→as the side chains.The backbone of OFPP-2 consisted of a disaccharide repeating unit→2)-α-L-Rhap-(1→4)-β-D-Galp A-(1→with T-β-L-Araf-(1→as the branches substituted at the O-4 position of→2,4)-α-LRhap-(1→.Whereas the backbone of OFPP-3 was→2,4)-α-L-Rhap-(1→2)-α-L-Rhap-(1→3)-β-L-Araf-(1→or→2,4)-α-L-Rhap-(1→2)-α-L-Rhap-(1→4)-β-D-Galp A-(1→,which was branched at the O-4 position of→2,4)-α-L-Rhap-(1→.Moreover,these three polysaccharide fractions could protect Huh-7 cells against H2O2-induced oxidative stress to different extents by decreasing the MDA content and increasing the SOD,CAT,GSH-Px activities and the GSH level in the Huh-7 cells.These results suggest that OFPPs have the potential to be used as natural antioxidants.

Structural characterization and anti-inflammatory activities of novel polysaccharides obtained from Pleurotus eryngii

Natural polysaccharides named PEP-0.1-1,PEP-0-1 and PEP-0-2 from edible mushroom species Pleurotus eryngii were obtained in the present study.Results showed that molecular weights of these polysaccharides were 3235,2041 and 23933 Da,respectively.Further,structural characterization revealed that PEP-0.1-1 had a→4-α-D-Glcp-1→backbone and contained→4)-α-D-Glcp and→4)-β-D-Glcp reducing end groups.PEP-0-1 backbone contained→4-α-D-Glcp-1→and→6-α-3-O-Me-D-Galp-1→,and the side chains containedα-D-Glcp,β-D-Manp-1→andα-D-Glcp-3→.However,PEP-0-2 backbone consisted of→4-α-DGlcp-1→and→6-α-3-O-Me-D-Galp-(1→6)-α-D-Galp-1→while the side chains containedα-D-Glcp andβ-D-Manp-1→.Biological activity analysis was then carried out and found that all these polysaccharides could significantly suppress the relative mRNA expression of toll-like receptor 4,nitric oxide(NO),tumor necrosis factor-α,interleukin(IL)-1βand IL-6 in lipopolysaccharide(LPS)-induced inflammation of RAW264.7 cells,as well as the over secretion of the above cell cytokines.Moreover,Western blotting analysis revealed that all these purified fractions displayed significant inhibition effects on the expression of c-Jun N-terminal kinases protein induced by LPS in mitogen activated protein kinase pathway,along with the relieving on the inhibition effect of LPS on IκB-αprotein expression.In summary,the information generated by the present study could provide a theoretical basis for the exploration of novel healthy food materials from edible mushroom with antiinflammation activities.

Establishment and characterization of a canine chondrosarcoma cell line:Mango

In the global progress of bone tumor research,established stable and long-lasting transgenic chondrosarcoma(CSA)cell lines are rare,mainly of murine and human origin,while the establishment of canine CSA cell lines has yet to be reported.This study established a canine CSA cell line to facilitate the basic clinical study of canine CSA.Fifty fve cases of canine osteolytic disease were collected,and more than 10 bone tumor samples from dogs with typical clinical signs were used for primary cell culture.A cell line with stable passaging for more than 100 generations and mouse tumorigenic ability was successfully cultured.According to the clinical characteristics of the dog and the histopathological results of the primary tumor,CSA was diagnosed,and the CSA cell line was designated Mango.Immunohistochemical(IHC)results showed that the immunoreactivity of bone gamma-carboxyglutamate protein(BGLAP),secreted protein acidic and rich in cysteine(SPARC),alkaline phosphatase(ALPL),vimentin(VIM)and S100 were positive.However,the immunoreactivity of pan-cytokeratin(PCK),chromogranin A(CGA),and platelet endothelial cell adhesion molecule-1(CD31)was negative.Immunofuorescence(IF)results showed that the protein expressions in the Mango cell line were consistent with the IHC identifcation of the primary tumor.The Mango cell line’s doubling time was 43.92 h,and the cell formation rate exceeded 20%.There were abnormal chromosome numbers,hetero staining with toluidine blue,and certain calcifcation abilities.It could be passaged stably and continuously without changing the cell morphology and characteristics.In vivo,the cells were successfully injected into the nude mice model with a tumorigenic rate of 100%.The immunophenotype of the xenograft tumor was consistent with that of the primary tumor.Therefore,we efectively established a canine CSA cell line.As a promising cell material,this cell line can be used to construct a tumor-bearing model conducive to the subsequent basic research of canine CSA.Moreover,because of its similarity to human CSA,the animal model of CSA is also indispensable for investigating human CSA.

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.

Fine quantitative characterization of high-H2S gas reservoirs under the influence of liquid sulfur deposition and adsorption

In order to clarify the influence of liquid sulfur deposition and adsorption to high-H2S gas reservoirs,three types of natural cores with typical carbonate pore structures were selected for high-temperature and high-pressure core displacement experiments.Fine quantitative characterization of the cores in three steady states(original,after sulfur injection,and after gas flooding)was carried out using the nuclear magnetic resonance(NMR)transverse relaxation time spectrum and imaging,X-ray computer tomography(CT)of full-diameter cores,basic physical property testing,and field emission scanning electron microscopy imaging.The loss of pore volume caused by sulfur deposition and adsorption mainly comes from the medium and large pores with sizes bigger than 1000μm.Liquid sulfur has a stronger adsorption and deposition ability in smaller pore spaces,and causes greater damage to reservoirs with poor original pore structures.The pore structure of the three types of carbonate reservoirs shows multiple fractal characteristics.The worse the pore structure,the greater the change of internal pore distribution caused by liquid sulfur deposition and adsorption,and the stronger the heterogeneity.Liquid sulfur deposition and adsorption change the pore size distribution,pore connectivity,and heterogeneity of the rock,which further changes the physical properties of the reservoir.After sulfur injection and gas flooding,the permeability of TypeⅠreservoirs with good physical properties decreased by 16%,and that of TypesⅡandⅢreservoirs with poor physical properties decreased by 90%or more,suggesting an extremely high damage.This indicates that the worse the initial physical properties,the greater the damage of liquid sulfur deposition and adsorption.Liquid sulfur is adsorbed and deposited in different types of pore space in the forms of flocculence,cobweb,or retinitis,causing different changes in the pore structure and physical property of the reservoir.

HVSR analysis of pumice sands for sediment depth characterization:A case study for Guadalajara,Mexico

The horizontal to vertical spectral ratio(HVSR)methodology is used here to characterize pumice soils and to image the three-dimensional surface geometry of Guadalajara,Mexico.Similar to other Latin American cities,Guadalajara is exposed to high seismic risk,with the particularity of being the largest urban settlement in Latin America built on pumice soils.Methodology has not yet been tested to characterize subsoil depths in pumice sands.Due to the questionable use of traditional geotechnical tests for the analysis of pumice soils,HVSR provides an alternative for its characterization without altering its fragile and porous structure.In this work,resonance frequency(F0)and peak amplitude(A0)are used to constrain the depth of the major impedance contrast that represents the interface between bedrock and pumice soil.Results were compared with borehole depths and other available geotechnical and geophysical data and show good agreement.One of the profiles estimated on the riverbanks that cross the city,reveals different subsoil thickness that could have an impact on different site responses on riverine areas to an eventual earthquake.Government and academic efforts are combined in this work to characterize depth sediments,an important parameter that impacts the regulations for construction in the city.