Experimental and Simulation Analysis of Two-Tone and Three-Tone Photodetector Linearity Characterizing Systems

Two measurement techniques are investigated to characterize photodetector linearity. A model for the two-tone and three-tone photodetector systems is developed to thoroughly investigate the influences of setup components on the measurement results. We demonstrate that small bias shifts from the quadrature point of the modulator will induce deviation into measurement results of the two-tone system, and the simulation results correspond well to experimental and calculation results.

An optimized fitting function with least square approximation in InAs/AlSb HFET small-signal model for characterizing the frequency dependency of impact ionization effect

An enhanced small-signal model is introduced to model the influence of the impact ionization effect on the performance of In As/Al Sb HFET, in which an optimized fitting function D（ωτi） in the form of least square approximation is proposed in order to further enhance the accuracy in modeling the frequency dependency of the impact ionization effect.The enhanced model with D（ωτi） can accurately characterize the key S parameters of In As/Al Sb HFET in a wide frequency range with a very low error function EF. It is demonstrated that the new fitting function D（ωτi） is helpful in further improving the modeling accuracy degree.

APPLICATION OF SURFACE-ENHANCED RAMAN SPECTORSCOPY FOR CHARACTERIZING HUMIC SUBSTANCES

Surface-enhanced Raman Spectroscopy(SERS)has been used to characterize hurnic substances.By using HNO_3 -roughened silver foils as the enhancing surface,both fluorescence quenching and strong SERS signals have been observed at the same time.The results obtained herein show that SERS is a particularly sensitive and highly selective technique for the characterization of humic substances in the environment. Humic substances axe receiving ever-inereasing attention because of their importance in the environment. Very recently,we have reported the first successful application of Raman spectroscopy for characterizing humic substances.In this present paper,the application of surface-enhanced Raman spectroscopy(SERS)for humic substances has further been investigated.To our knowledge,no such studies have previously been reported.The results obtained herein dearly demonstrate that SERS has a great deal of promise as an analytical method for“In Situ”characterizing humic substances in the environment.

FORWARD GATED-DIODE R-G CURRENT METHOD: A SIMPLE NOVEL TECHNIQUE FOR CHARACTERIZING LATERAL LIGHTLY DOPING REGION OF LDD MOSFET's

This paper presents a simple novel technique-forward gated-diode R-G current method-to determine the lateral lightly-doped source/drain (S/D) region interface state density and effective surface doping concentration of the lightly-doped drain (LDD) N- MOSFET's simultaneously. One interesting result of the numerical analysis is the direct characterization of the interface state density and characteristic gate voltage values corresponding to LDD effective surface doping concentration. It is observed that the S/D N- surface doping concentration and corresponding region's interface state density are R-G current peak position and amplitude dependent, respectively. It is convincible that the proposed method is well suitable for the characterization of deep sub-micron MOSFET's in the current ULSI technology.

Adaptive sampling strategy for characterizing spatial distribution of soil liquefaction potential using cone penetration test

Characterizing spatial distribution of soil liquefaction potential is critical for assessing liquefactionrelated hazards(e.g.building damages caused by liquefaction-induced differential settlement).However,in engineering practice,soil liquefaction potential is usually measured at limited locations in a specific site using in situ tests,e.g.cone penetration tests(CPTs),due to the restrictions of time,cost and access to subsurface space.In these cases,liquefaction potential of soil at untested locations requires to be interpreted from limited measured data points using proper interpolation method,leading to remarkable statistical uncertainty in liquefaction assessment.This underlines an important question of how to optimize the locations of CPT soundings and determine the minimum number of CPTs for achieving a target reliability level of liquefaction assessment.To tackle this issue,this study proposes a smart sampling strategy for determining the minimum number of CPTs and their optimal locations in a selfadaptive and data-driven manner.The proposed sampling strategy leverages on information entropy and Bayesian compressive sampling(BCS).Both simulated and real CPT data are used to demonstrate the proposed method.Illustrative examples indicate that the proposed method can adaptively and sequentially select the required number and optimal locations of CPTs.

Three-dimensional analysis technology for accurately characterizing non-metallic inclusion particles in steel

In this paper, a kind of three-dimensional analysis technology for characterizing non-metallic inclusions in steel was clearly elaborated. It is an electron microscopy observation, namely the non-aqueous electrolysis extraction method with a settled coulometer. In the research,the extraction effects of non-metallic inclusions in different electrolysis systems were studied, and it was concluded that alkalescent 2% TEA non-aqueous electrolyte was applicable for extracting most of non-metallic inclusion particles in steel. And then, in order to ensure the microscopic characterization and statistical calculation of inclusion particles, some electrolysis parameters should be confirmed, such as the size of the sample, control of the electrolysis mass, electric current, etc. Furthermore, for preventing the disturbance of carbides and presenting clear three-dimensional appearance by microscopic characterization, magnetic separation was utilized to separate the inclusion particles from carbides, which was useful for getting more veracious types, particle sizes and chemical composition of inclusions. Moreover, through calculation of quantity and particle size of inclusions in continuous determinate fields, the total quantity per unit volume or area and the particle size distribution of inclusions could be acquired by conversion with electrolysis loss. Besides, the comparison between this method and traditional quantitative metallography was also discussed, and finally, a conclusion was drawn that both of them have respectively applications in characterizing inclusions.

Characterizing Poroelasticity of Biological Tissues by Spherical Indentation: An Improved Theory for Large Relaxation

Flow of fluids within biological tissues often meets with resistance that causes a rate-and size-dependent material behavior known as poroelasticity.Characterizing poroelasticity can provide insight into a broad range of physiological functions,and is done qualitatively in the clinic by palpation.Indentation has been widely used for characterizing poroelasticity of soft materials,where quantitative interpretation of indentation requires a model of the underlying physics,and such existingmodels are well established for cases of small strain and modest force relaxationWe showed here that existing models are inadequate for large relaxation,where the force on the indenter at a prescribed depth at long-time scale drops to below half of the initially peak force.We developed an indentation theory for such cases of large relaxation,based upon Biot theory and a generalized Hertz contact model.We demonstrated that proposed theory is suitable for biological tissues(e.g.,spleen,kidney,skin and human cirrhosis liver)with both small and large relaxations.The proposed method would be a powerful tool to characterize poroelastic properties of biological materials for various applications such as pathological study and disease diagnosis.

PhiBench 2.0: characterizing data analytics workloads on Intel Knights Landing

With high computational capacity, e.g. many-core and wide floating point SIMD units, Intel Xeon Phi shows promising prospect to accelerate high-performance computing(HPC) applications. But the application of Intel Xeon Phi on data analytics workloads in data center is still an open question. Phibench 2.0 is built for the latest generation of Intel Xeon Phi(KNL, Knights Landing), based on the prior work PhiBench(also named BigDataBench-Phi), which is designed for the former generation of Intel Xeon Phi(KNC, Knights Corner). Workloads of PhiBench 2.0 are delicately chosen based on BigdataBench 4.0 and PhiBench 1.0. Other than that, these workloads are well optimized on KNL, and run on real-world datasets to evaluate their performance and scalability. Further, the microarchitecture-level characteristics including CPI, cache behavior, vectorization intensity, and branch prediction efficiency are analyzed and the impact of affinity and scheduling policy on performance are investigated. It is believed that the observations would help other researchers working on Intel Xeon Phi and data analytics workloads.

Characterizing Lake Bottom Sediments Using Marine Geophysical Tools

Missouri is a state with rich karst terrain. Geotechnical evaluation of foundation design for bridges and dams requires an understanding of the characteristics of subsurface geological environment, including sediments, bedrock and benthic habitat. It is crucial that the community empowers itself with the knowledge of the karst system’s characteristics in order to potentially use it as a source of water and drainage, but also to avoid the disaster of building constructions too close to vulnerable land on top of massive karst caverns. Electrical resistivity tomography profiling (underwater cables), and continuous resistivity profiling (towed cable) surveys were conducted to characterize the lake sediments (rock and soil) beneath the man-made Little Prairie Lake, in Central of Missouri State, United States. Electrical resistivity (with marine cables and towed cable) was used to determine variability in the lithology and thickness of sediments (soil and rock) beneath the lake with conjunction of echo sounder in order to calculate water depth. Side scan sonar was used to map the variations in the lithology/nature of exposed lakebed sediments and to locate the potential hazard of trees. On land, electrical resistivity tomography was used with multi-channel analysis of surface wave method to determine sediments, joints, and the depth of bedrock. Analyses of the acquired data revealed the location and orientation of the original stream channels (prior to the construction of the earth fill dam). Underwater electrical resistivity tomography and continuous resistivity profiling determined joints, sediments, and bedrock underneath water bodies. Integrated marine geophysical tools help to evaluate the subsurface prior to any construction project (dam or bridge), are useful in determining the characteristics of lithology (fractured rock, intact rock and soil), and make it possible to map benthic habitat and the submerged potential hazards of trees on the lakebed as well as accurately measuring water depth.

Contemporary strategies and approaches for characterizing composition and enhancing biofilm penetration targeting bacterial extracellular polymeric substances

Extracellular polymeric substances(EPS)constitutes crucial elements within bacterial biofilms,facili-tating accelerated antimicrobial resistance and conferring defense against the host's immune cells.Developing precise and effective antibiofilm approaches and strategies,tailored to the specific charac-teristics of EPS composition,can offer valuable insights for the creation of novel antimicrobial drugs.This,in turn,holds the potential to mitigate the alarming issue of bacterial drug resistance.Current analysis of EPS compositions relies heavily on colorimetric approaches with a significant bias,which is likely due to the selection of a standard compound and the cross-interference of various EPS compounds.Considering the pivotal role of EPS in biofilm functionality,it is imperative for EPS research to delve deeper into the analysis of intricate compositions,moving beyond the current focus on polymeric materials.This ne-cessitates a shift from heavy reliance on colorimetric analytic methods to more comprehensive and nuanced analytical approaches.In this study,we have provided a comprehensive summary of existing analytical methods utilized in the characterization of EPS compositions.Additionally,novel strategies aimed at targeting EPS to enhance biofilm penetration were explored,with a specific focus on high-lighting the limitations associated with colorimetric methods.Furthermore,we have outlined the challenges faced in identifying additional components of EPS and propose a prospective research plan to address these challenges.This review has the potential to guide future researchers in the search for novel compounds capable of suppressing EPS,thereby inhibiting biofilm formation.This insight opens up a new avenue for exploration within this research domain.

Editorial

In pursuit of higher energy density,lower cost,longer lifespan and safety,remarkable research efforts have been taken to innovate various types of energy storage materials/devices,especially metal-ion batteries such as Li-ion batteries(LIBs).One of the major challenges is to elucidate the working mechanisms and/or the controlling factors of any new material in a full battery,which requires adequate characterization/diagnosis techniques.Among the numerous electrochemical ex-situ and insitu characterization techniques,magnetic resonance techniques,including nuclear magnetic resonance(NMR),magnetic resonance imaging(MRI)and electron paramagnetic resonance(EPR),are unique in terms of providing structural information at the atomic level and real-time phase and morphology evolution and characterizing ionic motion at various timescales.This special issue is dedicated to an editorial and a selection of papers on the theme of investigating energy storage materials/devices using magnetic resonance techniques.As the guest editors of this special issue,we are honored to introduce the following high-quality research articles and review articles.

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.

Characterizing the rock geological time by terahertz spectrum

In the field of geology,it is necessary to get the information about the rock geological time,which includes absolute geologic age and relative geologic age .Tracing the evolutionary history of the earth is one of the research tasks of earth science.Time,space,material and motivation are the basic elements for studying geological processes and enviromnental evolution,and time is the basis for studying geological problems.A clear understanding of the interaction between the above elements will be able to clearly make sure the evolution of the earth and the conditions of rock formation.Nowadays,it is urgent to get the geochronological data of rocks for wide range comparison,so as to study the evolution trend and development rule of the earth's crust .

基于SCAR标记和DNA条形码技术的苍术基原鉴别研究

目的开发出能同时鉴别北苍术和关苍术的分子标记方法,并探究不同种质资源苍术的遗传进化关系。方法对不同地区北苍术Atractylodes chinensis(Bunge)Koidz及关苍术A.japonica Koidz.ex Kitam基因组DNA的差异片段进行测序,结合SRAP、ISSR、DAMD分子标记方法,优化PCR反应体系,筛选并转换成特异性标记,同时,采用条形码方法分析种间序列差异。结果通过SRAP、ISSR、DAMD三种分子标记方法的PCR扩增,共筛选出198对能稳定扩增且重现性好的引物,转换出7对能稳定、快速鉴别北苍术和关苍术的SCAR引物。条形码方法检测出北苍术ITS2序列长度为454 bp,关苍术ITS2序列长度为453 bp,与其他苍术属植物之间遗传距离较远。NJ树结果显示,北苍术、关苍术及其他苍术属植物均各自聚为一支,表现出良好的单系性。依据ITS2二级结构,4种苍术属植物在螺旋区的茎环数目、大小、位置均有明显差异,可以直观地进行区分。结论所开发的特异性SCAR标记为苍术属植物优良品种的筛选提供了新方法,DNA条形码能稳定、准确鉴别北苍术。

Pitfalls of restriction enzyme analysis in identifying, characterizing,typing, and naming viral pathogens in the era of whole genome data, as illustrated by HAdV type 55

Restriction endonuclease analysis(REA),or restriction fragment length polymorphism(RFLP),was useful for identifying and determining the relatedness and putative identities of microbial strains(Tang et al.,1997)and for characterizing and discriminating large numbers of samples inexpensively in the past。

Modeling and characterizing the typical under-ice acoustic channel for the Arctic

The properties of arctic underwater acoustic channel were researched using BurkeTwersky(BT) model and ray theory.In the BT model,sea ice ridge is assumed as a set of semi-elliptical cylinder randomly distributed on a stress-free surface.By approximation of low frequency and high frequency of the BT model,the reflection coefficients were calculated at different frequencies.On the basis of ray theory,the acoustic field was calculated and the properties of underwater acoustic channel was analyzed.Compared to underwater acoustic channel properties when the boundary is air,the results show that under the ice surface some sound rays disappear during transmission,because the ice surface reflection coefficients is less than absolute soft surface.Especially,the higher the frequency,the higher the under-ice transmission loss.As a result,under-ice condition is unfavourable for acoustic signals to travel far.Besides,as to the channel structure,the reflection coefficient of ice layer is smaller,the channel multi-path structure is not significant compared to water-air interface without ice.The research results are valuable for our understanding of hydroacoustic channel and the prediction of the sonar system working in the polar region.

Investigation of Microstructure, Microhardness and Thermal Properties of Ag-In Intermetallic Alloys Prepared by Vacuum Arc Meltings

Ag-In intermetallic alloys were produced by using vacuum arc furnace. Differential Scanning Calorimetry(DSC) and Energy Dispersive X-Ray Spectrometry(EDX) were used to determine the thermal properties and chemical composition of the phases respectively. Microhardness values of Ag-In intermetallics were calculated with Vickers hardness measurement method. According to the experimental results, Ag-34 wt%In intermetallic system generated the best results of energy saving and storage compared to other intermetallic systems. Also from the microhardness results, it was observed that intermetallic alloys were harder than pure silver and Ag-26 wt%In system had the highest microhardness value with 143.45 kg/mm^(2).

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.

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.

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.