SB Distribution Research Articles

Bulk Single Crystals and Physical Properties of Rutile GeO2 for High‐Power Electronics and Deep‐Ultraviolet Optoelectronics

The top‐seeded solution growth for rutile GeO2 single crystals using alkali carbonates or fluorides as flux is applied. Structural data of obtained single crystals confirm the rutile phase with a = b = 4.3966 Å and c = 2.8612 Å. The crystals with diameter of 5–15 mm are either undoped or intentionally doped with Sb5+, Sn4+, Al3+, Ga3+, and F− ions. It is found that Sb5+ is a very efficient n‐type donor enabling free electron concentration even above 1020 cm−3; thus, Sb‐doped GeO2 is a potential substrate for vertical power devices. In contrast, crystals doped with Al and Ga do not show p‐type conductivity suggested by the theory. The onset of the absorption occurs at 5.0 and 5.5 eV perpendicular and parallel to the c‐axis, respectively. Rutile GeO2 shows a very intense photoluminescence peaking at 420 nm (blue) and 520 nm (green). Raman spectra show narrow lines, in particular at high phonon energy (B1g, 170 cm−1). Prepared wafers show FWHM values of rocking curves below 30 arcsec and polishing is achieved down to RMS roughness of 0.15 nm. Transmission electron microscopy images do not show point or extended structural defects with uniform Sb distribution.

Uniform Sb doping of ZnO films with controllable morphology and enhanced optical property

In order to provide an effective and reliable approach to solving the difficulties in p-type modification of ZnO nanomaterials, in this work, we successfully synthesized ZnO films with uniform antimony distribution through low temperature aqueous growth method. The growth quality and dopant distribution of Sb-doped ZnO (SZO) films were evaluated by high-resolution micro-structural characterizations, and the growth mechanism for SZO films with various doping concentrations was discussed and revealed. Uniform and dispersive Sb distribution within SZO films contributed to the light transmittance of SZO films. The blue-shifted UV emission accompanied with weak visible light emission of SZO films were observed in room-temperature photoluminescent (PL) spectra, the rare yellow-red light emission and XPS results confirmed the existence of SbZn-related complex defects. This type of SZO films is competitive and promising for serving as the highly photo-conductive and photo-sensitive ZnO-based nanomaterials. And SZO films could be served as the basis for realizing the purpose of p-type modification with high efficiency and excellent stability.

A contrastive analysis of Sb distribution in Sn-Bi-Sb solder by WDS and EDS

This work provides a contrastive analysis of Sb distribution in Sn-57Bi-1Sb solder by WDS mapping, EDS count map and EDS net map. The mapping analysis on the same region shows that the WDS mapping provides the more accurate data on the distribution of Sb compared with EDS analysis, including the concentration gradient of dissolved Sb and the fine SnSb particles with size less than 1 μm. WDS equipped with the enhanced spectral resolution is a critical technique to separate the complex overlap spectrum, which was recommended for the Sb detection in Sb-doped solders.

Floodplain morphology influences arsenic and antimony spatial distribution in a seasonal acid sulfate soil wetland

Arsenic (As) and antimony (Sb) often co-occur in floodplain depositional environments that are contaminated by legacy mining activities. However, the distribution of As and Sb throughout floodplains is not uniform, adding complexity and expense to management or remediation processes. Identifying floodplain morphology predictor variables that help quantify and explain As and Sb spatial distribution on floodplains is useful for management and remediation. We developed As and Sb risk maps estimating concentration and availability at a coastal floodplain wetland impacted by upper-catchment mining. Significant predictors of As and Sb concentrations included i) distance from distributary channel-wetland intersection and ii) elevation. Distance from channel explained 53 % (P < 0.01) and 28 % (P < 0.01), while elevation explained 42 % (P < 0.01) and 47 % (P < 0.01) of the variability in near-total Sb and As respectively. As had a higher extractability than Sb across all tested soil extractions, suggesting that As is more environmentally available. As and Sb dry mass estimates to a depth of 0.1 m scaled to the lower coastal Macleay floodplain ranged from 113–192 tonnes and 14–24 tonnes respectively. Landscape-scale modelling of metalloid distribution, informed by morphology variables, presented here may be a useful framework for the development of risk maps in other regions impacted by contaminated upper-catchment sediments.

Inference for the Johnson SB distribution

This article develops inferential procedures for the Johnson SB distribution and the associated stress-strength model. The maximum likelihood estimators, uniformly minimum variance unbiased estimators and generalized confidence intervals for the parameters of the Johnson SB distribution are presented. The objective Bayesian inference methods based on the Jeffreys and reference priors are derived. Moreover, the generalized confidence lower limits and Bayesian credible lower limits for the reliability of the stress-strength model are provided. The performance of the proposed methods is evaluated by Monte Carlo simulation. Finally, an example is used to illustrate the proposed procedures.

Diameter distributions in Pinus sylvestris L. stands: evaluating modelling approaches including a machine learning technique

The diameter distribution of trees in a stand provides the basis for determining the stand’s ecological and economic value, its structure and stability and appropriate management practices. Scots pine (Pinus sylvestris L.) is one of the most common and important conifers in Turkey, so a well-planned management schedule is critical. Diameter distribution models to accurately describe the stand structure help improve management strategies, but developing reliable models requires a deep understanding of the growth, output and constraints of the forests. The most important information derived by diameter distribution models is primary data on horizontal stand structure for each diameter class of trees: basal area and volume per unit area. These predictions are required to estimate the range of products and predicted volume and yield from a forest stand. Here, to construct an accurate, reliable diameter distribution model for natural Scots pine stands in the Türkmen Mountain region, we used Johnson’s SB distribution to represent the empirical diameter distributions of the stands using ground-based measurements from 55 sample plots that included 1219 trees in natural distribution zones of the forests. As an alternative, nonparametric approach, which does not require any predefined function, an artificial intelligence model was constructed based on support vector machine methodology. An error index was calculated to evaluate the results. Overall, both Johnson’s SB probability density function with a three-parameter recovery approach and the support vector regression methodology provided reliable estimates of the diameter distribution of these stands.

Active-learning search for unitcell structures: A case study on Mg3Bi2-xSbx

Given a concentration, the determination of atomic configuration of a compound is very challenging, although it is the base and prerequisite for the investigation of the properties. Taken the Mg-Bi-Sb alloy system as an example, we have investigated the crystal structure of the Mg3Bi2-xSbx(0 < x < 2) using the revised LAsou method with an active learning strategy. We have explicitly examined the atomistic configurations with three unit-cell sizes (10, 40, and 90 atoms). Referring to the conventional method, our method reduces the computational demand by several order of magnitude. Structural analysis including bond-order parameter, disorder parameter, short-range order parameter, and radial distribution function, revealed that the 90-atom unit cells allowed for more diverse and random Sb distribution in the structure than the 10-atom and 40-atom cell simulations. The XRD spectral analysis confirms that the predicted structures agree well with experiment. Through an illustrative case study of Mg-Bi-Sb system, our work has demonstrated a route to determine the atomic configurations with the information of formula combined with first-principles calculations, which might benefit the atomistic unit-cell modelling of compounds and alloys in computational materials science.

Influence of the Impurity Element Sb on Oxidation Resistance and Creep Strength of the Ni-Base Single Crystal Superalloy TMS-238

The influence of impurity element Sb on the oxidation resistance and creep strength of the single crystal superalloy TMS-238 was studied in this work. It was found that 1.1 ppm Sb clearly degrades the oxidation resistance, but not for the creep strength. As we increased the amount of Sb up to 3.8 ppm, the weight loss of the sample increased, as expected for the effect of Sb on the oxidation resistance. To understand the mechanism, the oxide structure was characterized by scanning electron microscope with energy dispersive X-ray spectroscopy (SEM-EDS), and three-dimensional atom probe (3DAP) was used to visualize the Sb distribution. 3DAP analysis has revealed Sb segregation of 0.03 at％ to 0.04 at％ at the oxide/substrate interfaces for 3.8 ppm Sb sample. These results indicated that the segregation of Sb, a low melting point metallic impurity, at the oxide/substrate interface degrades the oxidation resistance for TMS-238.

Impact of Textile Industries on Surface Water Contamination by Sb and Other Potential Toxic Elements: A Case Study in Taihu Lake Basin, China.

Contamination of industry-derived antimony (Sb) is currently of great concern. This study was conducted to identify the source of Sb together with other potential toxic elements (PTEs) in a typical industrial area in China and emphasize the contribution of Sb to ecological risk in the local aquatic environment. By investigating the distribution of nine PTEs in surface water in Wujiang County in dry and wet seasons, this study revealed that textile wastewater was the main source of Sb. The distribution of Sb (0.48~21.4 μg/L) showed the least seasonal variation among the nine elements. Factor analysis revealed that the factor that controlled Sb distribution is unique. In general, Sb was more concentrated in the southeastern part of the study area where there was a large number of textile industries, and was affected by the specific conductivity and total dissolved solids in water (p < 0.01). Sb concentration in 35.71% of samples collected from the drainage outlet exceeded the standard limit of 10 μg/L. Results from three pollution assessment methods suggested that >5% of the sampling sites were slightly too heavily polluted and Sb contributed the most. Therefore, it is necessary to strengthen the administrative supervision of local textile enterprises and elevate the local standard of textile wastewater emission.

Probability distribution models for the ultimate strength of tubular T/Y-joints reinforced with collar plates at room and different fire conditions

In this research work, the simulation results of 360 T/Y-joints reinforced with collar plates have been used to propose theoretical probability distribution models for the ultimate capacity at ambient and fire conditions. So far, no study has been carried out on the probability distribution of ultimate strength in joints with collar plates at room or elevated temperature. Therefore, according to the reinforced T/Y-joint models, which were verified with 18 tests, a total of ultimate capacity data sets was produced. In the FE models, the welds along the collar/brace intersection and between the chord and collar have been generated. Also, the Augmented Lagrange method was applied as the contact algorithm for solving the contact between the collar and chord. In the next step, 13 theoretical probability density functions (PDFs) were fitted to the relative frequency histograms of the databases. For obtaining the parameters of each distribution, the maximum likelihood (ML) method was utilized. Assessing the goodness-of-fit based on the Kolmogorov-Smirnov and Anderson Darling tests indicated that the Johnson SB distribution is the best for the ultimate capacity values in the T/Y-joints reinforced with collar plates at 20, 400, 600, and 800 °C. But, for the reinforced joints at 200 °C, the Inverse Gaussian (3P) distribution is the best. In the next step, five fully defined theoretical PDFs were proposed for the collar plate reinforced T/Y-joints at room and different high temperatures. Probability difference and probability-probability graphs indicated that the proposed theoretical probability distributions are well near the given data sets.

Characterization of the variability of the diameter distribution of natural Taurus cedar stands in Türkiye using Johnson's Sb distribution

Characterization of the variability of the diameter distribution of natural Taurus cedar stands in Türkiye using Johnson's Sb distribution

Thermodynamic modeling of antimony removal from complex resources in copper smelting process

This work investigated the reaction mechanism of Sb in copper smelting process. The difference of multi-phase distribution of Sb in four typical copper smelting processes was analyzed. A multi-phase equilibrium model of the oxygen-enriched bottom-blow copper smelting process was developed. The impacts of Cu, S, and Sb concentrations in raw materials on Sb distribution in multiphases were researched. This model was also used to investigate the effect of process factors such as copper matte grade, oxygen-enriched concentration, smelting temperature, and oxygen/ore ratio (ratio of oxygen flow rate under standard conditions to concentrate charge rate) on Sb distribution behavior. The results showed that calculation data were in good agreement with the actual production results and literature data. Increasing the Cu content and decreasing the S and Sb contents in the concentrate, increasing the copper matte grade, oxygen/enriched concentration, and oxygen-ore ratio, and at the same time appropriately reducing the smelting temperature are conducive to the targeted enrichment of Sb into the slag. Modeling results can provide theoretical guidance for the clean and efficient treatment of complex resources and the comprehensive recycling of associated elements.

Study of the type-I to type-II band alignment transition in InAs(Sb)/GaAs quantum dot nanostructures

InAs(Sb)/GaAs self-assembled quantum dots (QDs) were grown by molecular beam epitaxy though incorporating Sb into InAs with increased beam equivalent pressure ratio, x = Sb2/(Sb2+As2), of x = 0, 0.15, 0.25, and 0.5. From photoluminescence measurements, we observed a transition of the band alignment from type-I for the InAs QDs to type-II for InAsSb QDs. Thus, after adding Sb into the QDs these type II InAsSb QDs have different characteristics from the well-studied type-I InAs QDs regarding to their excitation intensity dependence, temperature dependence, and time dependence of the luminescence. Additionally, the Sb distribution in the QDs and the wetting layer was studied. These results indicate that we are able to fabricate InAsSb QDs with a type II band alignment, which may be good optical materials for the development of intermediate-band photovoltaic cells.

Assessing Sb Cross Incorporation in InAs/InAsSb Superlattices

We developed an x-ray diffraction (XRD) method that uses relative satellite peak intensities to assess the width of the alloy interfaces in InAs/InAsSb Type 2 superlattices (T2SLs). Specifically, our method simulates XRD patterns for T2SLs based on a model of alloy cross-incorporation and fits the simulated pattern to experimental data through a small set of model parameters. We model the Sb distribution function with two forms (i) a Gaussian function, or (ii) two error functions. We compared the model with experimental data extracted from the literature. The first example is a T2SL with 50 periods of 7.0 nm thick InAs and 2.3 nm thick InAs1-xSbx with the targeted alloy composition of x = 0.23. The second example is a T2SL with 100 periods of 4.6 nm thick InAs and 1.7 nm thick InAs1-xSbx with the targeted composition of x = 33.3%. The width of the alloy interface is about 2.54 nm for the first example with the Gaussian model, and with the error function model is 2.8 nm. In the second example, we observed a lower width of the alloy interface of about 0.48 nm with the Gaussian model, and 0.5 nm with the error function model.

Long term monthly prediction of energy requirements from a probabilistic perspective - A case study in southern States of India

Long term energy requirement forecast is necessary for any policy decisions concerning management of resources and its expansions. Numerous works have been reported in the past which primarily focus on short or medium term forecasts which are not adequate for policy decision for the future. The long term forecasts requires a different approach due to the fact that the future trends on energy requirements are uncertain. This study proposes a long-term energy requirement forecast (upto 2030) using Artificial Neural Network (ANN) by correlating the relationship between the trend in the Gross Domestic Product (GDP) and energy demand, and the results are reported in a probabilistic sense by considering the best fitting probability distribution function. The proposed method is applied to the energy requirement data of five different States of India for 13 years (2008–2020). The forecast of future energy requirements and exceedance probability is estimated and discussed by considering 4 different scenarios from no change in trend to 25 % increase. Statistical assessment is done for three different probability distributions and is tested by goodness-of-fit tests namely, the Kolmogorov-Smirnov test, Anderson-Darling test and Chi-squared test to find the best probability fit. It is seen that Johnson SB distribution best fits the data of combined Andhra Pradesh and Telangana, Generalized Extreme Value distribution for the data of Karnataka, Kerala and Tamil Nadu, whereas Kumarasamy distribution best fits the data of Puducherry. In addition, based on a rank of goodness-of-fit tests, it can be concluded that 97 % minimum exceedance probability condition is maintained for overall states under four different conditions. It is concluded that the States will be able to meet the average energy requirement with minimal policy intervention for all the 10 % scenario whereas for the other scenarios a careful policy change may be required to create avenue for energy generation. However, there is only 1 % to 5 % exceedance probability for the 15 % scenario.

Growth interruption strategies for interface optimization in GaAsSb/GaAsN type-II superlattices

Recently, GaAsSb/GaAsN type II short-period superlattices (SLs) have been proposed as suitable structures to be implemented in the optimal design of monolithic multi-junction solar cells. However, due to strong surface Sb segregation, experimental Sb composition profiles differ greatly from the nominal square-wave design. In this work, the improvement of the interface quality of these SLs in terms of compositional abruptness and surface roughness has been evaluated by implementing different growth interruption times under Sb4/As4 (soaking) and As4 (desorption) overpressure conditions before and after the growth of GaAsSb layers, respectively. The combined effects of both processes enhance Sb distribution, achieving squarer compositional profiles with reduced surface roughness interfaces. It has been found that the improvement in compositional abruptness is quantitatively much higher at the lower interface, during soaking, than at the upper interface during desorption. Conversely, a larger decrease in surface roughness is achieved at the upper interface than at the lower interface. Fitting of the Sb segregation profiles using the 3-layer kinetic fluid model has shown that the increase in Sb incorporation rate is due to the decrease in segregation energy, presumably to changes in the surface reconstruction of the floating layer at the surface.

(Digital Presentation) Design of High-Performance Antimony / MXene Hybrid Electrodes for Sodium-Ion Batteries

As a result of the growing electrification and the ever-increasing demand for batteries, scarcity of fossil resources of lithium, and the resulting rise in price, energy storage technologies beyond lithium aroused high interest throughout the past years.1-3 Sodium is a naturally abundant element in the earth and therefore offers the opportunity to develop a promising low-cost, large-scale energy application with favorable energy and power densities. Recently, frequent new and further developments on the anode and cathode materials for sodium-ion batteries have been made. In particular, the development of anode material presents massive challenge while several requirements of high capacity and long lifetime/high durability need to be fulfilled.The unique properties of the novel 2D material MXene, including their excellent electrical conductivity and accessible interlayer space, enable them to be used as attractive electrode materials for battery and supercapacitor. Still, a major drawback is that the capacity of Na+-ion storage by intercalation chemistry is limited due to the limited storage sites.4 As it comes to high-capacity materials, the research field of conversion and alloying materials provides highly attractive candidates. For example, antimony is a promising anode candidate, which undergoes alloying reaction with sodium to form Na3Sb, delivering a high theoretical capacity of 660 mAh g-1. Still, the major drawback of alloying materials is the high volume changes during sodiation and de-sodiation which often leads to electrode cracking, pulverization, continuous reformation of SEI and thus results in poor electrochemical performance. It is, therefore, highly promising to combine both, MXene and antimony for stable, high performance energy storage.Our work explores the best strategy to achieve Sb/MXene hybrid electrodes. There is a tremendous influence in the electrochemical performance dependent on Sb-to-MXene ratio, Sb distribution, and Sb/MXene entanglement. The optimized performance does not align with the highest amount of antimony, the smallest nanoparticles, or the largest interlayer distance of the MXene but by the most homogeneous distribution of antimony and MXene while both components remain electrochemically addressable. With the best optimized hybrid material, we obtained electrodes showing a specific capacity of 450 mAh g-1 at 0.1 A g-1 and 365 mAh g-1 at 4 A g-1, with capacity retention of around 96% after 100 cycles. References Perveen, T.; Siddiq, M.; Shahzad, N.; Ihsan, R.; Ahmad, A.; Shahzad, M. I., Prospects in anode materials for sodium ion batteries-A review. Renewable and Sustainable Energy Reviews 2020, 119, 109549.Skundin, A.; Kulova, T.; Yaroslavtsev, A., Sodium-ion batteries (a review). Russian Journal of Electrochemistry 2018, 54 (2), 113-152.Kundu, D.; Talaie, E.; Duffort, V.; Nazar, L. F., The emerging chemistry of sodium ion batteries for electrochemical energy storage. Angewandte Chemie International Edition 2015, 54 (11), 3431-3448.Kim, Y.; Ha, K. H.; Oh, S. M.; Lee, K. T., High‐capacity anode materials for sodium‐ion batteries. Chemistry–A European Journal 2014, 20 (38), 11980-11992. Figure: De-sodiation capacity and Coulombic efficiency versus cycle number of a simple mechanical mixed antimony MXene electrode (pink) and optimized hybrid material (blue). Figure 1

Parametric Quantile Regression Models for Fitting Double Bounded Response with Application to COVID-19 Mortality Rate Data

In this paper, we develop two fully parametric quantile regression models, based on the power Johnson SB distribution for modeling unit interval response in different quantiles. In particular, the conditional distribution is modeled by the power Johnson SB distribution. The maximum likelihood (ML) estimation method is employed to estimate the model parameters. Simulation studies are conducted to evaluate the performance of the ML estimators in finite samples. Furthermore, we discuss influence diagnostic tools and residuals. The effectiveness of our proposals is illustrated with a data set of the mortality rate of COVID-19 in different countries. The results of our models with this data set show the potential of using the new methodology. Thus, we conclude that the results are favorable to the use of proposed quantile regression models for fitting double bounded data.

Uncertainties in internal pressure of oil transmission pipelines and implications for the reliability analysis

This study addresses a significant knowledge gap in the reliability-based fitnessfor-service assessment of pipelines, namely the statistical information of the internal operating pressure. To this end, probabilistic characteristics of the internal pressure of an in-service oil transmission pipeline are derived based on minute-by-minute pressure records collected from the discharge and suction ends of a pump station on the pipeline. The arbitrary-point-in-time discharge and suction pressures are found to follow the Johnson SB distribution; the monthly and annual maximum discharge pressures are found to be well represented by a deterministic quantity equal to 90% of the maximum operating pressure, and the monthly and annual maximum suction pressures follow the beta distributions. The autocorrelation and power spectral density functions of the discharge and suction pressures characterized as stationary stochastic processes are also derived from the pressure records. Furthermore, the statistics of the pressure ranges obtained from the rainflow counting analysis of the pressure records are obtained. Two example pipelines are used to examine the implications of the uncertainty in the internal pressure for the reliability analysis of corroding pipelines.

Security enhancement for adaptive optics aided longitudinal orbital angular momentum multiplexed underwater wireless communications.

The frozen-wave-based longitudinal orbital angular momentum multiplexing (LOAMM) system developed in [IEEE Photonics J.10, 7900416 (2018)10.1109/JPHOT.2017.2778238] has the potential to overcome the crosstalk effects induced by turbulence. In this paper, we propose a defocus measurement aided adaptive optics (DMA-AO) technique for turbulence compensation in a LOAMM underwater wireless optical communication (UWOC) system to investigate the enhancement of physical layer security. Relying on a phase retrieval algorithm and probe beam, three amplitude-only measurements obtained from different back focus planes can realize phase reconstruction of distorted OAM beams. Moreover, the so-called mixture generalized gamma-Johnson SB (GJSB) distribution is proposed to characterize the probability density function (PDF) of reference-channel irradiance of OAM. The GJSB allows for obtaining closed-form and analytically tractable expression for the probability of strictly positive secrecy capacity (SPSC) in a single input single output (SISO) system. Furthermore, the average secrecy capacity (ASC) and probability of SPSC for a multiple input multiple output (MIMO) system are investigated. Compared to the traditional OAM multiplexing system based on Laguerre-Gaussian (LG) beams, the LOAMM system with a probe beam assisted DMA-AO technique has potential advantages for improving the security performance in UWOC.