Application of robust machine learning methods to modeling hydrogen solubility in hydrocarbon fuels

Having accurate information about the hydrogen solubility in hydrocarbon fuels and feedstocks is very important in petroleum refineries and coal processing plants. In the present work, extreme gradient boosting (XGBoost), multi-layer perceptron (MLP) trained with Levenberg–Marquardt (LM) algorithm, adaptive boosting support vector regression (AdaBoost?SVR), and a memory-efficient gradient boosting tree system on adaptive compact distributions (LiteMORT) as four novel machine learning methods were used for estimating the hydrogen solubility in hydrocarbon fuels. To achieve this goal, a database containing 445 experimental data of hydrogen solubilities in 17 various hydrocarbon fuels/feedstocks was collected in wide-spread ranges of operating pressures and temperatures. These hydrocarbon fuels include petroleum fractions, refinery products, coal liquids, bitumen, and shale oil. Input parameters of the models are temperature and pressure along with density at 20 °C, molecular weight, and weight percentage of carbon (C) and hydrogen (H) of hydrocarbon fuels. XGBoost showed the highest accuracy compared to the other models with an overall mean absolute percent relative error of 1.41% and coefficient of determination (R²) of 0.9998. Also, seven equations of state (EOSs) were used to predict hydrogen solubilities in hydrocarbon fuels. The 2- and 3-parameter Soave-Redlich-Kwong EOS rendered the best estimates for hydrogen solubilities among the EOSs. Moreover, sensitivity analysis indicated that pressure owns the highest influence on hydrogen solubilities in hydrocarbon fuels and then temperature and hydrogen weight percent of the hydrocarbon fuels are ranked, respectively. Finally, Leverage approach results exhibited that the XGBoost model could be well trusted to estimate the hydrogen solubility in hydrocarbon fuels.     

Enhancement of super-hydrophilic/underwater super-oleophobic performance of ceramic membrane with TiO2 nanowire array prepared via low temperature oxidation

A gradient porous ceramic membrane with surface super-hydrophilic and underwater super-oleophobic performance was prepared by combining hydrogel directional freezing method and low temperature oxidation process. The effects of solid contents and sintering temperature on the ceramic membrane matrix were examined. The reaction time and synthesis temperature on the TiO₂ nanowire array were also evaluated. In addition, the related effects on pore size distribution, permeation flux, contact angle, and oil-in-water emulsion separation were systematically investigated. The ceramic membrane matrix pore size changed from 0.5 μm to 25 μm gradually, indicating the gradient structure controlled by the growth of ice. The super-hydrophilic and underwater super-oleophobic performance of ceramic membrane surface was obtained with surface modification by TiO₂ nanowire array, and the surface water contact angle and underwater oil contact angle were less than 5° and over 158°, respectively. The bonding strength between TiO₂ nanowire and ceramic membrane matrix was high enough to withstand ultrasonic waves. The ceramic membrane modified with TiO₂ nanowire array was used for 1000 ppm diesel oil-in-water emulsion separation, and the stable separation efficiency and flux were about 97% and 100–200 L/(m² h bar) even after 10 filtration cycles.     

Effects of alkali metal ion on imprinting GRIN microstructure in GeS2-Ga2S3-MCl (M=Na,K, Cs) glasses for visible to mid-infrared microgratings

Gradient refractive index (GRIN) micro-optics present unique opportunities for control of the chromatic properties, new degrees of freedom for optical design as well as the potential for use in new optical system applications. GRIN microgratings were imprinted in GeS₂-Ga₂S₃-MCl (M = Na, K, Cs) chalcohalide glasses by microthermal poling, and the effects of the type and concentration of alkali cations on their performance were investigated. Two effective imprinting formation regions of the GRIN microstructure based on the poling saturation voltage (U_s) and glass composition are observed at fixed poling time and temperature. The U_s increases from 140 to 750 and 2600 V in accordance with the activation energy (E_a) of alkali ions (Na⁺ to K⁺ and Cs⁺) increasing from 45.15 to 58.62 and 92.58 kJ/mol for studied samples. The saturated numbers of diffraction order (N_s) of the gratings in these samples are 7, 9 and 6, respectively, the highest number being provided by the K⁺-containing sample. This is in accordance with imprinting-induced phase differences (0.14λ, 0.19λ and 0.09λ) measured in the fabricated samples containing Na⁺, K⁺ and Cs⁺ ions. Furthermore, the U_s of samples decreases from 1500 to 300 V with four concentrations of K⁺ from 10 to 30%, associated with their E_a of K⁺ decreasing from 69.62 to 53.46 kJ/mol, while N_s increases from 8 to 14, which is attributed to the increase of the phase difference in the GRIN structures. The controllable GRIN microstructures are realized by adjusting the type and concentration of alkali cations in chalcohalide glasses, which is expected to drive the design of broadband GRIN microgratings.     

Synthesis and luminescence properties of reddish-orange-emitting Ca2GdNbO6:Sm3+ phosphors with good thermal stability for high CRI white applications

Novel reddish-orange-emitting Ca₂GdNbO₆:Sm³⁺ phosphors based on the emission of ⁴G_5/2 → ⁶H_9/2 transition at 651 nm with the chromatic coordinate of (0.633, 0.366) were synthesized. The crystal structure and chemical purity were identified in detail. Under the 407 nm excitation, the optimum concentration of Sm³⁺ ion was found to be 5 mol% dominated by the dipole-dipole interaction in the Ca₂GdNbO₆ host material. The color purity of the sample with optimum doping was estimated to be about 78.38%. Besides, the thermal stability was also studied, and it was further found that the emission intensity remained 65.32% at 423 K. The packaged white LED device exhibited excellent CRI and CCT values of 92.43 and 4896 K. Finally, the polydimethylsiloxane film with a stable structure and flexible property was prepared. These above results reveal that novel reddish-orange-emitting Ca₂GdNbO₆:Sm³⁺ phosphors can be applied in high CRI white communication and flexible display applications.     

哈尔滨典型街谷空间PM2.5分布场与绿色界面指数相关性 研究

在城市化快速进程的背景下，城市 街区PM2.5污染日益严重，本文选取哈尔滨 在不同季节的典型街谷空间，对以叶面积密 度（LA D）、叶面积指数（LAI）为实测要素 的绿色界面指数以及PM2.5浓度进行实测对 比研究。通过对实测数据的分析和挖掘，最 终得出如下结论：首先，典型街谷空间PM2.5 时段浓度呈现上午比下午平均高37.75%，冬 季比夏季高4.7倍的特征；其次，街谷空间的 灌木界面对PM2.5浓度场平均积极贡献率为 18.62%；最后，对PM2.5的衰减率与实测街 谷绿色界面的叶面积密度（LAD）与叶面积 指数（LAI）进行相关性分析，结果显示街谷 绿色界面对PM2.5浓度的衰减作用与叶面积 密度（LAD）呈显著负相关关系，与叶面积指 数（LAI）的相关性程度较弱。     

Schnelle lokale Raman‐Messung zur Untersuchung von Konzentrationsprofilen bei Mischvorgängen in Mikrokanälen

For the evaluation of mixing processes in microreactors, it is necessary to be able to investigate them in detail. For this purpose, a novel optical measuring system is presented, which allows the visualization of mixing and diffusion‐limited processes as well as concentration differences in fluid films. It consists of focusing optics with a microscope objective. In combination with a Raman spectrometer, various processes such as diffusion in the microreactor can be measured and investigated non‐invasively.     

Evaluation of Non-Ambiguous Critical Micelle Concentration of Surfactants in Relation to Solution Behaviors of Pure and Mixed Surfactant Systems: A Physicochemical Documentary and Analysis

Critical micelle concentration (CMC) is a fundamental physical parameter of surfactant aggregation in solution. The CMC is determined by different methods, tensiometry, conductometry, microcalorimetry, fluorimetry, and so on. However, it is known that though CMC is reported as a single value, in reality, micelle formation occurs over a narrow range of concentration for different experimental procedures produce different results. We shall discuss about a unique procedure of measuring correct CMC applicable to all potential methods used in practice. This is essential for the evaluation of thermodynamic properties of the micelle forming process in pure and mixed states in terms of solution theories. As we in this short documentary want to deal with various aspects of Milton Rosen's research—wherein we have also worked—a few other facets of surfactant chemistry research, besides the micelle formation, are also briefly discussed. In mixed surfactant systems, synergistic effects in various surfactant properties like detergency, foaming, solubilization, and so on are found whereas in some others non-synergistic effects are observed. Dehydration of micelles with an increase in temperature or by the addition of hydrophilic substances may cause clouding to the system. Soluble amphiphilic systems produce Gibbs monolayer at the air/water interface; insoluble amphiphiles form Langmuir monolayers. A documentary of the above aspects will be herein presented and discussed. We mention that this article is neither an original research article nor a review article. This is a mixture of the two: a documentary of both original research and some review of our works presented in memory of Prof. Milton Rosen.     

A gradient boosting decision tree approach for insider trading identification: An empirical model evaluation of China stock market

Insider trading is a kind of criminal behavior in stock market by using nonpublic information. In recent years, it has become the major illegal activity in China’s stock market. In this study, a combination approach of GBDT (Gradient Boosting Decision Tree) and DE (Differential Evolution) is proposed to identify insider trading activities by using data of relevant indicators. First, insider trading samples occurred from year 2007 to 2017 and corresponding non-insider trading samples are collected. Next, the proposed method is trained by the GBDT, and initial parameters of the GBDT are optimized by the DE. Finally, out-of-samples are classified by the trained GBDT–DE model and its performances are evaluated. The experiment results show that our proposed method performed the best for insider trading identification under time window length of ninety days, indicating the relevant indicators under 90-days time window length are relatively more useful. Additionally, under all three time window lengths, relative importance result shows that several indicators are consistently crucial for insider trading identification. Furthermore, the proposed approach significantly outperforms other benchmark methods, demonstrating that it could be applied as an intelligent system to improve identification accuracy and efficiency for insider trading regulation in China stock market.     

Microstructure and interface-adhesion of thermally sprayed continuous gradient elastic modulus FeCrAl-ceramic coatings

The bond strength between thermally sprayed metal bond-coats and ceramic top-coats is a key factor in determining their service life. However, most studies focus on interface modifications. In this research, based on FeCrAl bond-coats prepared by arc spraying, top-coats (Al₂O₃-40 wt% TiO₂) were prepared by plasma spraying, and heat treatment was carried out in a hypoxic atmosphere. Continuous gradient elastic modulus FeCrAl-ceramic coatings were successfully prepared, and the microstructural and mechanical properties from the substrate to the top-coats were systematically investigated. The Al₂O₃ content gradually decreased from the top-coats to the substrate, forming continuous gradient elastic modulus FeCrAl-ceramic coatings. The oxide formed during the heat treatment filled the defects in the bond-coats and greatly improved the mechanical properties of the coating. The bonding strength of the continuous gradient elastic modulus coating was 21.7% greater than that of the as-received coating.     

Numerical study of flow distribution uniformity for the optimization of gradient porosity configuration of porous copper fiber sintered felt for hydrogen production through methanol steam reforming micro-reactor

A macroscopic numerical method is proposed to study the flow distribution uniformity of a novel porous copper fiber sintered felt (PCFSF), which has gradient porosities and was developed as the methanol steam reforming micro-reactor catalyst support for hydrogen production for fuel cell applications. The macroscopic porous media developed by the ANSYS/FLUENT software is used to represent the PCFSF. Our results indicate that the gradient porosity can reshape the flow distribution of PCFSFs greatly, thus producing significant influence on their performance. It is further revealed that, for a PCFSF with a determined gradient porosity configuration but different reactant feed directions, the velocity uniformity can be used as a quantitative criterion to evaluate the performance of hydrogen production. Furthermore, new gradient PCFSFs are produced according to the flow distribution of original gradient PCFSFs. The preliminary experimental results of the new gradient PCFSFs of 0.8-0.9-0.7 and 0.7-0.9-0.8 exhibit better methanol conversion and H₂ flow rate. This indicates that the numerical method can be used for the optimization of PCFSFs' gradient porosity configuration, which consists of the shape and position of the interfaces between different porosity portions, the number of interfaces and the porosity distribution in different portions.