Influence of solvent characteristics in triaxial electrospun fiber formation

Triaxial electrospinning is a novel method for fabrication of multilayered nano and microsize fibers with desirable features for particular applications. Since the effect of solvent volatilities in each layer and relative polymer molecular weights on uniform encapsulation of the core polymer process is not well understood, we evaluated (i) the role of solvent volatilities, and (ii) molecular weights using cellulose acetate (CA, 30 kDa), polycaprolactone (PCL, 45 kDa and 80 kDa), mineral oil, and polyvinyl alcohol (PVA, 30 kDa and 100 kDa). Different solvent mixtures were evaluated based on the boiling points determined using a simulator. Inner mineral oil was selectively removed to form Hollow fibers. Analysis of chemical compositions using FT-IR and DSC revealed the presence of each component. 24-h viability of human umbilical vein endothelial cells indicated the formed fibers were not toxic. Scanning electron micrographs indicated the formation of triaxial structured fiber of outer hydrophobic PCL/CA/Hollow, PCL/PVA/Hollow and outer hydrophilic CA/PCL/Hollow fibers. Tensile tests (both wet and dry) revealed that PCL/CA/Hollow fibers had increased stiffness and load carrying capacity than CA/PCL/Hollow fibers. Successful fiber formation was dependent on ensuring that the outer shell formed first i.e., the relative solvent volatility of encapsulating core polymer to lower than that of the shell polymer.     

Generalized autoregressive moving average models with GARCH errors

One of the important and widely used classes of models for non-Gaussian time series is the generalized autoregressive model average models (GARMA), which specifies an ARMA structure for the conditional mean process of the underlying time series. However, in many applications one often encounters conditional heteroskedasticity. In this article, we propose a new class of models, referred to as GARMA-GARCH models, that jointly specify both the conditional mean and conditional variance processes of a general non-Gaussian time series. Under the general modeling framework, we propose three specific models, as examples, for proportional time series, non-negative time series, and skewed and heavy-tailed financial time series. Maximum likelihood estimator (MLE) and quasi Gaussian MLE are used to estimate the parameters. Simulation studies and three applications are used to demonstrate the properties of the models and the estimation procedures.     

动力煤期货价格波动对我国煤炭经济影响研究*

采用中国煤炭价格指数、中国煤炭市场景气指数、中国煤炭市场预期指数和煤炭行业失业率作为我国煤炭经济发展的代表变量,选取2013年9月～2018年7月之间的交易数据,构建VAR模型,研究了动力煤期货价格与中国煤炭价格指数、中国煤炭市场景气指数、中国煤炭市场预期指数和煤炭行业失业率之间的动态关系。格兰杰因果检验表明:国内动力煤期货价格是中国煤炭价格指数、中国煤炭市场景气指数、中国煤炭市场预期指数和煤炭行业失业率的格兰杰原因。脉冲响应和方差分解分析表明:动力煤期货价格波动会引起中国煤炭市场景气度同方向变动;滞后2阶的动力煤期货价格上涨会使得中国煤炭市场预期指数上升;滞后2阶动力煤期货价格上涨,失业率降低。长期来看,动力煤期货价格上涨会使得失业率降低,动力煤期货价格与我国煤炭经济发展之间呈现动态均衡关系。     

A hybrid modeling approach for forecasting the volatility of S&P 500 index return

Forecasting volatility is an essential step in many financial decision makings. GARCH family of models has been extensively used in finance and economics, particularly for estimating volatility. The motivation of this study is to enhance the ability of GARCH models in forecasting the return volatility. We propose two hybrid models based on EGARCH and Artificial Neural Networks to forecast the volatility of S&P 500 index. The estimates of volatility obtained by an EGARCH model are fed forward to a Neural Network. The input to the first hybrid model is complemented by historical values of other explanatory variables. The second hybrid model takes as inputs both series of the simulated data and explanatory variables. The forecasts obtained by each of those hybrid models have been compared with those of EGARCH model in terms of closeness to the realized volatility. The computational results demonstrate that the second hybrid model provides better volatility forecasts.     

Behavior of Ruthenium in Fluoride-Volatility Processes, (VI)

Hydrogen gas evolution from water dispersing nanoparticles induced by ⁶⁰Co γ-ray irradiation was studied. Nanoparticles of TiO₂ and Al_2O3 with average sizes of 7–33 nm supplied from several suppliers were examined. It was indicated that reactions enhancing the hydrogen evolution proceed on particle's surface. It was implied that the yield depends on size of agglomerated particle regardless of their primary particle size and chemical species. Reactions that enhance the hydrogen yields were discussed, and radiolysis process was concluded dominant in the total enhancement mechanism.     

Effects of Ultrasonic Waves on Vapor-Liquid Equilibrium of an Azeotropic Mixture

Abstract

Azeotropic and extractive distillation techniques used to separate azeotropic mixtures are among the most challenging separation processes in the chemical industry. In this work, an innovative distillation technique which employed ultrasonic waves was proposed to intensify the conventional multi-column azeotropic distillation method into a single-column alternative. The effects of ultrasonic intensity on the vapor-liquid equilibrium (VLE) of methyl-tert-butyl-ether (MTBE)-methanol was investigated at 50, 100, 200, and 250 W/A·cm² and at a fixed frequency of 40 kHz. Studies were also done to examine the effects of ultrasonic frequency on the VLE data at 25 and 68 kHz frequencies. It was found that ultrasonic waves at 50 W/A·cm² intensity and 25 kHz frequency gave the highest relative volatility (α) at 2.654 and completely eliminated the MTBE-methanol azeotrope, thereby allowing highly pure MTBE to be recovered in just a single distillation column. The results revealed that ultrasonic waves had the potential to favorably manipulate α, and hence, the VLE of an azeotropic mixture.     

Initial column profile with composition-dependent relative volatility

When solving the large scale, highly nonlinear, equation systems of steady state multistage distillation processes modelled with theoretical plates, convergence depends on the initial values. The conventionally applied linear initial profiles frequently give rise to divergence when azeotrope is present. The usual practice in such cases is initializing with engineering insight, i.e. anticipating the results. Composition-dependent relative volatility model is developed in the present work, and applied successfully to initialize the composition profiles of distillation columns. The model describes the implicit temperature dependence through composition dependence. Equlibrium plots computed with the new model well approximate the measured data of strongly non-ideal, and even azeotropic, mixtures. The initial column profiles computed with the new model are rather similar to the final solution, and thus accelerate the computation. Processes can be modelled with the new initial profile when the solution algorithms do not converge with the conventional initialization.     

阳极焙烧炉工艺管理节能优化分析

阳极焙烧炉的燃料消耗是阳极焙烧的一项重要指标,焙烧炉的燃料消耗取决于多种因素,合理的燃烧工艺管理操作方法是减少燃料消耗的一个重要环节.本文从阳极焙烧炉热平衡分析入手,通过分析找出影响燃料消耗的影响因素与燃烧消耗之间的关系并根据工作实践提出阳极焙烧工艺管理节能优化的措施.     

水-乙醇-1-丁基-3-甲基咪唑乙酸盐三元体系汽液平衡测定及模型

Vapor-liquid equilibrium (VLE) data were measured for ternary system water + ethanol + 1-butyl-3- methylimidazolium acetate ([bmim][OAc]), in a relatively wide range of ionic liquid (IL) mass fractions up to 0.8. Six sets of complete T-x-y data were obtained, in which the mole fraction of ethanol on IL-free basis was fixed separately at 0.1, 0.2, 0.4, 0.6, 0.8, and approximate 0.98. The non-random-two-liquid (NRTL) and electrolyte non-random-two-liquid (eNRTL) equations were used for correlation, showing similar deviations. The ternary VLE was also modeled with the correlation from two data sets, with the mole fractions of ethanol on IL-free basis being 0.1 and approximate 0.98. The VLE data were also reproduced satisfactorily. With the eNRTL model, the root-mean-square deviation for temperature is 0.79 K and that for vapor-phase mole fraction is 0.0094. The calculations are in good agreement with experimental data. The effect of the IL on the VLE behavior of the volatile components is also illustrated.