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.     

Effect of methylimidazolium-based ionic liquids on vapor–liquid equilibrium behavior of tert-butyl alcohol + water azeotropic mixture at 101.3 kPa

Three ionic liquids(ILs),1-ethyl-3-methylimidazolium bromine([EMIM]Br),1-butyl-3-methylimidazolium bromine([BMIM]Br),and 1-hexyl-3-methylimidazolium bromine([HMIM]Br),were used as the solvent for separation of {tert-butyl alcohol(TBA)+ water} azeotrope.Vapor–liquid equilibrium(VLE)data for {TBA + water + IL}ternary systems were measured at 101.3 k Pa.The results indicate that all the three ILs produce an obvious effect on the VLE behavior of {TBA + water} system and eliminate the azeotropy in the whole concentration range.[EMIM]Br is the best solvent for the separation of {TBA + water} system by extractive distillation among the three ILs.The experimental VLE data for the ternary systems are correlated with the NRTL model equation with good correlations.Explanations are given with activity coefficients of water and TBA,and the experimental VLE-temperature data for {TBA or water + IL} binary systems.     

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.     

A strategy for the development of optimised lubricants

The design of lubricants has traditionally relied on the use of single dimension constitution / performance or structure / property relationships. In this paper a strategy is described whereby consideration is given to the inherent property / property (physical and chemical) correlations that exist for fluid lubricants. Progress towards the development of optimised lubricants is then achieved by identifying the molecular structural or compositional traits associated with ‘extensions’ to or ‘deviations’ from the mainstream correlations. Some examples of the success of this novel strategy will be provided, and the directions of its further refinement briefly outlined.     

A new approach to the Noack volatility test

This paper reports on the method and preliminary results of a significant modification of the Noack volatility test. This modification permits collection and examination of the volatile products as well as of the residue. The analysis of such volatiles by chromatography and spectroscopy revealed surprising information that is especially relevant in the face of increasingly difficult automotive and heavy duty engine emission limitations. The data also showed very close agreement with the Unified Test Method for the Noack Volatility Test now covered by CEC L-40-T-87. Important to operators, the authors' modified Noack apparatus avoids the use of the toxic Wood's Metal of the earlier Noack apparatus.     

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。     

From single crystals to supported nanoparticles in experimental and theoretical studies of H2 oxidation over platinum metals (Pt, Pd): Intermediates, surface waves and spillover

The present paper reviews our investigations concerning the mechanism of H₂ + O₂ reaction on the metal surfaces (Pt, Pd) at different structures: single crystals (Pt(1 1 1), Pt(1 0 0), Pd(1 1 0)); microcrystals (Pt tips); and nanoparticles (Pd–Ti³⁺/TiO₂). Field electron microscopy (FEM), field ion microscopy (FIM), high-resolution electron energy loss spectroscopy (HREELS), XPS, UPS, work function (WF), TDS and temperature-programmed reaction (TPR) methods have been applied to study the kinetics of H₂ oxidation on a nanolevel. The adsorption of both O₂ and H₂ and several dissociative products (H_ads, O_ads, OH_ads) was studied by HREELS. Using the DFT technique the equilibrium states and stretching vibrations of H, O, OH, H₂O, adsorbed on the Pt(1 1 1) surface, have been calculated depending on the surrounding of the metal atoms. Sharp tips of Pt, several hundreds angstroms in radius, were used to perform in situ investigations of the dynamic surface processes. The FEM and FIM studies on the Pt-tip surface demonstrate that the self-oscillations and waves propagations are connected with periodic changes in the surface structure of nanoplane (1 0 0)-(hex) ↔ (1 × 1), varying the catalytic property of metal. The role of defects (Ti³⁺-□_O) in the adsorption centers formation, their stabilization by the palladium nanoparticles, and then the defects participation in H₂ + O₂ steady-state reaction over Pd–Ti³⁺/TiO₂ surface have been studied by XPS, UPS and photodesorption techniques (PhDS). This reaction seems to involve the “protonate” hydrogen atoms (H⁺/TiO_x) as a result of spillover effect: diffusion of H_ads atoms from Pd particles on a TiO_x surface. The comprehensive study of H₂, O₂ adsorption and H₂ + O₂ reaction in a row: single crystals → tips → nanoparticles has shown the same nature of active centers over these metal surfaces.     

存在多委托人条件下考虑溢出效应的重大工程多任务激励模型

在存在工程业主和政府部门作为委托人的情形下,考虑多任务之间存在的溢出效应构建激励模型,在共同代理和独家代理模式下, 分别讨论参与各方的策略与收益。 结果表明,由于溢出效应的存在,政府部门参与激励机制设计,可以使得工程业主和政府部门的收益相较于独家代理模式均得以提高;工程业主也乐于提供更高的激励系数,以刺激项目管理机构付出更多努力;项目管理机构在承接政府部门的任务后,提高了经济效益和声誉, 对来自工程业主的建设任务也产生了正向的溢出效应。建立了多委托人的激励模型,为项目管理机构协调完成工程建设任务和社会责任提供了理论依据。     

环境空气中挥发性有机污染物特征研究

研究环境空气中挥发性有机污染物特征,为城市环境治理提供科学数据依据。以某省为研究对象,使用恒流采样方式采集该省4个季节的空气样本。通过硅烷化苏玛罐—大气浓缩仪—气相色谱—质谱法的方法对采集到的空气样本进行挥发性有机污染物的检测分析。分析结果表明,该省环境空气中常规挥发性有机污染物污染因子主要为PM2.5、PM10和SO2等,且该省冬季和秋季常规挥发性有机污染物污染因子浓度均超过国家规定数值,冬季空气有机物污染较为严重;该省环境空气中挥发性有机污染物单体污染物有36种,包括烷烃、烯烃、炔烃、芳香烃和卤代烃,其中烷烃、烯烃、炔烃和芳香烃为该省环境空气内的主要有机污染物;5种挥发性有机污染物受环境温度、湿度和风速影响较大,且其主要成分浓度分布具备季节性特征。     

Forecasting financial time series volatility using Particle Swarm Optimization trained Quantile Regression Neural Network

Accurate forecasting of volatility from financial time series is paramount in financial decision making. This paper presents a novel, Particle Swarm Optimization (PSO)-trained Quantile Regression Neural Network namely PSOQRNN, to forecast volatility from financial time series. We compared the effectiveness of PSOQRNN with that of the traditional volatility forecasting models, i.e., Generalized Autoregressive Conditional Heteroskedasticity (GARCH) and three Artificial Neural Networks (ANNs) including Multi-Layer Perceptron (MLP), General Regression Neural Network (GRNN), Group Method of Data Handling (GMDH), Random Forest (RF) and two Quantile Regression (QR)-based hybrids including Quantile Regression Neural Network (QRNN) and Quantile Regression Random Forest (QRRF). The results indicate that the proposed PSOQRNN outperformed these models in terms of Mean Squared Error (MSE), on a majority of the eight financial time series including exchange rates of USD versus JPY, GBP, EUR and INR, Gold Price, Crude Oil Price, Standard and Poor 500 (S&P 500) Stock Index and NSE India Stock Index considered here. It was corroborated by the Diebold–Mariano test of statistical significance. It also performed well in terms of other important measures such as Directional Change Statistic (Dstat) and Theil's Inequality Coefficient. The superior performance of PSOQRNN can be attributed to the role played by PSO in obtaining the better solutions. Therefore, we conclude that the proposed PSOQRNN can be used as a viable alternative in forecasting volatility.