液相链烷烃热导率与其结构定量关系

应用密度泛函理论(DFT),在B3LYP/6-31+G(d)水平上对含有5～24个碳原子的部分液相链烷烃进行结构优化和量化计算其分子中各个原子间空间拓扑距离,并构建拓扑距离矩阵。结合分子中各原子的支化度,应用原子的平衡电负性对分子图进行着色,得到新型结构拓扑指数PX_m(m=1,2,3)。采用多元线性回归技术建立液相链烷烃热导率λ与PX_m(m=1,2,3)的定量关系拓扑模型,并用该模型对热导率λ进行预测与估算,结果表明实验值与预测值、估算值均很吻合。同时,采用留一法（leave-one-out）和外检验方法测试模型的内部稳定性和外部预测能力。与文献结果比较,本文所用参数少,计算简便,为液相链烷烃导热的研究提供了一种新方法。     

香茶菜属植物二萜化合物核磁共振碳谱模拟

将原子电性作用矢量(AEIV)和原子杂化状态指数(AHSI)应用于香茶菜属植物二萜化合物核磁共振碳谱(13C NMR)模拟。分别利用多元线性回归(MLR)和人工神经网络(CNN)建立定量结构波谱相关(QSSR)模型,同时采用内部及外部双重验证的办法对所得模型稳定性能进行了深入分析和检验。建模计算值、留一法(LOO)交互校验(CV)预测值和外部样本预测值的复相关系数分别为Rcum=0.9724, QLOO=0.9723, Qext=0.9738(MLR); Rcum=0.9957,Qext=0.9956(CNN)。结果表明：AEIV,AHSI与13C NMR谱化学位移显著相关,且CNN所建模型明显优于MLR。     

Artificial and Hybrid Fuzzy Linear Neural Network‐Based Estimation of Seed Oil Content of Safflower

Inexpensive and rapid methods for measurement of seed oil content by near infrared reflectance spectroscopy (NIRS) are useful for developing new oil seed cultivars. Adopting default multiple linear regression (MLR), the predictions of safflower oil content were made by 20–140 samples using a Perten Inframatic 8620 NIR spectrometer. Although the obtained interpolation results of MLR had desired accuracy, the extrapolation was extremely poor. The extrapolation determination coefficient (R²) and standard error (SE) of cross validation for MLR models were 0.63–0.78 and 3.71–4.44, respectively. In order to overcome the accuracy limitation of linear MLR models, a common suggestion is to use a nonlinear artificial neural network (ANN); however, it needs a large number of data to yield significant accurate results. We developed a novel robust hybrid fuzzy linear neural (HFLN) network to capture simultaneously linear and nonlinear patterns of data with a limited number of safflower samples. Empirical extrapolation results showed that the HFLN had higher R² (=0.85) and lower SE (=1.83) compared to those obtained by MLR and ANN models. It is concluded that hybrid methodologies could be used to construct efficient and appropriate models for estimation of seed oil content set up on NIR system.     

Fourier Transform Near Infrared Spectroscopy as a Quality Control Tool for the Analysis of Lecithin and By-Products During Soybean Oil Processing

Fourier transform near infrared (FT-NIR) spectroscopy was used to analyze multiple measurement parameters in lecithin production samples and soybean oil refining by-products. For lecithin, partial least squares (PLS) calibration models were developed for acetone insolubles, acid value and moisture and leave-one-out cross validation of the calibration models yielded root mean square error of cross validation (RMSECV) values of 0.37%, 0.59 (mg KOH/g) and 0.050%, respectively. An independent test set consisting of 40% of the lecithin production samples were predicted from the PLS calibration models and a root mean square error of prediction (RMSEP) of 0.41%, 0.53 (mg KOH/g) and 0.056% were obtained for acetone insolubles, acid value and moisture, respectively. Comparison of FT-NIR predictions and corresponding reference method values of 10 lecithin samples using a two-tailed t test showed no significant difference at the p = 0.05 level. A set of 51 samples of soybean oil refining by-products, including acidulated soapstock, fatty acids and black oil, were used for developing PLS calibration models for measuring acid value, moisture and iodine value and leave-one-out cross validations for each model gave values for RMSECV of 6.59 (mg KOH/g), 0.046% and 0.42 (mg I₂/g), respectively. Overall, the results of this study demonstrate the suitability of FT-NIR spectroscopy for the routine analysis of lecithin production samples and soybean oil refining by-products for quality control purposes.     

分子电性距离矢量预测金线莲挥发油成分结构表征及色谱保留值

采用分子电性距离矢量(molecular electro-negativity distance vector,MEDV)对金线莲挥发油中分离的72种化合物进行了结构表征,并采用SPSS统计处理软件对变量进行了逐步回归(SMR)分析,建立了4变量的定量结构-色谱保留(quantitative structure retention relationship,QSRR)相关模型,同时采用内部及外部双重验证的办法对所建模型稳定性进行了分析和验证,建模计算值、留一法(leave-one-out,LOO)交互检验预测值和外部样本预测值的复相关系数R、RLOO、Qext分别为0.959,0.947,0.913。结果表明,MEDV能较好地表征非同类化合物的分子结构信息,所建模型具有良好的稳定性和预测能力,将其用于中药化学成分分离、分析、结构表征及其药用价值的有效开发,具有重要的理论指导意义。     

Burning Characteristics of AP/HTPB Composite Propellants Prepared with Fine Porous or Fine Hollow Ammonium Perchlorate

Fine porous and hollow ammonium perchlorate (AP) particles were prepared by the spray‐drying method. Propellants prepared with porous or hollow AP were found to have bubble contamination. The bubble in the propellant appeared inside the porous and hollow AP particles because the voids in porous and hollow AP cannot be completely filled with HTPB. The relationship between the burning rate and the weight mean diameter, D_w, and the specific surface area, S_w, is divided into two regions. The burning rate was almost constant above the critical D_w and increased with decreasing D_w below that. The burning rate was almost constant below the critical S_w and increased with increasing S_w above that. These critical points did not depend on the voids in the AP particles. The burning rate of the propellant prepared with spherical AP was dependent on D_w and S_w. The burning rates of the propellants prepared with porous or hollow AP were not associated with D_w or S_w alone and were greater than that of the propellant prepared with spherical AP at a constant D_w or S_w. The voids in porous and hollow AP particles thus had a positive effect on the burning rate.     

载气流量及升温速率对污染土壤中多氯联苯热脱附的影响

利用小型管式炉进行了载气流量和升温速率对多氯联苯污染土壤的热脱附过程影响的实验研究。结果表明流量的增大对多氯联苯含量和毒性当量的去除效率影响不大,载气流量小于400 ml·min^-1时,气相中的脱附量明显增大,载气流量大于400 ml·min^-1则脱附量变化较小,而多氯联苯的毒性当量则随着载气流量增大呈线性增加趋势。实验结果还表明污染土壤中多氯联苯变化速率与升温速率呈明显的正线性相关,随着升温速率增加,污染土壤中多氯联苯去除效率总体呈上升趋势,毒性当量去除效率降低。总体结果分析可以看到升温速率越大,总体效果也越好。污染土壤经热脱附处理后气固相的二 英毒性当量则有不同程度提升,尤其气相内检测到了大量多氯二苯并呋喃生成。     

Chemical Conversion Pathways and Kinetic Modeling for the OH-Initiated Reaction of Triclosan in Gas-Phase

As a widely used antimicrobial additive in daily consumption, attention has been paid to the degradation and conversion of triclosan for a long time. The quantum chemistry calculation and the canonical variational transition state theory are employed to investigate the mechanism and kinetic property. Besides addition and abstraction, oxidation pathways and further conversion pathways are also considered. The OH radicals could degrade triclosan to phenols, aldehydes, and other easily degradable substances. The conversion mechanisms of triclosan to the polychlorinated dibenzopdioxin and furan (PCDD/Fs) and polychlorinated biphenyls (PCBs) are clearly illustrated and the toxicity would be strengthened in such pathways. Single radical and diradical pathways are compared to study the conversion mechanism of dichlorodibenzo dioxin (DCDD). Furthermore, thermochemistry is discussed in detail. Kinetic property is calculated and the consequent ratio of k_add/k_total and k_abs/k_total at 298.15 K are 0.955 and 0.045, respectively. Thus, the OH radical addition reactions are predominant, the substitute position of OH radical on triclosan is very important to generate PCDD and furan, and biradical is also a vital intermediate to produce dioxin.     

Artificial Neural Networks Modeling of Ozone Bubble Columns: Mass Transfer Coefficient,Gas Hold-Up,and Bubble Size

This study aims at applying artificial neural network (ANN) modeling approach in designing ozone bubble columns. Three multi-layer perceptron (MLP) ANN models were developed to predict the overall mass transfer coefficient (k_La, s^?1), the gas hold-up (? _G , dimensionless), and the Sauter mean bubble diameter (d_S , m) in different ozone bubble columns using simple inputs such as bubble column's geometry and operating conditions. The obtained results showed excellent prediction of k_La, ? _G , and d_S values as the coefficient of multiple determination (R² ) values for all ANN models exceeded 0.98. The ANN models were then used to determine the local mass transfer coefficient (k_L , m.s^?1). A very good agreement between the modeled and the measured k_L values was observed (R² ?=?0.85).     

Perspectives on the formation of polychlorinated dibenzo-p-dioxins and dibenzofurans during municipal solid waste (MSW) incineration and other combustion processes

The pathways by which polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) are formed and the interactions between their aromatic precursors, in particular chlorophenols (ClPhs), and transition metal catalysts are discussed. A literature survey and data from pilot-scale combustion experiments allow conclusions to be drawn on the relations between ClPhs and PCDD/Fs in municipal waste incineration and other combustion processes. The results suggest that the ClPh pathway is among the most important for the formation of PCDD/Fs.     

五氯酚在飞灰表面低温反应生成二口恶英特性

在管式炉上研究了不同试验条件飞灰/五氯酚生成二口恶英的分布特性.采用色质联机(HRGC/LRMS)测定了PCP中以及生成产物中的二口恶英含量.结果表明，生成产物中的二口恶英主要以气态形式存在，总的二口恶英中以PCDDs为主，比例高于97％，PCDDs中主要同系物是六至八氯代PCDDs.分析了飞灰含量以及氧含量对二口恶英生成的影响，二口恶英生成量随着飞灰中含碳量的增加而增大，氧含量是控制二口恶英生成的关键因素，氧含量在6.7％时生成的二口恶英总量及毒性当量值最小.对试验中产生的二口恶英进行了质量平衡，为进一步研究垃圾焚烧过程中二口恶英排放以及分布特性打下基础.     

医疗废物焚烧炉启炉过程二噁英排放特性

选择了位于华东地区的某医疗废物焚烧处置设施开展启炉过程与正常工况下烟气和飞灰的二噁英排放特性对比研究。数据显示, 启炉后期烟气中二噁英的浓度达到1.68 ng I-TEQ·m^-3, 在焚烧炉温度稳定以后12 h, 达到2.77 ng I-TEQ·m^-3, 飞灰中二噁英毒性当量水平也达到4.5 ng I-TEQ·g^-1。启炉过程中烟气中气相二噁英所占比例逐渐增加, 从平均占到50%增加到超过90%。启炉过程中烟气二噁英排放速率高于其正常达标时的排放水平, 最高值为58.1 mg I-TEQ·h^-1, 超过正常排放的40倍。一个启炉周期二噁英的排放总量达到0.785 mg I-TEQ, 达标正常工况下二噁英的年排放总量为8.4 mg I-TEQ, 按照平均每年3次启炉来计算, 启炉过程二噁英的排放量占到全年正常排放的28%。     

金属化合物催化多环芳烃合成二噁英的机理

为研究飞灰中金属化合物催化多环芳烃合成二噁英的机理,进行了不同催化剂和苊的燃烧试验,同时进行了X射线衍射试验(XRD)和热重试验(TGA)。根据试验结果分析得到：多环芳烃主要以de novo反应合成二噁英, PCDFs占主要成分;在无氯气氛下,CuCl₂绝大部分还原生成CuCl,金属氯化物主要通过金属配位体提供氯源;CuCl₂和FeCl₃对催化裂解氧化苊的作用相似;CuCl₂在150～200℃就可以和苊催化反应生成二噁英或氯代有机物。     

多溴代二苯并呋喃/噻吩热力学性质的定量构效关系

多溴代二苯并呋喃(PBDFs)是剧毒环境污染物,主要来源于溴系阻燃剂的燃烧和高温裂解过程,其性质与其结构有关;多溴代二苯并噻吩(PBDTs)的结构与其非常相似。通过计算多溴代二苯并呋喃和多溴代二苯并噻吩254个分子的原子特征值,利用分子图形学技术获得了一种新的连接性指数——路径指数mP,采用多元回归分析方法建立了PBDFs的分子总能量(ET)、标准焓(H0)、自由能(G0)、标准熵(S0)和恒容热容(c0v)以及PB-DTs的标准焓(H0)、自由能(G0)、标准生成焓(ΔfH0)和标准生成吉布斯自由能(ΔfG0)的定量结构-性质相关模型,相关性良好(r20.995),利用Jackknifed法检验了模型的稳定性和预测能力,Jackknifed检验的相关系数r2均在0.995以上,对标准熵预测的相对平均误差为0.52%,预测结果和文献值基本吻合。     

Experimental investigation of hysteretic dynamic effect in capillary pressure–saturation relationship for two‐phase flow in porous media

Well‐defined laboratory experiments have been carried out to investigate hysteretic dynamic effect in capillary pressure–saturation relationships for two‐phase flow in homogeneous and heterogeneous (layered) porous media. Conceptually, the dependence of the capillary pressure curves on the rate of change of saturation (dS_w/dt) is defined as the dynamic effect in capillary pressure relationship, which is indicated by a dynamic coefficient, τ (Pa s) and it determines the rate at which two‐phase flow equilibrium is reached, i.e., dS_w/dt = 0 where S_w and t are the water saturation and time, respectively. The dependences of τ on various fluid and porous materials properties have been studied in the context of drainage; but, there is limited study for imbibition and the hysteresis of τ?S_w relationships. As such, the emphasis in this article is on reporting τ?S_w curves for imbibition while also demonstrating the hysteresis in the τ?S_w relationships by comparing τ?S_w curves for drainage (previously reported) and imbibition (this study) in carefully designed laboratory experiments. Homogeneous sand samples composed of either fine (small particle size and lower permeability) or coarse (larger particle size and higher permeability) sand have been used for these experiments. Furthermore, a layered domain made of a find sand layer sandwiched between two coarse sand layers is used as a model of heterogeneous domain. The results of the study confirm that the τ?S_w relationships are hysteretic in nature and, as such, the speed to flow equilibrium should vary depending on whether drainage or imbibition takes place. At a particular water saturation, the magnitudes of the dynamic coefficient (τ) are found to be generally higher for imbibition, which imply that the speed to flow equilibrium at the same saturation will be slower for imbibition. © 2013 The Authors. AIChE Journal, published by Wiley on behalf of the AIChE. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. AIChE J, 59: 3958–3974, 2013     

Development of support vector regression (SVR)-based model for prediction of circulation rate in a vertical tube thermosiphon reboiler

The hydrodynamics and heat transfer in a thermosiphon reboiler interact with each other making the process very complex. Prediction of the rates of heat transfer and thermally induced flow are the primary requirements for the design of thermosiphon reboilers. The objective of this study was to develop, for the first time, a unified data-driven model, for the prediction of circulation rate in a thermosiphon reboiler for different pure components with wide variation in thermo-physical properties and operating parameters, using support vector regression (SVR)-based modeling technique. In the present work, 148 experimental data points from accessible sources, including the author's own study were used. First, a multiple regression (MR) model for circulation rate (in the form of Reynolds number) was developed as a function of dimensionless parameters namely, Peclet number for boiling (Pe_b), Subcooling number (K_sub), and the Lockhart–Martinelli parameter (X_tt), followed by the formulation of an SVR-based model. Statistical analysis revealed that the proposed generalized SVR-based model had high prediction accuracy with an average absolute relative error (AARE) of 3.82%, root mean square error (RMSE) of 0.0717, leave-one-out cross validation (Q²_LOO) of 0.9975 and mean relative error (MRE) of 0.0288 on the training data. Corresponding values of 6.11% AARE, 0.0816 RMSE, 0.9991 leave-one-out cross validation on test data (Q²_ext) and 0.0541 MRE were obtained for the test data. A comparison of the SVR-based correlation was made with the MR model and with some selected empirical correlations in the literature. It was observed that the proposed SVR-based model significantly exhibited an enhanced prediction and generalization performance.     

Dynamic effects in capillary pressure relationships for two‐phase flow in porous media: Experiments and numerical analyses

Well defined experiments and numerical analyses are conducted to determine the importance of dynamic effect in capillary pressure relationships for two‐phase flow in porous media. Dynamic and quasi‐static capillary pressure‐saturation (P^c‐S_w) and, ?S_w/?t‐t curves are determined. These are then used to determine the dynamic effects, indicated by a dynamic coefficient (τ) in the porous domains which establishes the speed at which flow equilibrium (?S_w/?t = 0) is reached. τ is found to be a nonlinear function of saturation which also depends on the medium permeability. Locally determined τ seems to increase as the distance of the measurement point from the fluid inlet into the domain increases. However, the functional dependence τ‐S_w follows similar trends at different locations within the domain. We argue that saturation weighted average of local τ‐S_w curves can be defined as an effective τ‐S_w curve for the whole domain which follows an exponential trend too. © 2012 The Authors. AIChE Journal, published by Wiley on behalf of the AIChE. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. AIChE J, 58: 3891–3903, 2012