用对应态基团贡献法估算有机物偏心因子

A new estimation method was proposed by combining the corresponding state principle with the group contribution method through introducing the concept of assumed-critical properties. Combining it with the Reidel equation, a new acentric factor correlation equation （CSGC-Reidel） was developed. Contribution values of 70 groups were obtained by correlating acentric factor data of 228 organic compounds of 14 type substances including saturated hydrocarbons, unsaturated hydrocarbons, cyclanes, aromatics, oxygen compounds, nitrogen compounds, halohydrocarbons, etc. The average error of acentric factor is 3.52% between the literature data and the predicated with the new estimation method.     

定位分布贡献方法估算有机物正常沸点

A new position group contribution model is proposed for the estimation of normal boiling data of organic compounds involving a carbon chain from C2 to C18. The characteristic of this method is the use of position distribution function. It could distinguish most of isomers that include cis- or trans-structure from organic com-pounds. Contributions for hydrocarbons and hydrocarbon derivatives containing oxygen, nitrogen, chlorine, bro-mine and sulfur, are given. Compared with the predictions, results made use of the most common existing group contribution methods, the overall average absolute difference of boiling point predictions of 417 organic com-pounds is 4.2 K; and the average absolute percent derivation is 1.0%, which is compared with 12.3 K and 3.2% with the method of Joback, 12.1 K and 3.1% with the method of Constantinou-Gani. This new position contribution groups method is not only much more accurate but also has the advantages of simplicity and stability.     

用基团贡献+神经网络+颗粒群优化相结合的方法来预测有机化合物的闪点温度

The flash points of organic compounds were estimated using a hybrid method that includes a simple group contribution method (GCM) implemented in an artificial neural network (ANN) with particle swarm optimization (PSO). Different topologies of a multilayer neural network were studied and the optimum architecture was determined. Property data of 350 compounds were used for training the network. To discriminate different substances the molecular structures defined by the concept of the classical group con-tribution method were given as input variables. The capabilities of the network were tested with 155 substances not considered in the training step. The study shows that the proposed GCM+ANN+PSO method represent an excellent alternative for the estimation of flash points of organic compounds with acceptable accuracy (AARD 1.8%; AAE 6.2 K).     

定位贡献方法计算有机物熔点

A new method is proposed based on the position group contribution additivity for the prediction of melting points of covalent compounds. The characteristics of this method are the use of position distribution function, which could distinguish between most isomers including cis or trans structure of organic compounds. Contributions for hydrocarbons and hydrocarbon derivatives containing oxygen, nitrogen, chlorine, bromine and sulfur, are given. Results are compared with those by the most commonly used estimating methods. The average derivation for prediction of normal melting temperature of 730 compounds is 14.46 K, compared to 29.33 K with the method of Joback, and 27.81 K with the method of Constantinou-Gani. The present method is not only more accurate, but also much simpler and more stable.     

Nonlinear state estimation for fermentation process using cubature Kalman filter to incorporate delayed measurements☆

State estimation of biological process variables directly influences the performance of on-line monitoring and op-timal control for fermentation process. A novel nonlinear state estimation method for fermentation process is proposed using cubature Kalman filter (CKF) to incorporate delayed measurements. The square-root version of CKF (SCKF) algorithm is given and the system with delayed measurements is described. On this basis, the sample-state augmentation method for the SCKF algorithm is provided and the implementation of the proposed algorithm is constructed. Then a nonlinear state space model for fermentation process is established and the SCKF algorithm incorporating delayed measurements based on fermentation process model is presented to implement the nonlinear state estimation. Finally, the proposed nonlinear state estimation methodology is applied to the state estimation for penicillin and industrial yeast fermentation processes. The simulation results show that the on-line state estimation for fermentation process can be achieved by the proposed method with higher esti-mation accuracy and better stability.     

PREDICTION OF VAPOR-LIQUID EQUILIBRIA USING UNIFAC BY ON-LINE PROCESSING PARAMETERS

In this paper the group concept and UNIFAC group contribution method have been discussed andextended.A method of on-line data processing for UNIFAC group interaction parameters based on therelevant component properties stored in data base has been proposed.Results of predicting vapor-liquid equilibria for 22 systems by on-line processing parameters are compared with those by original(off-line)parameters,the accuracy of prediction is improved considerably.     

通过官能团选择萃取精馏的溶剂

A method to select solvent for extractive distillation is proposed by UNIFAC group contribution. Solvent selectivity can be divided into two parts: the partial combinatorial solvent selectivity and the partial residual solvent selectivity. The properties of partial combinatorial and residual solvent selectivity are demonstrated. In most cases,the partial residual solvent selectivity is predominant. The candidate groups of solvent can be selected by group interaction parameter using UNIFAC group interaction parameter table as a guide.     

Estimating Hansen solubility parameters of organic pigments by group contribution methods

The Hansen solubility parameters(HSP) are frequently used for solvent selection and characterization of polymers,and are directly related to the suspension behavior of pigments in solvent mixtures.The performance of currently available group contribution(GC) methods for HSP were evaluated and found to be insufficient for computer-aided product design(CAPD) of paints and coatings.A revised and,for this purpose,improved GC method is presented for estimating HSP of organic compounds,intended for organic pigments.Due to the significant limitations of GC methods,an uncertainty analysis and parameter confidence intervals are provided in order to better quantify the estimation accuracy of the proposed approach.Compared to other applicable GC methods,the prediction error is reduced significantly with average absolute errors of 0.45 MPa~(1/2),1.35 MPa~(1/2),and 1.09 MPa~(1/2) for the partial dispersion(δ_D),polar(δ_P) and hydrogen-bonding(δ_H) solubility parameters respectively for a database of 1106 compounds.The performance for organic pigments is comparable to the overall method performance,with higher average errors for δ_D and lower average errors for δ_P and δ_H.     

Solvent Selection for Extractive Distillation by the Universal Quasichemical Functional Group Activity Coefficient(UNIFAC) Group Contribution Method

A method to select solvent for extractive distillation is proposed by UNIFAC group contribution. Solvent selectivity can be divided into two parts: the partial combinatorial solvent selectivity and the partial residual solvent selectivity. The properties of partial combinatorial and residual solvent selectivity are demonstrated. In most cases, the partial residual solvent selectivity is predominant. The candidate groups of solvent can be selected by group interaction parameter using UNIFAC group interaction parameter table as a guide.     

STUDY AND IMPROVEMENT OF RIHANI-DORAISWAMY ESTIMATION METHOD FOR Cp° WITH COMPUTER PROGRAM

Based on the group contribution method of Rihani and Doraiswamy, a program system has been set up for automatically analyzing structures and computing ideal gas heat capacities. The method was verifled by using evaluated literature data of 479 organic compounds. The assessment of its computing precision and applicability has been made and some new group parameters recommended.     

估算纯物质临界温度的新方法

提出了不用沸点 (Tb)的估算临界温度 (Tc)的方法———第 1水平基团法和第 2水平基团法 .对烷烃、烯烃、炔烃和二烯烃、环烷烃、芳香烃、醇、酯、醚、酮、酸、含硫化合物、含氮化合物以及卤烃等 12类物质的32 5个Tc 进行了关联 ,得到方程参数及 70个第 1水平基团对Tc 的贡献值以及 34个第 2水平基团对Tc 的贡献值 .新方法不依赖于Tb 的实验值 ,而用更易得到的相对密度d4 2 0 值 ,同时还对分子中相邻基团间的相互作用及同分异构体进行了校正 .新方法用于极不稳定的精细化学品也有良好的精度     

基团对应状态法(CSGC)用于纯物质饱和蒸气压的估算

将对应态原理与基团贡献法相结合,引入拟临界性质的概念,提出基团对应状态法(Correspounding State with Group Contribution,简称CSGC)。并将其与Riedel方程相结合用于饱和蒸气压的估算,提出新的蒸气压估算方程(CSGC-PR方程)。88种基团的参数由包括饱和烃、不饱和烃、环烃、芳烃、含氧化合物、含硫化合物、含氮化合物、含卤化合物等350种物质5255个饱和蒸气压实验数据关联获得。新模型的估算精度优于现有的对应状态法,不仅对于高碳数分子有良好的估算精度,并对非极性物质能较好地外推高压下的饱和蒸气压。     

基团溶解度参数及有机物汽化热的估算

为了使基团参数具有一值多用的性质,本文根据溶液的晶格理论,定义了基团溶解度参数,并利用该参数对有机物的汽化热进行了估算.结果表明,本文的方法在汽化热的估算精度上比现有的基团加和法在多数情况下有所提高.特别是,利用本文的方法还可以比较准确地估算多官能团有机物的汽化热.     

反相高效液相色谱法测定酚类化合物的正辛醇/水分配系数

应用反相高效液相色谱法测定了几种酚类化合物的正辛醇/水分配系数(Kow),建立了容量因子(k’)与Kow的关系方程,考察了标样化合物结构对测定结果的影响。实验结果表明,反相高效液相色谱法是一种有效测定物质Kow的方法,且标样化合物的结构对测定结果有较大影响,方程logKow=1.647403 logk’+3.292482(R=0.98)较方程logKow=2.042692 logk’+3.298356(R=0.94)对待测物有更好的预测能力,可使logKow值与文献值的平均偏差由0.397降低为0.23。     

用对应状态基团贡献法估算纯物质的饱和蒸汽压

提出一种估算纯物质饱和蒸汽压的新对应状态基团贡献法———CSGC -PC方程 ,用 2 6 1种物质 1177个数据回归出了方程的参数 ,并得到了 94个基团对临界温度和临界压力的贡献值。回归的平均相对误差为 1.81%。该方程仅需物质的正常沸点Tb,对缺乏实验临界数据的热敏性物质和大分子物质尤其适用。     

基团贡献状态方程的开发与热力学模型参数的理论预测

热力学模型是研究流体相行为和热力学性质的重要工具。理论模型的有效应用离不开模型参数的确定。为赋予热力学模型的预测功能，目前的策略一是建立基团贡献(GC)状态方程(EOS)，二是探索热力学模型参数的理论预测方法。围绕先前开发的变阱宽方阱链流体状态方程(SWCF-VR)，采用基团贡献法思路获得了不同基团对模型参数的贡献值，建立了GC-SWCF方程，证实GC-SWCF方程能满意预测纯物质的密度。进一步将似导体屏蔽模型(COSMO)与SWCF结合，基于COSMO方法获得了192种有机化合物的SWCF方程的模型参数，这是一种不依赖实验数据确定模型参数的理论方法。发现COSMO+SWCF能较好地预测纯物质的密度。引入一个与温度无关的二元交互作用可调参数后，GC-SWCF与COSMO+SWCF都可应用于二元混合物密度与气液相平衡的计算中。