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 distr...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 compounds.Contributions for hydrocarbons and hydrocarbon derivatives containing oxygen,nitrogen,chlorine,bromine 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 compounds 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.展开更多
Flash point is a primary property used to determine the fire and explosion hazards of a liquid. New group contribution-based models were presented for estimation of the flash point of alkanes by the use of multiple li...Flash point is a primary property used to determine the fire and explosion hazards of a liquid. New group contribution-based models were presented for estimation of the flash point of alkanes by the use of multiple linear regression(MLR)and artificial neural network(ANN). This simple linear model shows a low average relative deviation(AARD) of 2.8% for a data set including 50(40 for training set and 10 for validation set) flash points. Furthermore, the predictive ability of the model was evaluated using LOO cross validation. The results demonstrate ANN model is clearly superior both in fitness and in prediction performance.ANN model has only the average absolute deviation of 2.9 K and the average relative deviation of 0.72%.展开更多
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...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 contribution 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).展开更多
The modified van der Waals’model which has only one molecular size-dependent parameter is used to calculate the internal pressures of liquids.It is found that the model parameter has very good linear relation with th...The modified van der Waals’model which has only one molecular size-dependent parameter is used to calculate the internal pressures of liquids.It is found that the model parameter has very good linear relation with the molar volume of liquids at normal boiling point.A group contribution method is established for the molar volume of liquids at normal boiling point.Therefore the internal pressures of various liquids can be predicted.On the basis of the generalized Gibbs free energy model for mixing of liquids,proposed by our previous work,a new solubility parameter had been defined,which is equal to the ratio of the cohesive energy density with the square root of internal pressure.This definition is more strict and its range of application is more exten sive than classical Hildebrand solubility parameter.In present work,the values of new solubility parameter for 170 solvents at 298.15 K are obtained.展开更多
文摘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 compounds.Contributions for hydrocarbons and hydrocarbon derivatives containing oxygen,nitrogen,chlorine,bromine 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 compounds 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.
基金Projects(21376031,21075011)supported by the National Natural Science Foundation of ChinaProject(2012GK3058)supported by the Foundation of Hunan Provincial Science and Technology Department,China+2 种基金Project supported by the Postdoctoral Science Foundation of Central South University,ChinaProject(2014CL01)supported by the Foundation of Hunan Provincial Key Laboratory of Materials Protection for Electric Power and Transportation,ChinaProject supported by the Innovation Experiment Program for University Students of Changsha University of Science and Technology,China
文摘Flash point is a primary property used to determine the fire and explosion hazards of a liquid. New group contribution-based models were presented for estimation of the flash point of alkanes by the use of multiple linear regression(MLR)and artificial neural network(ANN). This simple linear model shows a low average relative deviation(AARD) of 2.8% for a data set including 50(40 for training set and 10 for validation set) flash points. Furthermore, the predictive ability of the model was evaluated using LOO cross validation. The results demonstrate ANN model is clearly superior both in fitness and in prediction performance.ANN model has only the average absolute deviation of 2.9 K and the average relative deviation of 0.72%.
文摘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 contribution 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).
文摘The modified van der Waals’model which has only one molecular size-dependent parameter is used to calculate the internal pressures of liquids.It is found that the model parameter has very good linear relation with the molar volume of liquids at normal boiling point.A group contribution method is established for the molar volume of liquids at normal boiling point.Therefore the internal pressures of various liquids can be predicted.On the basis of the generalized Gibbs free energy model for mixing of liquids,proposed by our previous work,a new solubility parameter had been defined,which is equal to the ratio of the cohesive energy density with the square root of internal pressure.This definition is more strict and its range of application is more exten sive than classical Hildebrand solubility parameter.In present work,the values of new solubility parameter for 170 solvents at 298.15 K are obtained.
