Non-electrolyte Organic Compounds Research Articles

Development of Abraham model correlations for dimethyl adipate from measured solubility data of nonelectrolyte organic compounds

ABSTRACT Mole fraction solubilities are reported for acenaphthene, o-acetoacetanisidide, anthracene, benzil, benzoic acid, benzoin, 4-tert-butylbenzoic acid, 1-chloroanthraquinone, 4-chlorobenzoic acid, 2-chloro-5-nitrobenzoic acid, 4-chloro-3-nitrobenzoic acid, 3,4-dichlorobenzoic acid, 3,4-dimethoxybenzoic acid, 3,5-dinitrobenzoic acid, diphenyl sulphone, 2-ethylanthraquinone, 2-naphthoxyacetic acid, 2-hydroxybenzoic acid, N-hydroxyphthalimide, 2-methoxybenzoic acid, 4-methoxybenzoic acid, 3-methylbenzoic acid, 2-methyl-3-nitrobenzoic acid, 3-methyl-4-nitrobenzoic acid, 4-methyl-3-nitrobenzoic acid, 3-nitrobenzoic acid, 4-nitrobenzoic acid, salicylamide, 3,4,5-trimethoxybenzoic acid, trans-stilbene, thioxanthen-9-one and xanthene dissolved in dimethyl adipate at 298.15 K. Results of these measurements, combined with published literature data for adipic acid, glutaric acid and succinic acid, are used to derive predictive Abraham model correlations. The derived correlations back-calculate the observed solubility data to within ±0.12 log units.

Development of Abraham Model Correlations for Solute Transfer into the tert-Butyl Acetate Mono-Solvent and Updated Equations for Both Ethyl Acetate and Butyl Acetate

Experimental solubilities were determined for 31 solid nonelectrolyte organic compounds dissolved in tert-butyl acetate at 298.15 K. Results of the experimental measurements were combined with published mole fraction solubility data for two lipid-lowering medicinal compounds (lovastatin and simvastatin) in order to derive Abraham model expressions for solute transfer into the tert-butyl acetate mono-solvent. The derived correlations provided an accurate mathematical description of the observed experimental data. As part of the current study, previously published Abraham model solvent correlations for both ethyl acetate and butyl acetate were updated using much larger datasets that contained an additional 64 and 35 experimental data points, respectively. The mathematical correlations presented in the current study describe the observed solubility ratios of solutes dissolved in tert-butyl acetate, ethyl acetate, and butyl acetate to within an overall standard deviation of 0.15 log units or less.

Determination of Abraham model correlations for describing solute transfer into the methyl butyrate mono-solvent at 298 K

ABSTRACT Experimental mole fraction solubilities have been determined for 27 crystalline nonelectrolyte organic compounds and for one organometallic compound (ferrocene) dissolved in methyl butyrate at 298.15 K. The crystalline compounds cover a wide range of polarity and hydrogen-bonding character. Abraham model correlations were derived by combining the solubility data measured in the current study with published values retrieved from the chemical and engineering literature. The mathematical correlations determined in the current study were found to back-calculate the observed solubility data to within standard deviations of 0.10 log units (or less).

Abraham Model Correlations for Triethylene Glycol Solvent Derived from Infinite Dilution Activity Coefficient, Partition Coefficient and Solubility Data Measured at 298.15 K

A gas chromatographic headspace analysis method was used to experimentally determine gas-to-liquid partition coefficients and infinite dilution activity coefficients for 29 liquid organic solutes dissolved in triethylene glycol at 298.15 K. Solubilities were also determined at 298.15 K for 23 crystalline nonelectrolyte organic compounds in triethylene glycol based on spectroscopic absorbance measurements. The experimental results of the headspace chromatographic and spectroscopic solubility measurements were converted to gas-to-triethylene glycol and water-to-triethylene glycol partition coefficients, and molar solubility ratios using standard thermodynamic relationships. Expressions were derived for solute transfer into triethylene glycol by combining our measured experimental values with published literature data. Mathematical correlations based on the Abraham model describe the observed partition coefficient and solubility data to within 0.16 log10 units (or less).

Comment on “Group Contribution-Based Method for Determination of Solubility Parameter of Nonelectrolyte Organic Compounds” and “Solubility Parameters of Nonelectrolyte Organic Compounds: Determination Using Quantitative Structure–Property Relationship Strategy”

ADVERTISEMENT RETURN TO ISSUEPREVCorrespondenceNEXTComment on “Group Contribution-Based Method for Determination of Solubility Parameter of Nonelectrolyte Organic Compounds” and “Solubility Parameters of Nonelectrolyte Organic Compounds: Determination Using Quantitative Structure–Property Relationship Strategy”Sierra Rayne*View Author Information Chemologica Research, PO Box 74, 318 Rose Street, Mortlach, Saskatchewan S0H 3EO, Canada*Tel.: + (1) 306 690 0573. Fax: + (1) 306 690 0573. E-mail: [email protected]Cite this: Ind. Eng. Chem. Res. 2013, 52, 10, 3947–3948Publication Date (Web):February 19, 2013Publication History Published online19 February 2013Published inissue 13 March 2013https://doi.org/10.1021/ie400117hCopyright © 2013 American Chemical SocietyRIGHTS & PERMISSIONSArticle Views405Altmetric-Citations3LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (120 KB) Get e-AlertsSUBJECTS:Alkyls,Anions,Hydrogen,Organic compounds,Solubility Get e-Alerts

Reply to “Comment on ‘Group Contribution-Based Method for Determination of Solubility Parameter of Nonelectrolyte Organic Compounds’ and ‘Solubility Parameters of Nonelectrolyte Organic Compounds: Determination Using Quantitative Structure–Property Relationship Strategy’”

ADVERTISEMENT RETURN TO ISSUEPREVCorrespondenceReply to “Comment on ‘Group Contribution-Based Method for Determination of Solubility Parameter of Nonelectrolyte Organic Compounds’ and ‘Solubility Parameters of Nonelectrolyte Organic Compounds: Determination Using Quantitative Structure–Property Relationship Strategy’”Farhad Gharagheizi†‡, Ali Eslamimanesh§, Amir H. Mohammadi*‡∇, and Dominique Richon‡View Author Information† Department of Chemical Engineering, Buinzahra Branch, Islamic Azad University, Buinzahra, Iran‡ Thermodynamics Research Unit, School of Chemical Engineering, University of KwaZulu-Natal, Howard College Campus, King George V Avenue, Durban 4041, South Africa§ Department of Chemical & Biomolecular Engineering, Clarkson University, Potsdam, New York 13699-5705, United States∇ MINES ParisTech, CEP/TEP−Centre Energétique et Procédés, 35 Rue Saint Honoré, 77305 Fontainebleau, France*Tel.: + (33) 1 64 69 49 70. Fax: + (33) 1 64 69 49 68. E-mail: [email protected]Cite this: Ind. Eng. Chem. Res. 2013, 52, 10, 3949Publication Date (Web):February 19, 2013Publication History Published online19 February 2013Published inissue 13 March 2013https://doi.org/10.1021/ie400202tCopyright © 2013 American Chemical SocietyRIGHTS & PERMISSIONSArticle Views390Altmetric-Citations1LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (124 KB) Get e-AlertsSUBJECTS:Electrolytes,Inorganic compounds,Organic compounds,Organometallic compounds,Solubility Get e-Alerts

Gene expression programming strategy for estimation of flash point temperature of non-electrolyte organic compounds

The accuracy and predictability of correlations and models to determine the flammability characteristics of chemical compounds are of drastic significance in various chemical industries. In the present study, the main focus is on introducing and applying the gene expression programming (GEP) mathematical strategy to develop a comprehensive empirical method for this purpose. This work deals with presenting an empirical correlation to predict the flash point temperature of 1471 (non-electrolyte) organic compounds from 77 different chemical families. The parameters of the correlation include the molecular weight, critical temperature, critical pressure, acentric factor, and normal boiling point of the compounds. The obtained statistical parameters including root mean square of error of the results from DIPPR 801 data (8.8, 8.9, 8.9K for training, optimization and prediction sets, respectively) demonstrate improved accuracy of the results of the presented correlation with respect to previously-proposed methods available in open literature.

Determination of Diffusion Coefficient of Organic Compounds in Water Using a Simple Molecular-Based Method

In this study, a new simple three-parameter equation is presented for calculation/prediction of the diffusion coefficient of nonelectrolyte organic compounds in water at infinite dilution. The model variables include three molecular-based descriptors. The model is developed using the genetic function approximation (GFA) method. The GFA is applied to select the parameters of the model from more than 3000 molecular-based parameters. To propose a comprehensive and predictive model, 4728 pure chemical compounds are investigated. Furthermore, several statistical methods are implemented to evaluate the predictive power of the model. The root-mean-square of error and the average relative deviation of the model are approximately equal to 3.13 × 10–6 cm2·s–1 and 3.6%.

A QSPR model for prediction of diffusion coefficient of non-electrolyte organic compounds in air at ambient condition

Evaluation of diffusion coefficients of pure compounds in air is of great interest for many diverse industrial and air quality control applications. In this communication, a QSPR method is applied to predict the molecular diffusivity of chemical compounds in air at 298.15K and atmospheric pressure. Four thousand five hundred and seventy nine organic compounds from broad spectrum of chemical families have been investigated to propose a comprehensive and predictive model. The final model is derived by Genetic Function Approximation (GFA) and contains five descriptors. Using this dedicated model, we obtain satisfactory results quantified by the following statistical results: Squared Correlation Coefficient=0.9723, Standard Deviation Error=0.003 and Average Absolute Relative Deviation=0.3% for the predicted properties from existing experimental values.

Empirical method for estimation of Henry’s law constant of non-electrolyte organic compounds in water

Henry’s law constant is a significant parameter in description of the phase behaviour of the dilute aqueous solutions. In this communication, a reliable empirical method is proposed for representing/predicting the Henry’s law constant (HLC) of 1816 non-electrolyte organic compounds from different chemical families in water within the (293.15 to 298.15) K temperature range. The normal boiling point temperature, critical pressure, number of phenol/enol/carboxyl OH, hydrogen atoms attached to carbon atom, aliphatic groups attached to OH bond, hydrogen atoms attached to carbon atom with hybridisation sp 3 in each compound, and existences of C–N and C–O bonds in each molecule are applied as the parameters of this correlation. The overall absolute average deviation observed on the calculated and predicted Henry’s constant values with respect to experimental ones is about 10% (based on logarithm of HLC values). The simple correlation presented here can be easily applied for rapid estimation of the Henry’s law constants of many of commonly-used organic compounds in water at specified conditions.

Group contribution model for determination of molecular diffusivity of non-electrolyte organic compounds in air at ambient conditions

Determination of diffusion coefficients of pure compounds in air is of great interest for modeling of air pollution control processes. In this communication, a Group Contribution (GC) method is applied to represent/predict the molecular diffusivity of chemical compounds in air at 298.15K and atmospheric pressure. 4661 compounds from various chemical families have been investigated to propose a comprehensive and predictive model. The final model is resulted from coupling the Artificial Neural Network (ANN) with group contributions. Using this dedicated model, we obtain satisfactory results quantified by the following statistical results: Squared Correlation Coefficient=0.995, Standard Deviation Error=0.02, and Average Absolute Deviation=1.4% for the calculated/predicted properties from existing experimental values.

Solubility Parameters of Nonelectrolyte Organic Compounds: Determination Using Quantitative Structure–Property Relationship Strategy

The solubility parameter is considered to be a significant parameter for the chemical industry. In this study, the quantitative structure–property relationship (QSPR) method is applied to develop three models for determination of the solubility parameters of pure nonelectrolyte organic compounds at 298.15 K and atmospheric pressure. To propose comprehensive, reliable, and predictive models, about 1400 data belonging to experimental solubility parameter values of various nonelectrolyte organic compounds are studied. The genetic function approximation (GFA) mathematical approach is applied for selection of proper model parameters (molecular descriptors) and to develop a linear QSPR model. To study the nonlinear relations between the selected molecular descriptors and the solubility parameter, two approaches are pursued: the three-layer feed forward artificial neural networks (3FFANN) and the least square support vector machine (LSSVM). Furthermore, the Levenberg–Marquardt (LM) and genetic algorithm (GA) optimization methods are respectively implemented to optimize the 3FFANN and LSSVM models. Consequently, we obtain three predictive models with satisfactory results quantified by the following statistical parameters: absolute average relative deviation (AARD) of the represented/predicted properties from existing experimental values by the GFA linear equation of 4.6% and squared correlation coefficient of 0.896; AARD of the QSPR-ANN model of 3.4% and squared correlation coefficient of 0.941; and AARD of 3.1% and squared correlation coefficient of 0.947 evaluated by the QSPR-LSSVM model.

Group Contribution-Based Method for Determination of Solubility Parameter of Nonelectrolyte Organic Compounds

The determination of the solubility parameter of organic compounds has been of much significance in the chemical industry. In this study, we propose a predictive method based on the combination of the Group Contribution strategy with the Artificial Neural Network to calculate/estimate the solubility parameter values of about 1620 nonelectrolyte organic compounds at 298.15 K and atmospheric pressure. The chemical functional groups are obtained for various compounds categorized in 81 different chemical families. The final results indicate the following statistical parameters of the presented method: average relative deviation (ARD %) of the determined properties from existing experimental values of 1.5% and a squared correlation coefficient of 0.985. It is finally inferred that the developed model is more accurate and predictive than our previously proposed models based on the Quantitative Structure–Property Relationship algorithm, which yielded 4.6, 3.4, and 3.1 ARD % from experimental values.

Representation and Prediction of Molecular Diffusivity of Nonelectrolyte Organic Compounds in Water at Infinite Dilution Using the Artificial Neural Network-Group Contribution Method

The determination of diffusion coefficients of pure compounds in water at infinite dilution is of utmost interest in chemical and environmental engineering, especially wastewater treatment processes. In this work, the artificial neural network-group contribution (ANN-GC) method is applied to represent and predict the molecular diffusivity of nonelectrolyte organic compounds in water at infinite dilution and 298.15 K. A total of 4852 pure compounds from various chemical families has been investigated to propose a predictive model. The obtained results show the squared correlation coefficient of 0.996, root-mean-square error of about 0.02, and average absolute deviation lower than 1.5 % for the calculated or predicted property from existing experimental values.

QSPR approach for determination of parachor of non-electrolyte organic compounds

In this work, the Quantitative Structure–Property Relationship (QSPR) method is applied to represent/predict the parachor of pure non-electrolyte organic compounds. A Genetic-Algorithm-based Multivariate Linear Regression (GA-MLR) is used to select the most statistically effective molecular descriptors for evaluating this property. To propose a predictive model, 227 pure non-electrolyte organic compounds are investigated. 2.8% absolute average deviation for the represented/predicted parachors of investigated compounds is found from the corresponding experimental values.

Estimation of pure component properties. Part 4: Estimation of the saturated liquid viscosity of non-electrolyte organic compounds via group contributions and group interactions

A new group contribution method for the prediction of pure component saturated liquid viscosity has been developed. The method is an extension of the pure component property estimation techniques that we have developed for normal boiling points, critical property data, and vapour pressures. Predictions can be made from simply having knowledge of the molecular structure of the compound. In addition, the structural group definitions for the method are identical to those proposed for estimation of saturated vapour pressures. Structural groups were defined in a standardized form and fragmentation of the molecular structures was performed by an automatic procedure to eliminate any arbitrary assumptions. The new method is based on liquid viscosity data for more than 1600 components. Results of the new method are compared to several other estimation methods published in literature and are found to be significantly better. A relative mean deviation in viscosity of 15.3% was observed for 813 components (12,139 data points). By comparison, the Van Velzen method, the best literature method in our benchmarking exercise produced a relative mean deviation of 92.8% for 670 components (11,115 data points). Estimation results at the normal boiling temperature were also tested against an empirical rule for more than 4000 components. The range of the method is usually from the triple or melting point to a reduced temperature of 0.75–0.8. Larger than average deviations were observed in the case of molecules with higher rotational symmetry, but no specific correction of this effect was included in this method.

Estimation of the vapour pressure of non-electrolyte organic compounds via group contributions and group interactions

A new group contribution method for the prediction of liquid vapour pressures for non-electrolyte organic compounds is presented. The model represents both a significant improvement and extension of the original method developed by Nannoolal et al. The method was developed with the aid of the Dortmund Data Bank, which contains over 180 000 data points for both solid and liquid vapour pressure (2007). Group parameters were regressed to a training set of nearly 114 000 data points for more than 2330 compounds. As in the case of the method of Nannoolal et al. the new model only requires knowledge about the molecular structure and a single vapour pressure point in order to generate the vapour pressure curve. In the absence of experimental data it is possible to predict the normal boiling point by a method developed earlier by Nannoolal et al. The relative error in pressure was found to be 5.0% (113 888 data points for 2332 compounds) which compares favourably with the previous model (6.6% for 111 757 data points and 2207 compounds).

Estimation of pure component properties: Part 3. Estimation of the vapor pressure of non-electrolyte organic compounds via group contributions and group interactions

A group contribution method for the estimation of the normal boiling point of non-electrolyte organic compounds, which was published earlier, has been the basis for development of subsequent physical property methods. In this work, the model was extended to enable the prediction of vapor pressure data with special attention to the low-pressure region. The molecular structure of the compound and a reference point, usually the normal boiling point, are the only required inputs and enables the estimation of vapor pressure at other temperatures by group contribution. The structural group definitions are similar to those proposed earlier for the normal boiling point, with minor modifications having been made to improve the predictions. Structural groups were defined in a standardized form and fragmentation of the molecular structures was performed by an automatic procedure to eliminate any arbitrary assumptions. The new method is based on vapor pressure data for more than 1600 components. The results of the new method are compared to the Antoine correlative equation using parameters stored in the Dortmund Data Bank, as well as, the DIPPR vapor pressure correlations. The group contribution method has proven to be a good predictor, with accuracies comparable to the correlations. Moreover, because the regression of group contributions was performed for a large number of compounds, the results can in several cases be considered more reliable than those of the correlative models that were regressed to individual components only. The range of the method is usually from about the triple or melting point to a reduced temperature of 0.75–0.8.

Estimation of pure component properties: Part 1. Estimation of the normal boiling point of non-electrolyte organic compounds via group contributions and group interactions

An improved group contribution method for the estimation of the normal boiling point of non-electrolyte organic compounds was developed using experimental data for approximately 2850 components stored in the Dortmund Data Bank (DDB). The new model is based on a method published earlier, which was extended using a steric parameter, additional corrections and group interaction parameters as well as several additional groups for extended range of applicability. The mathematical formalism was modified to allow for separate examination and regression of individual contributions. The results of this separate examination lead to the detection of unreliable data and the definition of further structural groups. For the boiling point prediction, only the molecular structure of the compound is used. The results of the new method are compared to the previous work and several currently used methods and are shown to be far more accurate and reliable. The detailed comparison for a large number of different sets of chemically similar compounds allows one to access the probable estimation error of the different methods. Structural groups were defined in a standardized form and fragmentation of the molecular structures was performed by an automatic procedure to eliminate any arbitrary assumptions.

A new method for the estimation of the normal boiling point of non-electrolyte organic compounds

A group contribution method for the estimation of the normal boiling point of non-electrolyte organic compounds was developed using experimental data for approximately 2500 components stored in the Dortmund Data Bank (DDB). Predictions are based exclusively on the molecular structure of the compound. The results of the new method are compared to currently-used methods and are shown to be far more accurate. Structural groups were defined in a standardized form and the fragmentation of the molecular structures was performed by an automatic procedure to eliminate any arbitrary assumptions.