Properties Of Pure Compounds Research Articles

Experimental Study of Electrical Properties of Pharmaceutical Materials by Electrical Impedance Spectroscopy

The physicochemical characterization of pharmaceutical materials is essential for drug discovery, development and evaluation, and for understanding and predicting their interaction with physiological systems. Amongst many measurement techniques for spectroscopic characterization of pharmaceutical materials, Electrical Impedance Spectroscopy (EIS) is powerful as it can be used to model the electrical properties of pure substances and compounds in correlation with specific chemical composition. In particular, the accurate measurement of specific properties of drugs is important for evaluating physiological interaction. The electrochemical modelling of compounds is usually carried out using spectral impedance data over a wide frequency range, to fit a predetermined model of an equivalent electrochemical cell. This paper presents experimental results by EIS analysis of four drug formulations (trimethoprim/sulfamethoxazole C14H18N4O3-C10H11N3O3, ambroxol C13H18Br2N2O.HCl, metamizole sodium C13H16N3NaO4S, and ranitidine C13H22N4O3S.HCl). A wide frequency range from 20 Hz to 30 MHz is used to evaluate system identification techniques using EIS data and to obtain process models. The results suggest that arrays of linear R-C models derived using system identification techniques in the frequency domain can be used to identify different compounds.

Melting properties of amino acids and their solubility in water.

The state-of-the-art unit operation for separation and purification of amino acids is still crystallization, which requires solubility data and melting properties of pure compounds. Since measuring solubility is time-consuming, prediction tools are desired. Further, melting properties are not yet available due to decomposition of amino acids upon slow heating. In this work, melting properties of twenty amino acids (except Met) were measured by Fast Scanning Calorimetry (FSC) with heating rates up to 20 000 K s−1. PC-SAFT was used to predict interactions in amino acid + water systems. Additionally, solubility, pH, and PXRD was measured. By combining FSC and PC-SAFT, the solubility of 15 amino acids was successfully predicted in a wide temperature range in good agreement with the experimental data. Thus, this work provides melting properties of amino acids for the first time and highlights the usefulness of such data to predict material properties such as aqueous solubility of amino acids.

A comprehensive description of single-phase and VLE properties of cryogenic fluids using molecular-based equations of state

A complete description of fluid-phase thermodynamic properties at cryogenic conditions undoubtedly presents a serious challenge for equations of state (EOSs). This work is focused on comparing the capabilities of two Statistical Associating Fluid Theory-based EoSs, namely PC-SAFT, SAFT + Cubic, and one cubic model, the original PR EOS, in correlating and predicting various thermodynamic properties of 14 main cryogenic fluids (noble gases, light hydrocarbons, nitrogen, oxygen, carbon dioxide, carbon monoxide, and nitrous oxide). Additionally, the available low temperature vapor-liquid equilibrium (VLE) data of their binary and ternary mixtures are also evaluated in this comparative study. It has been found that, apart from the critical and near-critical data, PC-SAFT has a clear advantage in modeling the pure compound properties such the sound velocity and density (with the overall AADs% less than 7%). Nevertheless, the overestimation of the single phase properties in low temperature and high pressure regions and the poor accuracy in modeling the high pressure VLE compositions of binary mixtures are two major drawbacks of PC-SAFT. SAFT + Cubic is less accurate in predicting pure compound properties; however, having small values of binary interaction parameters, it is slightly more accurate than PC-SAFT in modeling various VLE isotherms of mixtures in a predictive manner (with the overall AADs around 3%). At the same time, PR EOS exhibits the most significant deviations from the low temperature experimental data of both pure cryogens and their mixtures. However, it yields particularly accurate predictions of isochoric heat capacities in the liquid phase.

First-Principles Study of Optoelectronic Properties of the Noble Metal (Ag and Pd) Doped BiOX (X = F, Cl, Br, and I) Photocatalytic System

To explore the photocatalytic performances and optoelectronic properties of pure and doped bismuth oxyhalides D-doped BiOX (D = Ag, Pd; X = F, Cl, Br, I) compounds, their atomic properties, electronic structures, and optical properties were systematically investigated using first-principles calculations. In previous experiments, the BiOX (X = Cl, Br) based system has been observed with enhanced visible light photocatalytic activity driven by the Ag dopant. Our calculations also show that the potential photocatalytic performance of Ag-doped BiOCl or BiOBr systems is enhanced greatly under visible light, compared with other Pd-doped BiOX (X = Cl, Br) compounds. Furthermore, it is intriguing to find that the Pd-doped BiOF compound has strong absorption over the infrared and visible light spectrum, which may offer an effective strategy for a promising full spectrum catalyst. Indicated by various Mulliken charge distributions and different impurity states in the gap when Ag or Pd was doped in the BiOX compounds, we notice that all D-doped BiOXs exhibit a p-type semiconductor, and all impurity levels originated from the D-4d state. The charge transfer, optoelectronic properties, and absorption coefficients for photocatalytic activities among D-doped BiOX photocatalysts caused by the electronegativity difference of halide elements and metal atoms will finally affect the photocatalytic activity of doped BiOX systems. Therefore, it is significant to understand the inside physical mechanism of the enhanced Ag/Pd-doped BiOX photocatalysts through density functional theory.

A Computer-Aided Methodology for Mixture-Blend Design. Applications to Tailor-Made Design of Surrogate Fuels

Modern society needs various chemical products for its survival. The chemical products are classified in terms of single species products, multiple species products, and devices. Multiple species products such as mixtures and blends are one of the most widely used chemical products. However, the common design methods for this kind of product are still mostly by trial and error or by rule-based approaches. A computer-aided methodology integrated with experimental verification is presented in this article. In the first step of this methodology, model-based computer-aided techniques are employed to the design of mixtures and blends. In the second step, the properties of the most promising product candidates are verified through experiments and/or rigorous models. The starting point is to analyze the product needs and translate them into target property constraints. A list of molecules that serve as ingredient-chemicals for addition to the blended product together with their pure compound properties are gener...

Systematic identification method for data analysis and phase equilibria modelling for lipids systems

Abstract Industrial use of lipids has been increasing as a consequence of increased developments related to bio-based economies. In addition to applications in food-products, lipids are used by many industrial sectors, for example, biodiesel, edible oil, health, and personal care. Phase equilibria predictions for chemical systems with lipids play a major role in process–product modelling, simulation and design. Due to the large number of lipid-compounds involved, predictive methods like group contribution based methods are particularly suitable for estimation of pure compound and mixture properties that may not be available. Limited experimental data availability and poor performances of currently available group contribution based methods is therefore an obstacle for obtaining the necessary information regarding phase equilibria of chemical systems with lipids. In this paper, a systematic identification-regression method (to be called identification method) for phase equilibrium modelling, where, based on the available experimentally measured phase equilibrium data, the selected model parameters are estimated in a hierarchical and efficient manner, is presented. The aim of the method is to improve the quality of phase equilibria prediction for the selected group contribution based methods. By applying the identification method, a new set of binary group interaction parameters regressed from vapour-liquid equilibrium data for chemical systems with lipids is presented for the Original UNIFAC model, together with regression statistics and model performance. An extended and updated version of the in-house SPEED Lipids database, which is used for the needed pure compound properties and phase equilibria data, is also presented.

The Antoine equation of state: Rediscovering the potential of an almost forgotten expression for calculating volumetric properties of pure compounds

Antoine is mainly known for the equation usually used for predicting vapor pressure of pure compounds that bears his name. In this article we show a little known equation of state (EoS), as well as its functionality to predict current PvT properties of more than forty compounds including industrial, noble, and organic gases. The Antoine EoS has been parameterized in three regions: Pr<1.2,1.2⩽Pr⩽10 and Pr>10 in order to improve its performance in the widest possible area. The proposed sets of optimized parameters were fitted by minimizing deviations after comparing predicted values with available experimental data in open literature.The volumes predicted with the optimized Antoine EoS have been compared with those calculated with the widely-known Soave-Redlich-Kwong (SRK), Peng-Robinson-Stryjek-Vera (PRSV2) and Valderrama-Patel-Teja (VPT) equations of state. Results obtained by using the optimized Antoine EoS show better accuracy in the zone of high reduced pressures for all compounds and, in a more general way, for most of the compounds in the remaining zones than the other equations of state. The extension to noble gases and other compounds originally not taken into account by Antoine have been successfully achieved.

Estimating the Physicochemical Properties of Polysubstituted Aromatic Compounds Using UPPER

The UPPER model (Unified Physicochemical Property Estimation Relationships) has been used to predict 9 essential physicochemical properties of pure compounds. It was developed almost 25 years ago and has been validated by the Yalkowsky group for almost 2000 aliphatic, aromatic, and polyhalogenated hydrocarbons. UPPER is based on a group of additive and nonadditive descriptors along with a series of well-accepted thermodynamic relationships. In this model, the 2-dimensional chemical structure is the only input needed. This work extends the applicability of UPPER to hydrogen bonding and non-hydrogen bonding aromatic compounds with several functional groups such as alcohol, aldehyde, ketone, carboxylic acid, carbonate, carbamate, amine, amide, nitrile as well as aceto, and nitro compounds. The total data set includes almost 3000 compounds. Aside from the enthalpies and entropies of melting and boiling, no training set is used for the calculation of the properties. The results show that UPPER enables a reasonable estimation of all the considered properties.

Hydrate Equilibrium Modelling with the Cubic two-state Equation of State

A combination of the cubic two-state equation of state and the van der Waals–Platteeuw model was employed for the description of the hydrate formation thermodynamics, with and without inhibitors. The model parameters were determined from the properties of pure compounds and from phase equilibrium data of binary gas–water and water–inhibitor mixtures. With these parameters, predictions were performed for multicomponent gas–water–inhibitor systems. For single-gas hydrates, the average absolute deviations found for equilibrium pressure did not exceed 8%, whereas for multi-gas hydrates, these deviations were 23% maximum. The proposed model produced good predictions in the presence of inhibitors (methanol, ethanol, ethylene glycol and triethylene glycol), with increasing deviations at higher concentrations of inhibitors.

Artificial Neural Network Based Group Contribution Method for Estimating Cetane and Octane Numbers of Hydrocarbons and Oxygenated Organic Compounds

Chemical pathways for converting biomass into fuels produce compounds for which key physical and chemical property data are unavailable. We developed an artificial neural network based group contribution method for estimating cetane and octane numbers that captures the complex dependence of fuel properties of pure compounds on chemical structure and is statistically superior to current methods.

Studying of drug solubility in water and alcohols using drug-ammonium ionic liquid-compounds

Synthesis of three mefenamic acid (MEF) derivatives - ionic liquid compounds composed of MEF in an anionic form and ammonium cation (choline, MEF1), or {di(2-hydroxyethyl)dimethyl ammonium (MEF2)}, or {tri(2-hydroxyethyl)methyl ammonium compound (MEF3)} is presented. The basic thermal properties of pure compounds i.e. fusion temperatures, and the enthalpy of fusion of these compounds have been measured with differential scanning microcalorimetry technique (DSC). Molar volumes have been calculated with the Barton group contribution method. The solubilities of MEF1, MEF2 and MEF3 using the dynamic method were measured at constant pH in a range of temperature from (290 to 370) K in three solvents: water, ethanol and 1-octanol. The experimental solubility data have been correlated by means of three commonly known GE equations: the Wilson, NRTL and UNIQUAC with the assumption that the systems studied here present simple eutectic behaviour. The activity coefficients of pharmaceuticals at saturated solutions in each binary mixture were calculated from the experimental data. The formation of MEF-ionic liquid compounds greatly increases the solubility in water in comparison with pure MEF or complexes with 2-hydroxypropyl-β-cyclodextrin. The development of these compounds formulations will assist in medication taking into account oral solid or gel medicines.

Electrical, electrochemical and thermal properties of the ionic liquid + lactone binary mixtures as the potential electrolytes for lithium-ion batteries

Electrical conductivity of four binary mixtures containing 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ionic liquid, [bmim][NTf2], with selected lactones, namely: β-butyrolactone (BBL), γ-valerolactone (GVL), δ-valerolactone (DVL) and ε-caprolactone (ECL) was measured at temperatures from (293.15 to 323.15) K at atmospheric pressure (p=0.1MPa) over the whole composition range. The effects of the temperature and ionic liquid (IL) concentration on the electrical conductivity were correlated using Casteel-Amis and Arrhenius equations. It was found that addition of lactone does not reduce electrochemical stability of investigated solution. In order to determine the flammability of the mixtures, the electrolyte self-extinguishing time (SET) was measured and evaluated. DSC was used to determine thermophysical properties of pure compounds and mixtures such as phase transition temperatures and changes in heat capacities. Different heating rates were used to evaluate the kinetic events. Determination of these properties for investigated systems is relevant for their possible applications in the field of electrochemistry.

Exploiting biological activities of brown seaweed Ishige okamurae Yendo for potential industrial applications: a review

Functional products such as cosmeceuticals, functional foods, and nutraceuticals with natural ingredients have more market demand than their synthetic counterparts due to the lower side effects and health-promoting properties associated with the natural functional ingredients. Ishige okamurae is an edible brown seaweed growing on rocks in the upper and middle intertidal zones of rough open coasts in Korea, Japan, and China. Studies carried out to isolate and evaluate the bioactive properties of crude and pure compounds from I. okamurae have shown promising results under in vitro and in vivo conditions. As a result, I. okamurae has recently gained considerable attention as a functional material in industries such as functional foods, nutraceuticals, and cosmeceuticals. However, the promising health effects associated with the extracts and pure compounds isolated from I. okamurae have not been reviewed to date. Herein, the authors review some health-promoting properties of crude and pure compounds from this seaweed, including anti-cancer, anti-oxidant, anti-inflammation, anti-HIV, anti-diabetic, anti-obesity, and anti-MMP activities. Thus, this review might serve to increase the utilization of this invaluable natural resource as an ingredient in the aforementioned industries.

Generalized models for predicting the critical properties of pure chemical compounds

Critical properties of chemical compounds are of great importance as they are necessary for estimating large variety of thermodynamic and physical properties by equations of state or theorem of corresponding states. These properties are important in optimum design, operation and control of every piece of equipment in petroleum and chemical industries. In this communication, four intelligent models including radial basis function (RBF) and multilayer perceptron (MLP) neural networks, least square support vector machine (LSSVM) and hybrid group method of data handling type neural network (GMDH-PNN) are used to develop predictive models for estimation of the critical properties of pure compounds including critical temperature, critical pressure, and critical volume. A comprehensive data set of 563 pure compounds from 13 different chemical groups has been used to develop rigorous and reliable predictive models. Three easily measurable properties (normal boiling point, molecular weight, and specific gravity) were chosen as input parameters of the proposed models. The results illustrate that all of the developed models have high accuracy in predicting the critical properties, while the developed RBF models are the most accurate ones and GMDH-PNN models are the simplest models in the form of simple mathematical correlations. Comparison of the proposed models in this study with the previously developed models shows the high superiority of the proposed models. The influence degree of each input parameter on the models' outputs was investigated quantitatively using the relevancy factor. Finally, the Leverage approach was used to find out applicability domain and probable outliers of the developed models. It was found that only small percent of the data are located out of the applicability domain of the developed models.

Study Approach of Antioxidant Properties in Foods: Update and Considerations.

The assessment of interactions between natural antioxidants and other food matrix components represents the main step in the investigation of total antioxidant properties, in terms of potential health benefits. The diversity of chemical structures of natural compounds, besides their possible interactions, as well as the biological role and different modes of action makes it difficult to assess a single and reliable procedure for the evaluation of antioxidant activity. Today, much attention is given to the distinction between extractable and non-extractable antioxidants as a key tool in the description of the nutritional and healthy properties of food matrices. The starting point for the investigation of antioxidant effects of food extracts is the analysis of antioxidant properties of pure compounds and their interactions. Another complementary approach could be represented by the study of how different biologically active compound-rich extracts contribute to the total antioxidant capacity.

Application of the modified Group-Contribution Perturbed-Chain SAFT to branched alkanes, n-olefins and their mixtures

A new empirical approach has been developed to estimate parameters of the modified Group Contribution Perturbed-Chain statistical associating fluid theory (mg-SAFT) for alkane and alkene isomers. A key advantage of this approach is that the molecular parameter of isomer components is distinguished simply through the chain length parameter. New group parameters for 1-alkenes, cis- and trans-alkenes, methyl-alkanes and dimethyl-alkanes are determined. Several pure compound properties such as the vapor pressure, liquid density, enthalpy of vaporization, heat capacities are predicted. It has been found that the use of two adjustable parameters in determining the chain length parameters of different isomer groups in the fitting procedure for alkane or alkene isomers is enough to provide a good description of PVT and some derivative properties. Test and comparison with other existing SAFT-based group-contribution approaches were performed in calculating the vapor pressure and saturated liquid density of heavy compounds. The results show that, mg-SAFT describes the fluid phase behavior for light compounds with a comparable accuracy compared to other group contribution approaches and much better for heavier compounds (prediction results).

A modified group-contribution PC-SAFT equation of state for prediction of phase equilibria

The group contribution (GC) method proposed by Tamouza et al. (Fluid Phase Equilibria 222–223, (2004), 67–76) has been improved to estimate parameters of the Perturbed-Chain statistical associating fluid theory (hereby called mg-SAFT). The improvement is the “exclusion” of the over-accounting of dispersion energy between intra-molecular segments through an empirical correlation parameter. We have treated three hydrocarbon families (n-alkanes, n-alkyl-cycloalkanes and n-alkyl-benzenes); several pure compound properties such as the enthalpy of vaporization, single-phase density, speed of sound, heat capacities are predicted. The results indicate that most pure compound property predictions are satisfactory, mg-SAFT appears to offer a systematic improvement as compared to the original GC-PC-SAFT approach, but no improvement in prediction of speed of sound. Vapor-liquid equilibria of some binary mixtures are purely predicted using the mg-SAFT (kij = 0). Good agreements between the model predictions and the experimental data were found. Comparison with other existing SAFT-based group contribution approach was performed in calculating vapor pressure and saturated liquid density of heavy hydrocarbon; mg-SAFT demonstrated significant improvements in accuracy.

Development of the translated-consistent tc-PR and tc-RK cubic equations of state for a safe and accurate prediction of volumetric, energetic and saturation properties of pure compounds in the sub- and super-critical domains

In this paper, translated and consistent versions of the Peng-Robinson (tc-PR) and Redlich-Kwong (tc-RK) cubic equations of state (CEoS) are developed. The adjective consistent means that the α-function used in such models passes the consistency test we recently developed and which guarantees safe extrapolation in the supercritical region and safe VLE calculation in multi-component systems. The adjective translated means that a volume translation aimed at exactly reproducing the experimental saturated liquid volume at a reduced temperature of 0.8 was used. The key conclusion of this paper is that the tc-PR EoS is certainly the safest and the most accurate 3-parameter cubic EoS ever published. Indeed the average deviations over roughly 1000 compounds belonging to different chemical families are: ΔPsat<1 %, ΔvapH=ΔcP,Lsat=2% and ΔvLsat(Tr<0.9)=2.3%.In the case of a lack of experimental data to fit the 3 parameters of the α-function and to determine the value of the volume correction, the second part of this study aims at providing a generalized version of the tc-PR and tc-RK CEoS in which all parameters can be estimated from the mere knowledge of the acentric factor.

Prediction of thermodynamic properties of refrigerant fluids with a new three-parameter cubic equation of state

To describe the thermodynamic properties of refrigerant fluids, it is important to use a reliable thermodynamic model able to predict accurate results for both pure compounds and mixtures. In this study, a new three-parameter cubic equation of state is presented, based on the modification of the well-known Patel–Teja equation of state. The new equation of state is associated with the Mathias–Copeman alpha function.By only knowing the acentric factor ω and the experimental critical compressibility factor Zc of pure compounds, it is possible to predict the thermodynamic properties of both pure compounds and mixtures by means of the new equation of state. No binary interaction parameter kij is needed for the prediction of mixture properties.The results obtained with the new equation of state show a good agreement with experimental data for vapor–liquid equilibrium and density properties. The obtained results are particularly satisfying for liquid density, and in the vicinity of the critical point, by comparison with the results obtained using the Peng–Robinson and the Patel–Teja equations of state.

Protonic Ammonium Nitrate Ionic Liquids and Their Mixtures: Insights into Their Thermophysical Behavior.

This study is centered on the thermophysical characterization of different families of alkylammonium nitrate ionic liquids and their binary mixtures, namely the determination at atmospheric pressure of densities, electric conductivities and viscosities in the 288.15 < T/K < 353.15 range. First, measurements focusing on ethylammonium, propylammonium and butylammonium nitrate systems, and their binary mixtures, were determined. These were followed by studies involving binary mixtures composed of ethylammonium nitrate (with three hydrogen bond donor groups) and different homologous ionic liquids with differing numbers of hydrogen bond donor groups: diethylammonium nitrate (two hydrogen bond donors), triethylammonium nitrate (one hydrogen bond donor) and tetraethylammonium nitrate (no hydrogen bond donors). Finally, the behavior of mixtures with different numbers of equivalent carbon atoms in the alkylammonium cations was analyzed. The results show a quasi-ideal behavior for all monoalkylammonium nitrate mixtures. In contrast, the other mixtures show deviations from ideality, namely when the difference in the number of carbon atoms present in the cations increases or the number of hydrogen bond donors present in the cation decreases. Overall, the results clearly show that, besides the length and distribution of alkyl chains present in a cation such as alkylammonium, there are other structural and interaction parameters that influence the thermophysical properties of both pure compounds and their mixtures.