Vaporization Thermodynamics of Pyrrolidinium, Pyridinium, and Imidazolium-Based Ionic Liquids Bearing the Bis(fluorosulfonyl)imide [FSI] and the Bis(trifluoromethylsulfonyl)imide [NTf2] Anions

New experimental vapor pressures in the range 407 K to 460 K and vaporization enthalpy of the ionic liquids (IL) N-alkyl-N-methyl-pyrrolidinium bis(fluorosulfonyl)imide ionic liquids have been measured using quartz crystal microbalance. The absolute vapor pressures and vaporization enthalpies were compared with analogous pyrrolidinium-based ILs with the bis(trifluoromethanesulfonyl)imide anion. The evaluated difference in vaporization enthalpy of ILs with bis(fluorosulfonyl)imide and bis(trifluoromethanesulfonyl)imide anions allowed for estimation of corresponding property for a wide set of ILs with bis(fluorosulfonyl)imide anion. The results are relevant to chemical engineering calculations of processes involving ILs as reaction and separation media.

Vertex-Based Topological Indices of Double and Strong Double Graph of Dutch Windmill Graph

A measurement of the molecular topology of graphs is known as a topological index, and several physical and chemical properties such as heat formation, boiling point, vaporization, enthalpy, and entropy are used to characterize them. Graph theory is useful in evaluating the relationship between various topological indices of some graphs derived by applying certain graph operations. Graph operations play an important role in many applications of graph theory because many big graphs can be obtained from small graphs. Here, we discuss two graph operations, i.e., double graph and strong double graph. In this article, we will compute the topological indices such as geometric arithmetic index GA , atom bond connectivity index ABC , forgotten index F , inverse sum indeg index ISI , general inverse sum indeg index ISI α , β , first multiplicative-Zagreb index PM 1 and second multiplicative-Zagreb index PM 2 , fifth geometric arithmetic index GA 5 , fourth atom bond connectivity index ABC 4 of double graph, and strong double graph of Dutch Windmill graph D 3 p .

Sharp Bounds of First Zagreb Coindex for F -Sum Graphs

Let G = V E , E G be a connected graph with vertex set V G and edge set E G . For a graph G, the graphs S(G), R(G), Q(G), and T(G) are obtained by applying the four subdivisions related operations S, R, Q, and T, respectively. Further, for two connected graphs G 1 and G 2 , G 1 + F G 2 are F -sum graphs which are constructed with the help of Cartesian product of F G 1 and G 2 , where F ∈ S , R , Q , T . In this paper, we compute the lower and upper bounds for the first Zagreb coindex of these F -sum (S-sum, R-sum, Q-sum, and T-sum) graphs in the form of the first Zagreb indices and coincides of their basic graphs. At the end, we use linear regression modeling to find the best correlation among the obtained results for the thirteen physicochemical properties of the molecular structures such as boiling point, density, heat capacity at constant pressure, entropy, heat capacity at constant time, enthalpy of vaporization, acentric factor, standard enthalpy of vaporization, enthalpy of formation, octanol-water partition coefficient, standard enthalpy of formation, total surface area, and molar volume.

The Vaporization Enthalpy and Vapor Pressure of (±) N-Ethyl Amphetamine by Correlation Gas Chromatography

The vaporization enthalpy, and vapor pressure as a function of temperature of N-ethylamphetamine, a substance used in the 1950s as an appetite suppressant and more currently abused as a designer drug, is reported. Its physical properties are compared to those of S (+)-N-methamphetamine, a substance whose physiological properties it mimics. A vaporization enthalpy of (62.4 ± 4.4) kJ·mol−1 and vapor pressure of (19 ± 11) Pa at T = 298.15 K has been evaluated by correlation gas chromatography. Results are compared to estimated values and to the limited amount of experimental property data available.

Application of the Buckingham ∏ theorem to model multiple effect vacuum membrane distillation

This study aims to develop a dimensionless model of the V-MEMD performance indicator through which a preliminary prediction of the most critical performance indicators can be attained. Buckingham ∏ theorem was utilized to define dimensionless parameters that allow the predicted relationships associating independent input parameters to describe the essential performance indicators of the V-MEMD system. The obtained compact model reduces the design parameters from ten to two effective dimensionless parameters to realize the realistic and actual behavior of the designated system. The self-sustained model stands as a short-cut tool for design and performance analysis avoiding time consuming experimentations and/or complicated theoretical models. The compatibility of the generated model is assessed by matching the expected response of output dimensionless parameters (e.g., recovery ratio, R, and gain output ratio, GOR) to variation in pressure ratio and cooling process. The model is validated with other works, and discrepancies are remarked to be within ±10% and ±25% for recovery ratio and gain output ratio, respectively. Furthermore, the specific thermal energy consumption, STEC is correlated to GOR assuming constant vaporization enthalpy and density of the distillate water. The correlation can predict STEC within 5% accuracy over different operating conditions for the supplied hot water.

Estimation of secondary organic aerosol formation parameters for the Volatility Basis Set combining thermodenuder, isothermal dilution and yields measurements

<p>Secondary organic aerosol (SOA) constitutes a major fraction of the total organic aerosol (OA) in the atmosphere. SOA is formed by the partitioning onto pre-existent particles of low vapor pressure products of the oxidation of volatile, intermediate volatility, and semivolatile organic compounds. Oxidation of the precursor molecules results a myriad of organic products making the detailed analysis of smog chamber experiments difficult and the incorporation of the corresponding results into chemical transport models (CTMs) challenging. The volatility basis set (VBS) is a framework that has been designed to help bridge the gap between laboratory measurements and CTMs. It describes the volatility distribution of the OA and the SOA. The parametrization of SOA formation for the VBS has been traditionally based on fitting yield measurements of smog chamber experiments. To reduce the uncertainty of this approach we developed an algorithm to estimate parameters such as volatility product distribution, effective vaporization enthalpy, and accommodation coefficient combining SOA yield measurements with thermograms (from thermodenuders) and areograms (from isothermal dilution chambers) from different experiments and laboratories. The algorithm was first evaluated with “pseudo-data” produced from the simulation of the corresponding processes assuming SOA with known properties. The results showed excellent agreement and low uncertainties when the volatility range and the mass loadings range of the yield measurements coincide. One of the major features of our approach is that it estimates the uncertainty of the resulting parameterization for different atmospheric conditions (temperature, concentration levels, etc.). In the last step of the work, the use of the algorithm with realistic smog laboratory data is demonstrated.</p>

Evaluation of the Temperature Dependence of Vaporization Enthalpy and its Correlation with Surface Tension by Machine Learning and Predictive Correlations

Temperature dependence of vaporization enthalpy is one of the most important thermophysical properties of compounds. In the present study, we theoretically developed relationships applicable to evaluation of vaporization enthalpy of compounds from diverse chemical families for a wide temperature range from melting point to the critical temperature. One outcome of the proposed approach is a relationship describing the correlation between the surface tension and vaporization enthalpy which outperforms the extensively applied Kabo method proposed for the same purpose.<br>

Evaluation of the Temperature Dependence of Vaporization Enthalpy and its Correlation with Surface Tension by Machine Learning and Predictive Correlations

Temperature dependence of vaporization enthalpy is one of the most important thermophysical properties of compounds. In the present study, we theoretically developed relationships applicable to evaluation of vaporization enthalpy of compounds from diverse chemical families for a wide temperature range from melting point to the critical temperature. One outcome of the proposed approach is a relationship describing the correlation between the surface tension and vaporization enthalpy which outperforms the extensively applied Kabo method proposed for the same purpose.<br>