Prediction of the Vapor Pressure Boiling Point, Heat of Vaporization and Diffusion Coefficient of Organic Compounds

Abstract

The prototype computer program SPARC has been under development for several years to estimate physical properties and chemical reactivity parameters of organic compounds strictly from molecular structure. SPARC solutesolute physical process models have been developed and tested for vapor pressure (at any temperature), heat of vaporization (at 25C and the boiling point), diffusion coefficient (at 25C) and boiling point (at any pressure) for a relatively large number of organic molecules. The RMS deviation error of the predicted the vapor pressures, heats of vaporization (at any temperature) and boiling points (at any pressure) were close to the intralaboratory experimental errors.

Formation of Low Volatility Organic Compounds and Secondary Organic Aerosol from Isoprene Hydroxyhydroperoxide Low-NO Oxidation

“…Inputs for this calculation include temperature (26C), pressure (98 kPa for a 252 m altitude in Pasadena, CA, USA), species diffusion coefficient for a model LVOC in air (~5 x10 -6 m 2 s -1 ) estimated using the SPARC calculator 3,4 , sample tube inner diameter (0.00476 m), tube length (2m), and air flow rate of 5x10 -5 m 3 s -1 corresponding to the sample gas flow of 3 SLPM. This process assumes that these S3 species are of sufficiently low volatility that they are irreversibly lost to the walls (uptake coefficient of 1) and that there is no re-partitioning back to the gas-phase, 1 which is consistent with their behavior in the chamber as discussed elsewhere in this work.…”

Influence of non-ideality on condensation to aerosol

“…In SPARC, molecules are described by a set of molecular descriptors (molecular polarizability, molecular volume, microscopic dipole, hydrogen bond), which are themselves sums over "atomic" fragments (Hilal et al, 2003b). Vapor pressures are calculated by solute-solute interaction models (Hilal et al, 2003b) and activity coefficients by solute-solvent interaction models (Hilal et al, 2004).…”

“…Therefore, we rely on the model SPARC (Sparc Performs Automated Reasoning in Chemistry) (Carreira et al, 1994), available online (http://ibmlc2.chem.uga.edu/sparc/), to generate activity coefficients for species containing these functional groups, and determine the missing parameters by fitting to these data. SPARC provides estimates for various chemical properties (saturation vapor pressures (Hilal et al, 2003b), activity coefficients (Hilal et al, 2004), hydration constants (Hilal et al, 2005),. .…”

Benchmarking the SPARC software program for estimating solubilities of naphthalene and anthracene in organic solvents

“…[5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21]), a number of studies have developed quantitative structure-property relationships (QSPRs) and employed associated software programs (see, e.g., ref. [22][23][24][25][26][27][28]) for predicting the solubility of these compounds in a wide range of solvent systems.To date, despite its broad applications towards predicting the partitioning behavior and reactivity of various organic compounds, the SPARC software program [29][30][31][32][33][34][35][36] has not been previously benchmarked for its capacity to estimate the solubility of representative PAHs in organic solvents. Consequently, in the current work we investigate the ability of SPARC to predict the solubilities of naphthalene (1) and anthracene (2) (Figure 1) in a range of organic solvents at various temperatures.…”

“…To date, despite its broad applications towards predicting the partitioning behavior and reactivity of various organic compounds, the SPARC software program [29][30][31][32][33][34][35][36] has not been previously benchmarked for its capacity to estimate the solubility of representative PAHs in organic solvents. Consequently, in the current work we investigate the ability of SPARC to predict the solubilities of naphthalene (1) and anthracene (2) (Figure 1) in a range of organic solvents at various temperatures.…”