Several studies were done to illustrate the versatillity of the Abraham model in mathematically describing the various solute-solvent interactions found in a wide range of different chemical and biological systems. The first study focused on using the solvation model to construct mathematical correlations describing the minimum inhibitory concentration of organic compounds for growth inhibition towards the three bacterial strains Porphyromonas gingivalis, Selenomonas artemidis, and Streptococcus sobrinus. The next several studies expand the practicallity of the Abraham model by predicting free energies of partition in chemical systems. The free energy studies expand the use of the Abraham model to other temperatures and properties by developing correlations for the enthalpies of solvation of gaseous solutes of various compounds dissolved in water, 1-octanol, hexane, heptane, hexadecane, cyclohexane, benzene, toluene, carbon tetrachloride, chloroform, methanol, ethanol, 1-butanol, propylene carbonate, dimethyl sulfoxide, 1,2-dichloroethane, N,N-dimethylformamide, tert-butanol, dibutyl ether, ethyl acetate, acetonitrile, and acetone. Also, a generic equation for linear alkanes is created for use when individual datasets are small. The prediction of enthalpies of solvation is furthered by modifying the Abraham model so that experimental data measured at different temperatures can be included into a single correlation expression. The temperature dependence is directly included in the model by separating each coefficient into an enthalpic and entropic component. Specifically, the final study describes the effects of temperature on the sorption coefficients of organic gases onto humic acid. The derived predicted values for each research study show a good correlation with experimental values.

In this experiment, more than one hundred volatile organic compounds were analyzed with the gas chromatograph. Six capillary columns ZB wax plus, ZB 35, TR1MS, TR5, TG5MS and TG1301MS with different polarities have been used for separation of compounds and illicit drugs. The Abraham solvation model has five solute descriptors. The solute descriptors are E, S, A, B, L (or V). Based on the six stationary phases, six equations were constructed as a training set for each of the six columns. The six equations served to calculate the solute descriptors for a set of illicit drugs. Drugs studied are nicotine (S= 0.870, A= 0.000, B= 1.073), oxycodone(S= 2.564. A= 0.286, B= 1.706), methamphetamine (S= 0.297, A= 1.570, B= 1.009), heroin (S=2.224, A= 0.000, B= 2.136) and ketamine (S= 1.005, A= 0.000, B= 1.126). The solute property of Abraham solvation model is represented as a logarithm of retention time, thus the logarithm of experimental and calculated retention times is compared.

The Abraham Solvation Parameter Model (ASPM) is a linear, free-energy relationship that can be used to predict various solute properties based on solute-solvent interactions. The ASPM has been used to predict log (K or Cs,organic/Cs,gas) values, as well as log (P or Cs,organic/Cs,water) values for solute transfer into the following organic solvents: 2-methoxyethanol, 2-ethoxyethanol, 2-propoxyethanol, 2-isopropoxyethanol and 2-butoxyethanol. The derived log (K or Cs,organic/Cs,gas) correlations describe the experimental data to within 0.14 log units (or less). The derived log (P or Cs,organic/Cs,water) correlations describe the experimental data to within 0.16 log units (or less). The ASPM has also been used to predict the enthalpies of solvation of organic solutes dissolved in the following solvents: acetic acid, dimethyl carbonate, diethyl carbonate, 1-butanol, 1-pentanol, 1-hexanol. The derived enthalpy of solvation correlations, using the L solute descriptor, describe the experimental data to within 2.50 log units (or less). The derived enthalpy of solvation correlations, using the V solute descriptor, describe the experimental data to within 3.10 log units (or less). Validation analyses have been performed on several of the correlations; and, as long as the solute descriptors fall within the given ranges as reported, the original correlations show good predictive ability for determining 1) solute transfer into, and 2) enthalpy of solvation for the aforementioned solvents.

The Abraham solvation model (ABSM) is an experimentally derived predictive model used to help predict various solute properties. This work covers various uses for the ABSM including predicting molar enthalpies of vaporization, predicting solvent coefficients for two new solvents (2,2,5,5-tetramethyloxolane and diethyl carbonate), predicting values for multiple new ionic liquids (ILs). This work also introduces a novel method for updating IL ABSM parameters by updating cation- and anion-specific values using linear algebra and binary matrices.