Samuel H. Yalkowsky

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The revised general solubility equation (GSE) proposed by Jain and Yalkowsky is used to estimate the aqueous solubility of a set of organic nonelectrolytes studied by Jorgensen and Duffy. The only inputs used in the GSE are the Celsius melting point (MP) and the octanol water partition coefficient (K(ow)). These are generally known, easily measured, or(More)
The revised general solubility equation (GSE) is used along with four different methods including Huuskonen's artificial neural network (ANN) and three multiple linear regression (MLR) methods to estimate the aqueous solubility of a test set of the 21 pharmaceutically and environmentally interesting compounds. For the selected test sets, it is clear that(More)
This study compares the solubility predictions of the two parameter general solubility equation (GSE) of Jain and Yalkowsky with the 171 parameter Klopman group contribution approach. Melting points and partition coefficients were obtained for each of the compounds from Klopman's test set. Using these two variables, the solubility of each compound was(More)
A stability-indicating high-performance liquid chromatography method to quantify 2-(2,4-difluorophenyl)-4,5,6,7-tetrafluoroisoindoline-1,3-dione (NSC-726796) and its three main degradation products was developed. This method was used to investigate its degradation kinetics and mechanism. The reaction follows first-order kinetics and appears to be base(More)
The title compound, C(14)H(5)F(6)NO(3), was synthesized by condensation of tetra-fluoro-phthalic anhydride and 2,4-difluoro-aniline. It was then recrystallized from hexane to give a nonmerohedral twin with two crystallographically unique mol-ecules in the asymmetric unit. The refined twin fraction is 0.460 (3). Torsional differences between the aryl rings(More)
This research examined the applicability of using a neural network approach to the estimation of aqueous activity coefficients of aromatic organic compounds from fragmented structural information. A set of 95 compounds was used to train the neural network, and the trained network was tested on a set of 31 compounds. A comparison was made between the results(More)
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