Polymer and Separations (PolySep) Research Laboratory

Last update:

01/04/2004

M.Sc., Chemical Engineering, University of California, Los Angeles, 1997. Current degree objective: Ph.D.

Research Interests

• Environmental risk assessment
• Multimedia exposure and analysis
• Estimation of physicochemical properties using Neural Networks

Current Project

In order to assess the existing and potential environmental impact of chemical contaminants it is necessary to predict their likely distribution in the environment. The distribution of chemicals in the environment is governed by their physicochemical  and transport properties. However, given the large number of present and future chemicals which may be of concern, it is infeasible to measure the required physicochemical properties of all those chemicals. Therefore, property prediction methods are necessary. Unfortunately, existing prediction methods are either cumbersome to use or do not apply over a sufficient range of chemical functionalities. Therefore, in this project, the use of neural networks for designing a set of prediction tools is being investigated. The goal is to develop a neural network prediction system which will allow one to estimate basic physicochemical properties such as boiling points, vapor pressure, Henry's law constants, octanol-water partition coefficients, aqueous solubility and others. The tools generated by this research will be directly applicable for use in models of contaminant transport and exposure assessment models.

Publications

• Yaffe, D., G, Espinosa, A. Arenas, F. Giralt and Y. Cohen, "Back Propagation and Fuzzy ARTMAP Neural Network Based Quantitative Structural Property Relations (QSPRs) for Prediction of Henry’s Laws of Organic Compounds", J. Chem. Inf. Comput. Sci, in press.
• Yaffe, D., Y. Cohen, G. Espinosa, A. Arenas and F. Giralt, "Fuzzy ARTMAP and Back-Propagation Neural Networks Based Quantitative-Structure-Property Relationships (QSPRs) for Octanol-Water Partition Coefficient of Organic Compounds", J. Chem. Inf. Comput. Sci., 42, 162-183 (2002).
• Yaffe, D. and Y. Cohen, "Neural Network Based Temperature-Dependent Quantitative Structural Property Relations (QSPRs) for Predicting Vapor Pressure of Hydrocarbons," Journal of Chemical Information and Computer Sciences, 41, 463-477 (2001).
• Espinosa, G., D. Yaffe, A. Arenas, Y. Cohen and F.  Giralt, "A Fuzzy ARTMAP based Quantitative Structure-Property Relationships (QSPRs) for predicting Physical Properties of Organic Compounds", I&EC Research, 40, 2757-2766 (2001).
• Yaffe, D., Y. Cohen, G. Espinosa, A. Arenas and F. Giralt, "A Fuzzy ARTMAP Based Quantitative Structure-Property Relationships (QSPRs) for Predicting Aqueous Solubility of Organic Compounds", Journal of Chemical Information and Computer Sciences, 41,1177-1207 (2001). Click here for published errata.
• Yaffe, D., Y. Cohen, J. Arey and A. J. Grosovsky, "Multimedia Analysis of PAHs and Nitro-PAH Daughter Products in the Los Angeles Basin", Risk Analysis, 21, 275-294 (2001).

• Espinosa, G., D. Yaffe, Y. Cohen, A. Arenas and F. Giralt, "Neural Network Based Quantitative Structural Property Relations (QSPRs) for Predicting Boiling Points of Aliphatic Hydrocarbons," Journal of Chemical Information and Computer Sciences, V40(N3):859-879 (2000).

Address
Department of Chemical Engineering
5531 Boelter Hall
UCLA 90095

Phone
(310) 206-4107

Email
dyaffe@ucla.edu