Gordon H Fricke Ph.D.
Associate Professor Emeritus, Associate Dean Emeritus, Chemistry
A.B., Goshen College, 1964
M.A., State University of New York at Binghamton, 1966
Ph.D., Clarkson College of Technology, 1970
Postdoctoral Research Associate, State University of New York at Buffalo, 1970-71
Postdoctoral Research Fellow, Wright State University, 1971-72
Awards & Honors
Loren T. Jones Award for Excellence in Teaching, 1977
Lola L. Loshe Award for Outstanding Service, 1978
Purdue School of Science Counseling Award, 1992
Glenn W. Irwin Jr. Experience Excellence Award, 1993
Indiana University Teaching Excellence Recognition Award, 1997, 1998.
We are developing useful, user-friendly, educationally sound expert systems which teach people how to initiate and solve complex chemical problems. Expert systems are part of the broad field of artificial intelligence. They are computer programs designed to rival a human expert. Data bases of empirical rules, or heuristics, are being developed to search for best answers to problems which the user presents to the expert system. Unlike conventional computer programs, which most often deal with numeric data and algorithms, expert systems are primarily symbolic and deal with complex, uncertain, and ambiguous situations. Currently, one expert system helps the user set-up and solve competing chemical equilibria problems; we solve for unknown concentrations of many species using symbolic manipulation. It is anticipated that new ways of solving systems of nonlinear equations applied to chemical equilibria will be revealed by this program as the expert system searches for the best route to the answers. A second program is in the initial stages; it will be used to help interpret infrared and nuclear magnetic resonance data. We are building the expertise of many scientists into this expert system.
We apply mathematics, statistics, and computer science to extract vital and obscure information and patterns from chemical data. With the increased use of computer-coupled data acquisition and computer-controlled chemical instrumentation, comes massive amounts of data and the ability to guide experimentation in new ways. These methods and data are being used to help design efficient experiments. For example, we have used computer aided design to optimize solvent composition to separate mixtures in thin-layer chromatography (TLC) and high-performance liquid chromatography (HPLC). We have also applied mathematics and statistics to derive equations to separate and quantitate sources of errors in an experimental design so attention can be focused on problem areas in the design.
W.C. Stagner, B.J. Cerimele, and G.H. Fricke, "Content Uniformity: Separation and Quantitation of Sources of Dose Variation," Drug Development and Industrial Pharmacy, 17, 233-244 (1991)
G.H. Fricke, P.G. Mischler, F.P. Stafferi, and C. Housmyer, "Sample Weight as a Function of Particle Sizes in Two-Component Mixtures," Analytical Chemistry, 59, 1213-1217 (1987)
R.E. Tecklenburg, G.H. Fricke, and D. Nurok, "Overlapping Resolution Maps as an Aid in Parallel Development Thin-Layer Chromatography," Journal of Chromatography, 290, 75-81 (1984)
G.H. Fricke, "Ion-Selective Electrodes," Analytical Chemistry, 52, 259R-275R (1980)
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