Roberto Irizarry1, Madeline Leon2, and Miguel Castro2. (1) Electronic Technologies, DuPont, 14 TW Alexander Drive, Research Triangle Park, Raleigh, NC 27709, (2) Chemical Imaging Center, Department of Chemistry, University of Puerto Rico, Car. 108 km 2.0, Mayaguez, PR 00680
Determination of kinetic parameters of metal precipitation is very complex because it is a multiple scale phenomena with a very fast kinetics. The kinetic data is obtained using a stopped flow reactor to eliminate the effect of micro-mixing. The change of size with time is determined using surface plasmon theory. The characteristics of the surface plasmon, is also utilized to determine changes in morphology during growth. The inverse problem is solved to infer nucleation parameters from experimental kinetic data. The dynamic of the metal formation is simulated using MC simulation. The inverse problem is solved using the coarse-grained methods (PEMC and t-PEMC) recently introduced in the literature ([1], [2]) and the artificial chemical plant paradigm for global optimization [3].
[1] R. Irizarry, Fast Monte Carlo Methodology for Multivariate Particulate Systems-I: Point Ensemble Monte Carlo (2008) Chemical Engineering Science 63, 95-110.
[2] R. Irizarry, Fast Monte Carlo Methodology for Multivariate Particulate Systems-II: t-PEMC (2008) Chemical Engineering Science 63, 111-121.
[3] R. Irizarry, LARES: An Artificial Chemical Process Approach for Optimization (2004) Evolutionary Computation Journal, 12 (4), 435-460.