Combinatorial Chemistry Random Phase Volume Model used in the validation of combinatorial chemistry protocols. The goal of combinatorial materials discovery is to find compositions of matter that maximize a specific material property, such as superconductivity, magnetoresistance, luminescence, ligand specificity, sensor response, or catalytic activity. We have developed new experimental protocols for searching the space of variables in combinatorial chemistry, exploiting an analogy between combinatorial materials discovery and Monte Carlo computer modeling methods. Efficient implementations of the search strategy are feasible with existing library creation technology. These multiple-round protocols, when combined with appropriate robotic controls, should allow the practical application of combinatorial chemistry to more complex and interesting systems.
Zeolites continue to be synthesized at a furious pace.
The techniques of diversity synthesis have recently been introduced to the field, and this may soon lead to a tremendous explosion in the number of new synthetic zeolites. We work on direct methods for determining the structure of microcrystalline materials from powder diffraction data. The approach makes use of powerful ideas from importance-sampling Monte Carlo. Roughly a dozen new zeolite structures have been solved with our method. The structural information provided by this approach is necessary not only to understand the performance of newly synthesized catalysts but also to propose rational syntheses of homologous materials with tailored performance.