"New Computational Methods and Their Applications to Renewable Energy, Semiconductors and the Materials Genome"
Department of Chemical and Biomedical Engineering
Florida State University
Computational chemistry and materials science algorithms are now powerful enough that they can predict many properties of materials and molecules before they are synthesized. By implementing materials and chemical properties calculations in supercomputing clusters, we have predicted over 100,000 materials for energy storage and catalysis. The computations predicted several new materials which were made and tested in the lab, leading to the discovery and development of five new materials that overcome the DOE targets for methane and molecular hydrogen storage. Recently we found a new strategy for tuning the band gap of layered materials to capture light which may couple to its intrinsic water-splitting catalytic properties, thus resembling photosynthesis and creating a step forward for alternative energy.
In another research direction we have calculated the properties of over 40,000 new compounds from a few weeks of running our algorithm. The great challenge is to be able to manage this large amount of data and computation effi ciently. To this end we started the organization of this database of compounds; this project intends to create databases with the information properties of di fferent chemicals and materials using our computing capabilities. We will present some results from our proposed algorithms for porous frameworks and semiconductors. The hope is that we will release our results to the experimental community so that they can target the most promising compounds from our computational databases. Such databases can be improved by using traditional distributed computing and modern online computing. Along the way, we have to developed new computational and theoretical tools that allowed us to calculate new properties of chemicals and materials and thus enhance the scope of our databases.