With this award from the Chemistry Research Instrumentation and Facilities: Departmental Multi-User Instrumentation program (CRIF:MU), Professor Charles L. Liotta and his colleagues Angelo Bongiorno, Jean-Luc E. Bredas, Rigoberto Hernandez and Charles D. Sherrill will acquire an energy efficient computer cluster to pursue fundamental theoretical and computational chemistry studies of broad relevance to issues in sustainable energy research. Projects that will be investigated include computational studies of: donor/acceptor interfaces in organic solar cells, organic supramolecular architectures and their potential as organic semiconductors and light-harvesting systems, dynamics of peptide nucleic acid for molecular electronics applications, model processes occurring on solid oxide fuel cells, simulations on the mechanism of formation and the electrical and electrochemical properties of nanostructured composites which are candidates for anode materials of improved lithium batteries. In parallel with these computational studies, other team members will focus on the development of improved theoretical and computational approaches which can provide more reliable results at a smaller cost in computer time and power expended including speedups of coupled cluster code by adapting it for Graphical Processing Units and improved methods for studying dynamics in nonequilibrium environments.
A computer cluster is a group of linked processors that work in concert to achieve vastly more computational power that the individual computers. These are employed to investigate complex problems using computational methods based on theoretical models and programs. Such calculations, often used in conjunction with experimental data, allow chemists to better understand many types of complex chemical and biological phenomenon. This resource will be used by students and faculty at Georgia Tech and at the following institutions: Hampton U., Norfolk State U., U. of Puerto Rico, Westminster College and Bethel College.
This grant allowed the purchase of GreenGate, a machine meant to demonstrate that high-performance computing is still possible even when using very energy-efficient parts. Green computing is becoming an increasingly important topic as a rapidly growing amount of energy is used by computers across the US and across the world. At the time of its purchase in 2010, GreenGate was among the most energy efficient computers available. The machine enabled the development of new computer algorithms tailored to energy-efficient hardware, including graphical processing units (GPU's); this new software is being released for free to the community as open-source software. Energy-efficiency of molecular simulations was also improved by the development of new theoretical approaches that, through better approximations, obtain results faster with less computation required. GreenGate has been used by a large number of faculty and student researchers at Georgia Tech and at partner primarily undergraduate institutions. It has aided many publications on the development of improved theoretical/computational tools for molecular computations, and also on the use of these tools to challenging problems in chemistry, biology, and materials science. In particular, a substantial part of the work has focused on computations of molecules relevant for green energy sources such as organic solar cells. In addition to these research purposes, GreenGate has also served an educational role. It has been used for lab exercises in Georgia Tech's Computational Chemistry class, and also by an NSF-sponsored Workshop on Computational and Theoretical Chemistry, which teaches faculty at 2- and 4-year colleges how to incorporate modern techniques in Computational Chemistry into their curricula.
