Srinivasan S. Iyengar of Indiana University is supported by an award from the Chemical Theory, Models and Computational Methods program. Many problems at the forefront of energy, environmental and biological research demand the quantum mechanical treatment of electrons and nuclei. But the detailed quantum description of such problems is much too complex even in today?s high performance computing environment. This is because the computational complexity in these problems grows exponentially with system size, which makes them intractable. Iyengar and his research group are developing new computational methods to address these issues. These methods are poised to have major impact on the study of a wide class of problems in biological enzymes, atmospheric chemistry and materials science including study of hydrogen transfer in polymer electrolyte fuel cells. The methods are at the forefront of modern computational quantum chemistry and chemical physics. Hence students in the PI's group have the opportunity to learn and develop new theoretical methods and apply these methods to important practical problems. The results, involving computer codes as well as novel scientific ideas are widely disseminated to the scientific community. Specifically, the computer programs when completed will appear as part of the NSF-funded SEAGrid science gateway. In addition, the PI continues to initiate participation and mentoring of freshman by chemistry faculty. The PI further envisions homogenizing the chemistry curriculum by developing student directed web-based learning methods to connect the sub-disciplines of chemistry and achieve a continuous rather than discrete education of undergraduates.
Computing accurate classical trajectories and potential surfaces in agreement with high levels of electronic structure for complex chemical systems is a major challenge in computational chemistry and chemical physics. Iyengar and co-workers are making contributions in this area, including the development of on-the-fly molecular dynamics methods that allow accurate treatment of electronic structure at the MP2 and Coupled Cluster level, using methods that scale like DFT. Furthermore, they are computing potential surfaces for quantum-mechanical nuclear degrees of freedom that are in good agreement with higher levels of electronic structure methods such as MP2 and Coupled Cluster, at computational costs comparable to DFT. While ab initio molecular dynamics (AIMD) methods are appealing because they do not need an a priori fitted potential surface, this advantage is normally precluded since on-the-fly evaluation of potential and forces is a strong computational constraint. Hence most implementations of AIMD are limited to density functional theoretic (DFT) treatment of electronic structure. The goal of this project is to alleviate this computational constraint and make AIMD more routinely and broadly applicable using efficient methods that allow higher levels of electronic structure, post-Hartree-Fock accuracy. Specifically, the proposal deals with (a) the development of new methods to efficiently compute on-the-fly electronic structure for AIMD and Car-Parrinello-like methods in agreement with MP2, Coupled Cluster and other post-Hartree-Fock methods, (b) the computation of potential surfaces using these approaches to facilitate on-the-fly quantum dynamics. Chemical problems to be studied include, (i) the study conformation dynamics and vibrational properties of protonated water clusters, and (ii) the determination of accurate potential surfaces for reaction paths and quantum wave packet dynamics studies on hydrogen transfer reactions involved in the oxidation pathways of hydroxyl-isoprene, which is a biogenic volatile organic compound.
