Beyond the Fit: Towards Efficient Elucidation of Factors that Govern Selectivity and Reactivity in Synthetic Transformations - Models from Electron Density Topology

About This Grant

In this project co-funded by the Chemical Mechanism, Function, and Properties Program and the Chemical Synthesis Program of the Chemistry Division of the NSF, Professor Ha-Yeon (Paul) Cheong, a computational chemist at the Chemistry Department of Oregon State University (OSU, Corvallis, OR), and Professor Kevin Brown, a complex systems expert at the College of Pharmacy, have discovered a way to create mathematical models based on electron densities of the computed transition states. This enables scientists to create conceptual models and develop hypotheses of what structural features may lead to the observed chemistry in a fraction of the time it currently takes. This information can then be used to efficiently plan the next experiment. The OSU team will develop and apply these tools as well as share them so that other researchers can effectively use this new method to understand how their complex synthetic reactions work. The team will integrate this new method into upper division undergraduate/graduate chemistry courses. This project also supports collaborative research and training with a faculty member and undergraduate students from Stetson University (DeLand, FL), a primarily undergraduate liberal arts institution (PUI). In large, complex synthetic reactions, one hopes that computer models may be able to resolve the mystery of how these powerful reactions function. However, it is here where computational results are often the most bewildering. This grant addresses this challenge of how to effectively and efficiently use results from computer modeling of chemical processes to understand chemical transformations and processes. This proposal aims to develop a platform to create mathematical models based on topological electron density descriptors derived from the computed Transition States (TSs). These statistical models can reproduce the relative energies of the TSs, and the terms of the model reveal specific pair-wise inter-atomic interactions, their relative magnitudes, and whether they are repulsive or attractive. This enables the creation of conceptual models and hypotheses of what features are responsible for the observed chemistry in a fraction of the time it currently takes. Ultimately, this project aims to contribute to transform the way chemical research is enhanced by computations by expanding the accessibility of computational modeling such that non-experts and seasoned veterans alike may reliably arrive at the same robust models and hypotheses efficiently with statistical confidence. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.