CDS&E: Retrosynthetic nanoreactor method for reaction discovery in the interstellar medium

University Of California-Davis, Davis CA

Investigators

Abstract

Chemistry in space - including the interstellar medium and circumstellar envelopes - is an important source of organic compounds across the universe and may have contributed to the beginnings of life on Earth. The great majority of organic molecules observed in space have been in cold molecular clouds that are often hundreds of light-years away, and the only means of directly observing the compounds is via radio astronomy. Direct observation of the reactions is not possible. Therefore, terrestrial experiments or computer simulations are needed to understand the chemical reactions that create or destroy compounds in these environments. This research team will study chemical reactions in the interstellar medium using a computational method called the retrosynthetic nanoreactor (RNR). The reaction mechanism is the first step toward obtaining accurate reaction rates from laboratory kinetic studies or theoretical kinetic calculations. A graduate student will carry out the proposed calculations that comprise the main portion of the research project. The team will also develop a computationally inexpensive version of the nanoreactor that will be incorporated into the Scientific Programming for Chemistry course to enable undergraduate and high school students to carry out reaction discovery simulations on their personal computers. Mechanistic studies on astronomical molecules of interest will be carried out using the RNR. Starting from a target compound of interest, the proposed method uses first-principles molecular dynamics simulations to predict the possible precursors and gas-phase reactions that lead to its formation, complete with potential energy surface data that indicate the kinetic feasibility of each mechanism under the low density, low temperature conditions typical to astronomical environments. The team propose several methodological advancements that will extend, accelerate, and automate the RNR in a transformative way, providing the scientific community with a powerful, intuitive, and easy-to-use tool for astronomical reaction discovery. The team will create an AI-based recommendation system to rank and prioritize the relevance of molecules in astrochemical setting. 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.