D3SC: Dynamic Effects in Ordinary Organic Reactions in Solution

In this project funded by the Chemical Structure, Dynamics, and Mechanism-B Program of the Chemistry Division, Professor Daniel A. Singleton of Texas A&M University will investigate “dynamic effects” in reaction mechanisms. These are experimental observations in reactions that can neither be predicted nor explained using the standard models for mechanisms.

The proposed research has five aims related to dynamic effects. The first two aims would explore newly identified forms of dynamic effects, one resulting from localized molecular vibrations that can occur in reactions promoted by light and another that arises from a flaw in modern statistical rate theories. A third aim is to apply newly developed understanding of dynamic effects in solvent to reinterpret a large classical area of chemistry, specifically 20th century carbocation chemistry.

In this broad field, it is suggested that old controversies arose from the use of mechanistic models that were too simplified. A fourth aim is to apply a technology that arises from a dynamic effect to learn about mechanisms that are hidden from current chemical approaches. The overarching aim is to develop a comprehensive chemical theory of dynamic effects by combining current theories with machine-learning.

Overall, this project will impact at a fundamental and broad level the understanding of many classic chemical reactions, while providing new approaches to the development and control of reactions. Student training is a major goal of this research including with a good record of including women and members of underrepresented groups in science as part of the research team.

Graduate and undergraduate students in the Singleton group undertake comprehensive projects, which lead to the development of diverse skills. These range from experimental organic chemistry and precision analytical measurements, to quantum chemistry, coding, molecular dynamics calculations, and machine learning. The Singleton group will also continue its program of developing and distributing to the community computational tools that aid the study of dynamic effects in reactions.

The research will particularly investigate an indirect approach to the long-sought goal of vibrationally promoting specific reactions in complex molecules. The idea to be explored is that triplet photosensitizers of varying energies can provide a controllable amount of energy to localized regions in molecules. The project will also investigate a flaw in variational transition state theory in which the actual reaction path departs from that expected based on the potential energy surface, with the primary goal of identifying additional examples of reactions subject to this flaw.

The third project aim is based on the proposal that historical controversies in carbocation chemistry have resulted from the unconsidered intermediacy of incompletely solvated structures. This idea will be explored within a series of prominent classical carbocation reactions. The fourth project aim is to use a recently developed application of a dynamic effect, “energy read-out,” to study key hidden steps in reactions involving alkoxy radicals.

This idea is notably applicable to non-adiabatic proton coupled electron transfer (PCET) reactions where mechanisms are inaccessible through ordinary experimental and computational methods. The final aim is to modify transition state theory by partitioning the transition state into regions of dynamical outcome using machine learning. This includes the development of active-learning and precision-enhancing methods designed to ease the application of trajectories to dynamic effects, as well as the provision of these computational tools to the wider chemical community.

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.