NSF Award
2305086
With support from the Chemical Measurement and Imaging Program in the Division of Chemistry, Professor David Rovnyak and his group at Bucknell University are developing data sampling technology and principles to accelerate the discovery of complex molecular structures. Broadly, chemists are studying molecules of increasing complexity and size, such as complex natural products from which scientists can develop new bio-inspired drugs, where it is vital to discover the exact structures of these molecules. A central technique in chemistry that meets this need is nuclear magnetic resonance (NMR). However, the more complex and large a molecule is, the more difficult it is to solve its structure. Using statistical and related data science methods, the Rovnyak group is developing and disseminating next-generation data sampling methods that make advanced NMR analysis much faster and more accessible to chemists. The work is providing research opportunities to undergraduate students, including members of underrepresented groups. The team is also involved in outreach activities, including summer science camps for high school students and presentations at regional schools and museums. <br/><br/>Advanced 2D-NMR experiments, often used for detecting long range atomic connectivities, are required to probe the structure of increasingly complex proton-poor natural products and bio-inspired molecules. The burden of indirect incrementation in powerful 2D-NMR spectroscopies leads to very long acquisition times and extremely low sensitivity. Solutions to the ‘incrementation problem’ of multidimensional NMR have been pursued for about three decades, through a broad family of techniques known as nonuniform sampling (NUS). In 2D-NMR, NUS is often not used at all or only conservatively, such as 50% data reduction. This fails to take advantage of the benefits NUS offers. This work is probing the barriers to sparser NUS and developing improved 1D-NUS schedules for advanced 2D-NMR experiments beyond the 50% threshold while ensuring high spectral fidelity. The work includes strategies for ‘super resolution’ NMR spectroscopy with ultra-high incrementation values. Intuitive and easy-to-use 1D-NUS schedules will be made widely available with potentially wide impact on the experimental chemical science community.<br/><br/>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.
