The National Science Foundation Division of Chemistry awarded Bucknell University $236,565 on January 1, 2027, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop advanced data sampling techniques in multi-dimensional nuclear magnetic resonance (NMR) spectroscopy.
The project pursues non-uniform sampling (NUS) strategies and machine learning methods to enable scientists in pharmaceutical, materials, battery, and diagnostic research to deploy new NMR sampling approaches without requiring specialized expertise. Work addresses the need for comparative studies in NUS design, objective quality metrics for both 1D-NUS and multidimensional NUS approaches, and community familiarity with NUS strengths and limitations relative to established Fourier transform methods. The research integrates undergraduate student training in data science alongside advancement of NMR data sampling methodology, yielding time and cost savings in multidimensional NMR while enhancing data resolution and information content.
Performance occurs in Lewisburg, Pennsylvania, with a period of performance from January 1, 2027, through December 31, 2029. The award is a Project Grant, a standard assistance type for research support at primarily undergraduate institutions.