CAREER: Confinement Effects & Emergent Reactivity in Multifunctional Metal-Organic Framework (MOF)-Based Catalysts
- Institution
- Kansas State University, KS
- Principal investigator
- Tendai Gadzikwa
- Funding
- $780K
- Duration
- 2023–2028
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Abstract
With the support of the Chemical Catalysis program in the Division of Chemistry, Professor Tendai Gadzikwa of Kansas State University is studying materials whose physical and chemical structure are modeled after the active sites of enzymes. Enzymes are our most efficient and selective catalysts, accelerating reactions by many orders of magnitude and producing a single product out of many possibilities. By studying the properties and reactivities of synthetic materials that share structural features with enzymes, Dr. Gadzikwa’s laboratory will ascertain structure-function correlations as they relate to catalysis. The insights gained will be applied to the design and construction of more efficient catalysts, thereby reducing energy consumption and waste generation from chemical reactions, two major sustainability goals for the chemical industry. Dr. Gadzikwa supports broadening participation in the chemical sciences, with a focus on the retention of underrepresented minority students in STEM programs at Kansas State. Efforts in this regard include faculty mentorship, professional development opportunities, outreach activities, and the fostering of community and leadership in the local NOBCChE chapter. These studies are directed at exploring unexpected reactivity within, and upon, multifunctional metal-organic framework (MOF) materials, with the goal of using the insights gained to design and construct more efficient enzyme-inspired catalysts. Enzymes operate via multiple, precisely located, chemical functionalities immobilized within confined space, acting synergistically to activate, orient, and stabilize reacting species. The multiple functional groups in close proximity are known to perturb each other’s physical properties, thereby affecting reactivity. With the aid of machine learning, the Gadzikwa Lab will elucidate the molecular origins of unexpected reactivity that has been observed in multifunctional MOFs. The structure-function relationships that are determined from these investigations will inform the design of multifunctional MOF-based confined catalysts. 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.
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