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Postdoctoral Fellowship: MPS-Ascend: Using Autonomous Electrochemistry to Develop Highly Selective Plant Hormone Sensors

NSF

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About This Grant

Michael A. Pence is awarded an NSF Mathematical and Physical Sciences Ascending Postdoctoral Research Fellowship (NSF MPS-Ascend) to conduct a program of research and activities related to broadening participation in STEM. This fellowship to Dr. Pence supports the research project entitled “Postdoctoral Fellowship: MPS-Ascend: Using Autonomous Electrochemistry to Develop Highly Selective Plant Hormone Sensors” under the mentorship of a sponsoring scientist. The host institution for the fellowship is Missouri University of Science and Technology, and the sponsoring scientist is Dr. Shelley Minteer. This proposal focuses on developing a highly selective electrochemical sensor for abscisic acid (ABA), a critical plant hormone involved in regulating plant growth and stress responses. The proposed work will use a copolymer approach to enhance the selectivity of molecularly imprinted polymers (MIP) and an autonomous electrochemical platform for rapidly screening and optimizing sensor performance. The proposed sensor will be low-cost and field-deployable, enabling real-time monitoring of ABA and other plant hormones. Successful implementation of this work would contribute to the fundamental understanding of MIP-analyte interactions, develop a framework for designing sensors for a variety of analytes, expand the scope of automated electrochemistry, and provide a means to selectively detect plant hormones. The PI intends to increase the participation of undergraduate and high school students in STEM fields through a summer school program and the implementation of a remote learning-based electrochemistry curriculum for rural populations, where agriculture is most important. Both efforts will be highly interdisciplinary, with students learning electrochemistry while also gaining exposure to programming, robotics, and machine learning. 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.

Focus Areas

machine learningchemistry

Eligibility

universitynonprofitsmall business

How to Apply

Funding Range

Up to $300K

Deadline

2028-07-31

Complexity
Medium
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