CAREER: Understanding and Controlling Single-Molecule Fluorescence Spectral Heterogeneity of Organic Fluorophores
- Institution
- North Carolina State University, NC
- Principal investigator
- Yang Zhang
- Funding
- $641K
- Duration
- 2025–2030
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Abstract
This CAREER project, funded by the Chemical Mechanism, Function, and Properties Program of the Chemistry Division, focuses on uncovering conventionally overlooked chemical mechanisms underlying the variability in fluorescence spectra of single molecules of the same dye species across space and time. Led by Professor Yang Zhang of the Department of Textile Engineering, Chemistry, and Science at North Carolina State University, the project aims to advance the understanding of these mechanisms to develop innovative chemical strategies for illuminating and visualizing biological and artificial nanoscopic processes. Situated at the intersection of color/dye chemistry (organic, analytical, and physical), single-molecule imaging, and deep learning, the project is uniquely positioned to foster interdisciplinary education across all levels. The educational initiatives will integrate color chemistry and machine learning into curriculums spanning K-12 through graduate studies. Additionally, outreach activities will include organizing statewide competitions for K-12 students through the North Carolina Science Olympiad, further promoting scientific engagement. The long-term objective of this project is to understand and control single-molecule fluorescence spectral heterogeneity (smFLUSH) across diverse families of organic fluorophores, including Rhodamine, Boron Dipyrromethene (BODIPY), Cyanine, and Squararine dyes. Mechanistic insights into smFLUSH are critical for guiding the design of next-generation fluorescent probes that meet the demands of advanced multiplexed and functional imaging capabilities in cutting-edge single-molecule super-resolution fluorescence imaging technologies. To achieve these goals, the project focuses on (a) developing a high-throughput single-molecule spectroscopy platform coupled with deep-learning-enabled imaging analytics for systematic characterization of smFLUSH, and (b) synthesizing model compounds to validate structure-property relationships observed in existing fluorophore families. Key research questions include: (1) How can smFLUSH be statistically characterized with precision, accounting for noise uncertainties? (2) How do intrinsic fluorophore structures and environmental interactions influence smFLUSH across different dye families? (3) What chemical modifications can be employed to manipulate and control smFLUSH? By addressing these questions, the project will pave the way for transformative advancements in single-molecule super-resolution imaging, enabling the visualization of biological and artificial processes at an unprecedented level. 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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