NSF AI Disclosure Required
NSF requires disclosure of AI tool usage in proposal preparation. Ensure you disclose the use of FindGrants' AI drafting in your application.
LEAPS-MPS: Multimodal-Enhanced Raman Scattering (MERS) for Ultrasensitive Molecular Detection
NSF
About This Grant
In this project, funded by the MPS-LEAPS (Launching Early-Career Academic Pathways) Program and managed by the Division of Chemistry, Professor Tej B. Limbu and his students at the University of Houston-Clear Lake will perform studies focused on the development of a highly sensitive and reliable sensing technique based on the interaction of light and matter to detect trace levels of hazardous chemicals in the environment. Detecting such environmental pollutants remains a major challenge due to the high cost and limited sensitivity of current detection technologies. To address this, Professor Limbu and his students will design and investigate a novel sensing platform that integrates advanced nanomaterials, specifically gold nanostructures and two-dimensional titanium carbide (MXenes), to enhance light-matter interactions and significantly improve the cost-effectiveness and detection sensitivity of the technique. Additionally, the research will explore optical detection mechanisms to better comprehend their role in chemical sensing. The project will involve students in hands-on experimental research, providing opportunities to develop skills and experience that support success in STEM education and careers. Professor Limbu and his students will synthesize two-dimensional titanium carbide (MXene) and integrate it with plasmonic nanostructures in a state-of-the-art architecture to design and optimize a multimodal-enhanced Raman scattering (MERS) substrate capable of ultra-sensitive detection of chemical analytes, including environmental contaminants such as thiram, diquat, and polycyclic aromatic hydrocarbons (PAHs). The team will further investigate the mechanisms contributing to Raman signal enhancement using standard dye molecules, methylene blue (MB), crystal violet (CV), and rhodamine 6G (R6G) under multiple laser excitations. The performance of the developed MERS substrate will be benchmarked through quantitative comparisons with conventional noble metal-based surface-enhanced Raman scattering (SERS) substrates. Through systematic exploration of light–matter interactions in these specially engineered hybrid nanostructures, the research aims to deepen fundamental insight into Raman enhancement mechanisms and drive the development of scalable, highly sensitive molecular sensing platforms for applications in chemical analysis and environmental monitoring. 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
Eligibility
How to Apply
Up to $250K
2027-08-31
One-time $749 fee · Includes AI drafting + templates + PDF export
AI Requirement Analysis
Detailed requirements not yet analyzed
Have the NOFO? Paste it below for AI-powered requirement analysis.