Computation-guided design and synthesis of plasmonic metal-insulator-metal (MIM) nanosensor for liquid sensing

About This Grant

This research project advances the development of next-generation liquid nanosensors using surface-enhanced Raman spectroscopy (SERS), a powerful technique that enables highly sensitive detection of molecular signatures. These sensors have transformative potential for early detection of environmental pollutants in water supplies and non-invasive diagnosis of diseases such as cancer and neurodegenerative disorders. However, current SERS probes face major limitations in sensitivity and reproducibility due to the complexity of detecting trace biomolecules in liquid samples. This award supports a cost-effective, computation-guided approach to the design, synthesis, and application of high-performance SERS nanoprobes. By integrating multiscale simulations with experimental synthesis, the project reduces reliance on traditional trial-and-error methods. Computational models will guide the structural design of plasmonic nanostructures and predict optimal synthesis conditions, accelerating discovery while conserving resources. This interdisciplinary collaboration between engineering and the physical sciences supports NSF’s mission to promote the progress of science and advance national health and welfare. The project also fosters STEM education and expands the workforce by providing hands-on research opportunities for students, helping to train the next generation of scientists and engineers. This award supports the rational design and synthesis of metal-insulator-metal (MIM) nanoprobes for enhanced SERS-based liquid sensing. The project combines continuum-scale finite element analysis (FEA), colloidal theory, and atomistic molecular simulations to model field enhancement, nanoparticle assembly, and interfacial interactions. Simulation outputs will directly inform the experimental fabrication of MIM nanoprobes with tunable core shape, silica thickness, and surface ligand chemistry. The project includes three integrated tasks: (1) development of a multiscale modeling framework to design optimal MIM nanostructures and predict solution-phase assembly conditions; (2) synthesis of MIM nanoprobes with tailored morphology and surface functionality based on computational guidance; and (3) evaluation of SERS performance across a range of analytes, including in silico screening and experimental detection of biological and chemical targets in liquid media. This integrated approach aims to establish generalizable design principles for reproducible, high-sensitivity SERS nanoprobes and accelerate their application in diagnostic and environmental monitoring technologies. 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.