PhD Thesis Proposal: Junhu Zhou

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"Computation-Driven Design and Synthesis of Molecular Sensors for Surface-Enhanced Raman Spectroscopy in Liquids"

Abstract

Detecting target analytes with high specificity and sensitivity in liquid samples is essential for applications spanning analytical science, environmental monitoring, and clinical diagnostics. Raman spectroscopy, a non-destructive chemical analysis technique, is particularly suited for liquid sensing due to water’s weak Raman scattering and minimal interference from O-H stretching modes. However, the inherently low excitation efficiency of normal Raman scattering limits its sensitivity, requiring analyte concentrations exceeding 1 mM for reliable detection. Surface-enhanced Raman spectroscopy (SERS) addresses these limitations by amplifying Raman signals using nanostructured metallic materials. Traditional SERS designs, such as nanoparticle clusters and nanopatterned arrays, focus on generating "hotspots" to enhance local electromagnetic fields, achieving signal amplification factors up to 10⁸. Despite their success, these configurations face significant challenges in liquid environments, including non-uniform signal distribution caused by the "coffee ring" effect and limitations in detecting large biological targets like extracellular vehicles (EVs) due to spatial constraints.

This thesis introduces a novel metal-insulator-metal (MIM) nanoprobe design for molecular sensing in liquid environments. By integrating finite element analysis (FEA) for structural optimization, colloidal theory and molecular dynamics simulations for synthesis and assembly guidance, this research establishes a computational framework that ensures reproducibility, scalability, and precise control over nanoprobe morphology. The proposed MIM nanoprobes enable the detection of analytes ranging from small molecules to large biological targets, overcoming the spatial and plasmonic limitations of traditional SERS platforms. By combining advanced computational techniques with experimental validation, this work establishes a robust platform for plasmonic sensing in liquids. The outcomes demonstrate significant improvements in sensitivity, specificity, and reproducibility, advancing applications in environmental monitoring, clinical diagnostics, and biochemical analysis.

Thesis Committee

• John XJ Zhang
• Xin Qi, Department of Chemistry
• Geoffrey P Luke
• Tyler Derr, Vanderbilt University

Contact

For more information, contact Thayer Registrar at thayer.registrar@dartmouth.edu.