Plenary Speaker

In recent years we have built precision self-organised metallic structures which confine light reliably to the nanoscale. Such plasmonic devices routinely provide intense coupling to vibrations, giving a wide variety of novel effects to be discussed. These include the most tightly confined Lamb modes, how thermal energy is transported through molecular monolayers, coherent vibrations delocalised among many molecules, optomechanical tuning of molecular bonds, single molecule forces from picocavities, the control and structure of single water monolayers, how to make molecular vibrations emit light, and electrochemical SERS magnification and separation. I will also discuss key applications including in ubiquitous low-cost sensing for Healthcare.

Understanding how water, ions, and surfaces interact across length scales is central to electrochemistry, nanofluidics, and catalysis. In particular, the impact of hydrogen-bond network termination and interfacial charges on the arrangement of counterions and water has been the subject of intense debate. Across three studies, we have established a molecular-level picture of structure and dynamics at aqueous interfaces under confinement and electrostatic perturbation.
At angstrom-scale confinement, interfacial effects dominate water structure, disrupting bulk hydrogen bonding and creating asymmetric environments governed by surface interactions. [1] Extending this, we show that even nominally neutral materials, such as hexagonal boron nitride, spontaneously acquire surface charge upon contact with water, indicating that electric double-layer formation is nearly universal at solid–liquid interfaces. [2] Finally, femtosecond spectroscopy reveals that ionic rearrangements in the electric double layer occur on tens-of-picoseconds timescales, faster than diffusion-limited expectations but consistent with classical Debye theory. [3] Together, these results provide a unified molecular understanding of how confinement, interfacial polarization, and charge govern water behavior in nanofluidic and electrochemical systems.

Surface-enhanced Raman scattering (SERS) has emerged as an attractive analytical tool for swift detection of multiplex chemicals or even disease biomarkers. This talk highlights our group's recent advancements in engineering high-performance SERS platforms and integrating them with advanced data analytics for diverse biomedical applications. First, I will discuss SERS substrate fabrication strategies designed to enhance chemoselectivity and target affinity, thereby pushing the boundaries of detection sensitivity and selectivity. Second, I will highlight the integration of chemometrics and machine learning algorithms into SERS. We demonstrate how machine learning transforms the interpretation of complex biological Raman spectra by extracting hidden spectral patterns, enabling rapid, high-throughput, and automated on-site disease prediction. Together, these innovations underscore the power of AI-driven SERS platforms to overcome long-standing challenges in biomarker sensing and accelerate next-generation biomedical diagnostics.