Plasmonic Scattering Interferometric Microscopy: Decoding the Dynamic Interfacial Chemistry of Single Nanoparticles.

Acc Chem Res

Hefei National Laboratory for Physical Sciences at the Microscale, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei 230026, China.

Published: August 2025


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Article Abstract

ConspectusThe ability to detect and image nanomaterials at interfaces is crucial for a wide range of applications, from the engineering and characterization of nanocomposites to enabling label-free detection for biomedical diagnostics and therapy. Light microscopy, which relies on the optical properties of nanomaterials, has significantly contributed to this goal due to its adequate temporal and spatial resolutions and compatibility with diverse application scenarios. However, the optical intensity readout of these label-free optical imaging techniques inherently limits their selectivity. Consequently, visualizing dynamic interfacial changes over a single particle with high spatiotemporal resolution under mild solution reaction conditions remains a challenge.In this Account, we highlight the recent progress in plasmonic scattering interferometric microscopy (PSIM), a technique developed to address these challenges. We begin with the fundamental principles of plasmonics and light scattering relevant to PSIM, demonstrating its ability to optically identify and measure various nanoparticles. Significant improvements in imaging quality were achieved through the development of a high-resolution plasmonic scattering interferometric microscope (HR-PSIM). These advances have enabled the real-time observation of compositional transformations in single nanoparticles, offering new insights into their electrocatalytic activity and reaction kinetics at the single-particle level. Leveraging the high-resolution capacity of HR-PSIM for visualizing chemical reactions, we explored electrochemical processes in real-time with remarkable spatial resolution. In addition, we introduce novel algorithmic tools for noise reduction and automation, designed to eliminate background interference and reconstruct high-quality, high-resolution images. The integration of deep learning into PSIM has further advanced the technique, enabling the precise localization and identification of nanoparticles with enhanced robustness across varying spatiotemporal conditions. This Account concludes with an outlook on the future development of PSIM, discussing current limitations and the potential for further enhancements. We envision that the continued refinement of PSIM will open new avenues for studying surface chemistry and nanoscale reactions, leading to significant breakthroughs in nanoscience research and a broad range of practical applications.

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http://dx.doi.org/10.1021/acs.accounts.5c00294DOI Listing

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