Label-Free Microrefractometry of Interfacial Processes Using Fluorescent Smart Coverslips
Hodaya Klimovsky, Amitay Ginsberg, Dmytro Ohorodniichuk, Maria Shehadeh, Ilya Olevsko + 3 more
TLDR
A new label-free microrefractometry method uses fluorescent smart coverslips to monitor interfacial processes and thin films in real-time.
Key contributions
- Introduces smart coverslips with uniform, brightly fluorescent nanobead films for micro-refractometry.
- Utilizes Supercritical-angle fluorescence refractometry (SAF) for real-time refractive index sensing.
- Enables nanometric thin-film height measurements from single back-focal-plane images, simplifying acquisition.
- Provides a fast, label-free, and non-invasive approach compatible with standard inverted microscopes.
Why it matters
This method offers a significant advancement in label-free sensing by providing real-time, high-sensitivity measurements of interfacial dynamics and thin films. Its compatibility with standard microscopes and non-invasive nature makes it broadly applicable across nanobiophotonics, chemical sensing, and materials analysis.
Original Abstract
Molecular dipoles near interfaces emit highly directional radiation due to near-field interactions, making surface-bound fluorophores sensitive probes of local physicochemical changes. We introduce smart coverslips, stably coated with uniform, brightly fluorescent nanobead films, that exploit refractive-index-dependent emission shifts for sensitive micro-refractometry in small volumes. Supercritical-angle fluorescence refractometry uses single back-focal-plane images to allow us real-time RI sensing and nanometric thin-film height measurements without the need for multi-angle or multi-wavelength acquisition. Our fast, label-free, and non-invasive approach allows measurements of thin-film properties and monitoring of interfacial dynamics on a standard inverted microscope and is broadly applicable to nanobiophotonics, chemical sensing, and in-situ materials analysis.
📬 Weekly AI Paper Digest
Get the top 10 AI/ML arXiv papers from the week — summarized, scored, and delivered to your inbox every Monday.