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Updated: Jun 5, 2025
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Measurement of Scattering Nonlinearities from a Single Plasmonic Nanoparticle
Published on: January 3, 2016
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Counting and mapping of subwavelength nanoparticles from a single shot scattering pattern
Eng Aik Chan1, Carolina Rendón-Barraza1, Benquan Wang1
1Centre for Disruptive Photonic Technologies, The Photonics Institute, School of Physical and Mathematical Sciences, Nanyang Technological University, 637371 Singapore, Singapore.
Nanophotonics (Berlin, Germany)
|December 5, 2024
Summary
A new super-resolution optical method uses deep learning to count and map subwavelength particles on surfaces with over 90% accuracy. This technique is crucial for nanotechnology and various industries, offering precise particle analysis without fluorescent labeling.
Area of Science:
- Optics
- Nanotechnology
- Data Science
Background:
- Accurate particle counting is vital across diverse scientific and industrial fields, including nanotechnology, environmental monitoring, pharmaceuticals, food, and semiconductors.
- Existing methods often face limitations in resolution, speed, or sample preparation, necessitating advanced techniques for subwavelength particle analysis.
Purpose of the Study:
- To introduce a novel super-resolution, single-shot optical method for simultaneously counting and mapping the positions of subwavelength particles on a surface.
- To demonstrate the efficacy of deep learning applied to scattered light intensity profiles for particle analysis.
Main Methods:
- Utilized a single-shot optical approach analyzing the intensity profile of coherent light scattered from particles.
- Employed deep learning algorithms for the analysis of scattered light patterns to determine particle counts and locations.
- Validated the method through proof-of-principle experiments on particle ensembles.
Main Results:
- Achieved particle counting accuracies exceeding 90% for subwavelength particles.
- Demonstrated highly accurate mapping of particle locations on a 4x4 grid with nearly perfect precision.
- Showcased super-resolution capabilities, maintaining high accuracy for both closely packed and sparsely distributed, optically unresolvable particles.
Conclusions:
- The developed method offers a powerful, non-invasive tool for super-resolution particle counting and mapping.
- Its resilience to variations in particle size, independence from fluorescent labeling, and potential for high-throughput analysis make it broadly applicable in nanotechnology, life sciences, and beyond.
