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    We developed a new model for interferometric scattering (iSCAT) microscopy's point spread function. This enables precise 3D nanoparticle tracking over large axial ranges, even in challenging environments.

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    Area of Science:

    • Optical microscopy
    • Nanotechnology
    • Biophysics

    Background:

    • Interferometric scattering (iSCAT) microscopy is a label-free technique for detecting nanomatter.
    • Previous iSCAT studies used Gaussian approximations for the point spread function (PSF).
    • Accurate PSF modeling is crucial for nanoparticle tracking in complex environments and over extended axial ranges.

    Purpose of the Study:

    • To develop a quantitative vectorial diffraction model for the interferometric PSF (iPSF).
    • To investigate the iPSF under various imaging conditions.
    • To enable nanometric 3D localization of nanoparticles over extended axial ranges.

    Main Methods:

    • Vectorial diffraction modeling of the iPSF.
    • Experimental iSCAT measurements.
    • Finite-difference time-domain (FDTD) simulations.
    • Analytical model fitting and unsupervised machine learning for localization.

    Main Results:

    • A robust vectorial diffraction model for the iPSF was established.
    • The lateral shape of the iPSF encodes nanoparticle information.
    • Nanometric 3D localization was achieved over a 10 µm axial range.
    • Calibration-free machine learning approach demonstrated for localization.

    Conclusions:

    • The developed iPSF model accurately describes interferometric scattering microscopy.
    • The findings enable precise 3D single particle tracking in complex scattering media.
    • This advancement has significant implications for nanotechnology and biophysics research.