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Parameterless detection of liquid-liquid interfaces with sub-micron resolution in single-molecule localization

Dingeman L H van der Haven1, Roderick Prudent Tas2, Pim van der Hoorn3

  • 1Department of Chemical Engineering and Chemistry, Eindhoven University of Technology, The Netherlands; Department of Materials Science & Metallurgy, University of Cambridge, United Kingdom.

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Summary

We developed a new maximum likelihood estimator (MLE) method to accurately pinpoint soft interfaces, like oil-water boundaries, using iPAINT imaging. This approach precisely determines interface locations, crucial for nanoscale wetting studies.

Keywords:
ColloidEmulsionIn situ characterizationLiquid–liquid interfacesParticle-stabilized interfacesSingle-molecule localization microscopy

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Area of Science:

  • Physical Chemistry
  • Nanotechnology
  • Surface Science

Background:

  • Accurate determination of soft interfaces is critical for understanding nanoscale wetting phenomena.
  • Current methods using iPAINT (imaging, الفيزيائي, and analysis of nanoscale structures) face challenges in precisely locating these interfaces.
  • Visualizing soft interfaces in situ with minimal invasiveness is an ongoing research goal.

Purpose of the Study:

  • To propose and validate a novel, highly accurate method for determining the exact location of soft interfaces.
  • To address the limitations of existing techniques in precisely quantifying interface positions.
  • To advance the in situ characterization of nanoparticle-laden interfaces.

Main Methods:

  • Developed a maximum likelihood estimator (MLE) based on modeling localizations as two homogeneous Poisson processes.
  • Utilized discontinuity in localization density at the interface to estimate its position.
  • Tested the MLE using experimental iPAINT data of oil-water interfaces and Monte Carlo simulations.

Main Results:

  • The MLE rapidly converges to the true interface location in simulations.
  • The estimation error of the MLE falls below the experimental localization precision.
  • The MLE demonstrates accuracy even with reduced fields-of-view or particles present at the interface.

Conclusions:

  • The proposed MLE method offers a significant advancement for accurately determining soft interface locations.
  • This technique is robust and maintains accuracy under various experimental conditions.
  • The study provides a crucial step towards sub-micron characterization of interfaces with minimal invasiveness.