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

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.