# Image-based 3D active sample stabilization on the nanometer scale for optical microscopy

## TL;DR

This paper introduces a new method for stabilizing microscope samples in 3D at the nanometer scale to improve super-resolution imaging quality.

## Contribution

A novel, easy-to-implement scheme for 3D active drift correction with nanometer-scale stability using a refined algorithm and open-source software.

## Key findings

- The method achieves ∼1 nm stability in 3D using both high and low numerical aperture objective lenses.
- The approach uses a simple widefield imaging path and open-source control software for easy adoption.
- The stabilization enhances data collection for diffraction-limited and super-resolution imaging techniques.

## Abstract

Super-resolution microscopy often entails long acquisition times of minutes to hours. Since drifts during the acquisition adversely affect data quality, active sample stabilization is commonly used for some of these techniques to reach their full potential. Although drifts in the lateral plane can often be corrected after acquisition, this is not always possible or may come with drawbacks. Therefore, it is appealing to stabilize sample position in three dimensions (3D) during acquisition. Various schemes for active sample stabilization have been demonstrated previously, with some reaching sub-nanometer stability in 3D. Here, we present a scheme for active drift correction that delivers the nanometer-scale 3D stability demanded by state-of-the-art super-resolution techniques and is straightforward to implement compared to previous schemes capable of reaching this level of stabilization precision. Using a refined algorithm that can handle various types of reference structure, without sparse signal peaks being mandatory, we stabilized sample position to ∼1 nm in 3D using objective lenses both with high and low numerical aperture. Our implementation requires only the addition of a simple widefield imaging path and we provide an open-source control software with graphical user interface to facilitate easy adoption of the module. Finally, we demonstrate how this has the potential to enhance data collection for diffraction-limited and super-resolution imaging techniques using single-molecule localization microscopy and cryo-confocal imaging as showcases.