Modeling the Temperature-Dependent Size Change of Polydisperse Nano-objects using a Deep Generative Model

Nano Letters, vol. 24, pp. 4447–4453

Abstract

Modern microscopy techniques can be used to investigate soft nano-objects at the nanometer scale. However, time-consuming microscopy measurements combined with low numbers of observable polydisperse objects often limit the statistics. We propose a method for identifying the most representative objects from their respective point clouds. These point cloud data are obtained, for example, through the localization of single emitters in super-resolution fluorescence microscopy. External stimuli, such as temperature, can cause changes in the shape and properties of adaptive objects. Due to the demanding and time-consuming nature of super-resolution microscopy experiments, only a limited number of temperature steps can be performed. Therefore, we propose a deep generative model that learns the underlying point distribution of temperature-dependent microgels, enabling the reliable generation of unlimited samples with an arbitrary number of localizations. Our method greatly cuts down the data collection effort across diverse experimental conditions, proving invaluable for soft condensed matter studies.

Authors 7

1. Reza Azad Aachen Institute of Physical Chemistry

   RWTH Aachen University

   Affiliation as printed

   Institute of Physical Chemistry, RWTH Aachen University, 52074 Aachen, Germany

2. Pia Lenßen Aachen Institute of Physical Chemistry

   RWTH Aachen University

   Affiliation as printed

   Institute of Physical Chemistry, RWTH Aachen University, 52074 Aachen, Germany

3. Yiwei Jia Aachen Institute of Imaging & Computer Vision

   RWTH Aachen University

   Affiliation as printed

   Institute of Imaging and Computer Vision, RWTH Aachen University, 52056 Aachen, Germany

4. Martin Strauch Aachen Institute of Imaging & Computer Vision

   RWTH Aachen University

   Affiliation as printed

   Institute of Imaging and Computer Vision, RWTH Aachen University, 52056 Aachen, Germany

5. Berk Alperen Bener Aachen Institute of Physical Chemistry

   RWTH Aachen University

   Affiliation as printed

   Institute of Physical Chemistry, RWTH Aachen University, 52074 Aachen, Germany

6. Dorit Merhof corresponding

   University of Regensburg

   Affiliation as printed

   Institute of Image Analysis and Computer Vision, University of Regensburg, 93040 Regensburg, Germany

7. Dominik Wöll corresponding Aachen Institute of Physical Chemistry

   RWTH Aachen University

   Affiliation as printed

   Institute of Physical Chemistry, RWTH Aachen University, 52074 Aachen, Germany