Research Topics of Rüdiger Berger

My research is focussing on two topics: (1) Friction forces of liquid drops that slide over surfaces and (2) interfaces in battery materials.

Friction Force Measurements of Liquids on Surfaces

We built up a method that allows the measurement of forces required to slide sessile drops over surfaces. The forces were measured by means of a deflectable glass capillary stuck in the drop (image close by). The drop friction force instrument (DoFFI) allowed the investigation of sliding forces of water drops at defined velocities [1]. 
The DoFFI is a suitable tool allowing us to resolve different wetting phenomena of surfaces spatially (image close by). Thus, the DoFFI could even be applied for quality control of surfaces made by large-scale industrial processes. We used the DoFFI to investigate the "static" and a "kinetic" regime of sliding drops [2], pinning of defects [3] and slip stick motion of drops [4]. We are using the DoFFI to characterize omniphobic surfaces and study the interaction between transport and wetting processes within a Transfer Project of the collaborative reserach center 1194. We have combined friction force measurements with current measurements to better understand slide electrification processes DynaMo.

References:
[1] Dynamic Measurement of the Force Required to Move a Liquid Drop on a Solid Surface, D. W. Pilat et al., Langmuir 28, 16812-16820 (2012).
[2] How drops start sliding over solid surfaces Nan Gao et al., Nature Physics, 14, 191 - 196 (2018).
[3] Pinning forces of sliding drops at defects, A. Saal et al., Europhys. Lett. 139, 47001 (2022).
[4] Scanning Drop Friction Force Microscopy, C. Hinduja et al., Langmuir 38, 14635-14643 (2022).

Interfaces in Battery Materials

Interfaces play a major role in electrical devices. In case interfaces are heterogenous the electrical current that can flow through the interface locally varies. Such variations can be probed by advanced scanning probe microscopy methods.

We used conductive scanning froce microscopy (cSFM) to quantitify the current flow along individual nano-pillars made from P3HT and PCBM [1] (see also image). We investigated all-solid-state battery materials while charging an discharging. In particular, we use operando Kelvin probe force microscopy (KPFM) to map locally time-dependent electric potential changes in garnet-type solid electrolytes [2].

References:
[1] Controlled Mutual Diffusion between Fullerene and Conjugated Polymer Nanopillars in Ordered Heterojunction Solar Cells,  Jongkuk Ko et al., Advanced Materials Interfaces, 1600264 (2016). 
[2] Understanding the evolution of lithium dendrites at Li_6.25Al_0.25La₃Zr₂O₁₂ grain boundaries via operando microscopy techniques, C. Zhu et al., Nature Communications 14, 1300 (2023).

Machine Learning

We developed a deep learning-based super-resolution model to analyse videos of drops sliding down a tilted plate. We implemented a 4-segment super-resolution optimized-fitting (4S-SROF) method which increases the accuracy of measured contact angles by 21% for contact angles lower than 90° and by 33% for contact angles higher than 90° [1]. We explore the use of various regression and multivariate sequence analysis (MSA) models to estimate the drop width at a solid surface solely from side-view videos. This approach eliminates the need for cameras or mirrors to monitor changes in the width of drop. We can predict the width of sliding drops with an error of 2.4% [2].

References:
[1] Deep learning to analyze sliding drops, S. Shumaly, et al. Langmuir 38, 14635-14643 (2023).
[2] Estimating sliding drop width via side-view features using recurrent neural networks, S. Shumaly, et a., Scientific Reports 14, 12033 (2024).