Biofilms in New Light: When Machine Learning Meets Nonlinear Optics

The central goal of this project is the development of neural network-based control and data acquisition software package for a custom-built multiphoton microscopy system employing ultrafast lasers. This minimally invasive and label-free diagnostic instrument represents a significant advance in health diagnostics. The automation and synchronization of AI/ML-supported imaging protocols enables high-resolution visualization of biological materials without the need for external dyes or markers. The hardware is based on a nonlinear optical method in the mid-infrared spectral range known as ultra-broadband vibrational sum-frequency generation (VSFG). It measures the low-frequency vibrational spectrum of a molecule and thus displays a characteristic fingerprint of a substance at physiologically relevant low sample concentrations at liquid/solid interfaces. The ability to detect relevant substances in low concentrations at complex interfaces makes it possible to unravel the molecular mechanisms involved in the formation of bacterial biofilms, for example, which can lead to better infection control strategies. The development potential of VSFG spectroscopy in the mid-infrared spectral range towards marker-free, chemically selective imaging is immense. Due to its extreme sensitivity, this technology can help to distinguish individual cancer cells from healthy tissue at a very early stage of cancer. The related challenges can only be met by closely linking DESY's research activities in the life sciences in the Science City Hamburg Bahrenfeld with methodologically oriented applied research in data science and applied mathematics at HAW. A key aspect is the cross-institutional and interdisciplinary training of talents, which is very important for DESY's future and provides HAW master students with valuable opportunities to gain research experience.