Advancing Chemical Imaging at the Nanoscale: New Insights and Technologies from NanoSYD
At SDU NanoSYD, cutting-edge developments in nanoscale chemical imaging and environmental sensing are driving new frontiers in material science and sustainability research. Leveraging state-of-the-art Confocal Raman Spectroscopy and Nano-FTIR, our team is uncovering novel insights into the composition and interactions of nanomaterials, with direct applications in environmental monitoring, sustainable materials, and advanced photonic devices.
Expanding the Capabilities of Chemical Imaging
Recent advancements in our Confocal Raman Spectroscopy and Nano-FTIR facilities allow for unprecedented resolution in vibrational spectroscopy, enabling the precise characterization of materials at the nanoscale. These techniques provide critical insights into molecular composition, structural properties, and chemical interactions, supporting research in:
- Quantum and Polaritonic Materials: Investigating excitonic and plasmonic properties at nanometer resolution.
- Thin Films and Nanocomposites: Understanding chemical bonding, phase transitions, and interface properties.
- Environmental and Biomedical Applications: Mapping contaminants, biointerfaces, and complex organic-inorganic hybrid materials.
With the integration of AI-assisted spectral analysis, our researchers are enhancing data interpretation, improving sensitivity, and enabling real-time chemical identification in highly complex material systems.
New Developments in Environmental Sensing: Plastics and PFAS Detection
Environmental monitoring remains a core focus at NanoSYD, particularly in the detection of nanoplastics and perfluoroalkyl substances (PFAS)—two major pollutants impacting ecosystems and human health.
- Nanoplastics in the Environment: Tracking Contamination
As part of the PlastTrack project, NanoSYD researchers are utilizing Confocal Raman Spectroscopy and Nano-FTIR to study the environmental pathways of nanoplastics in water, soil, and biological systems. By identifying characteristic molecular fingerprints, we are developing high-sensitivity detection workflows to assess plastic degradation, bioaccumulation, and potential toxicity. - Rapid PFAS Detection with Raman Spectroscopy
In collaboration with WaterCareGuard and LightNovo ApS, we are developing a portable Raman-based detection system for PFAS monitoring. This innovative technology enables on-site, real-time identification of PFAS contaminants in drinking water and industrial wastewater, offering a fast, non-invasive, and highly selective sensing solution.
Towards a More Sustainable Future
These advancements reinforce NanoSYD’s position as a leading nanoscale chemical imaging and environmental sensing research . Through interdisciplinary collaborations and cutting-edge spectroscopic methodologies, we continue to develop transformative solutions for sustainable materials, pollution monitoring, and next-generation nanotechnology applications.
Stay updated as we push the boundaries of chemical imaging and environmental sensing at the nanoscale!
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Next-Generation Environmental Sensing: AI for Plastics and PFAS Detection
NanoSYD is at the forefront of AI-powered environmental sensing, focusing on detecting and characterizing nanoplastics and perfluoroalkyl substances (PFAS)—key pollutants with significant ecological and health impacts.
- Tracking Nanoplastics in the Environment
As part of the PlastTrack project, we are using Confocal Raman Spectroscopy, Nano-FTIR, and AI-based spectral recognition to map nanoplastic contamination in environmental and biological systems. By employing deep learning models for automated identification, we enhance the detection of plastic particles down to the nanometer scale, improving our understanding of their degradation, transport, and biological interactions. - AI-Driven PFAS Detection with Raman Spectroscopy
In collaboration with WaterCareGuard and LightNovo ApS, we are developing a portable AI-enhanced Raman-based detection system for rapid and precise PFAS monitoring in water sources. By integrating AI-based spectral interpretation, this system provides real-time, field-deployable identification of PFAS contamination, significantly improving the speed and accuracy of on-site testing.
People involved: Jacek Fiutowski, Ayoub Laghrissi, Casper Kunstmann, Arkadiusz Goszczak, Marcus Alexander Johns, Till Leissner and Roana Hansen.