We had the pleasure of hosting Amil Aligayev from the National Centre for Nuclear Research (Świerk) for an insightful session on innovative diagnostic technologies and molecular research.
Amil’s talk primarily focused on the development of a dual-mode SERS and colorimetric sensor designed to detect Volatile Organic Compound (VOC) biomarkers. By using hydrogel patches, this technology offers a non-invasive way to identify markers associated with lung cancer, potentially making screening more accessible and efficient. He explained how combining Surface-Enhanced Raman Scattering (SERS) with colorimetric sensing allows for high sensitivity and precision, marking a significant step toward more reliable tools for early medical diagnosis.
In addition to his work on physical sensors, Amil also discussed the application of Graph Neural Networks (GNNs) for the classification and detailed structural research of molecular materials. He highlighted how these models are used to test the relevance and viability of potential new materials by modeling complex atomic relationships. This approach allows researchers to validate which molecular structures are worth pursuing for real-world applications, moving beyond traditional trial-and-error methods.
A huge thank you to Amil for sharing such a diverse and interesting range of research with us!
