Presentation Information
[25a-1BL-6]Hyperspectral imaging-based stimulus recognition patterns of polydiacetylene sensors
〇(D)Jiali Chen1, Kaori Sugihara1 (1.Tokyo Univ.)
Keywords:
Polydiacetylene,Hyperspectral imaging,Hyperspectral microscopy
Polyacetylene(PDA) stands out as a promising material for sensor design due to its visible color transition, on-demand modification capabilities, and straightforward assembly methods. Numerous advanced designs for biosensors, chemical sensors, and physical sensors based on this material continue to emerge, thanks to its responsiveness to various stimuli such as heat, pH, force, light, and biomolecules. However, despite these advantages, no PDA-based sensor has been successfully deployed in real-world applications, primarily due to its poor reproducibility. Hyperspectral imaging, an up-and-coming technology providing dual views of spatial and spectral resolution at the pixel level. In this work, conducted using hyperspectral microscopy, we demonstrated that the poor reproducibility of PDA sensors mainly comes from the structural diversity formed during the self-assembly process. Additionally, benefiting from hyperspectral microscopy, we found that different PDA structures exhibit corresponding structural transformation preferences when subjected to different types of stimuli. While poor reproducibility limits its efficacy as a macroscopic sensing tool, hyperspectral imaging has shown promise in visualizing stimulus recognition patterns of PDA from its structural transformation preference. Furthermore, we introduced peptides to PDA and extracted the stimulus recognition patterns from hyperspectral imaging. Despite the surprise, the result is consistent with the expectations that it exhibits distinct recognition patterns for different peptides. This finding suggests the potential use of polyacetylene as a biomolecular fingerprint, opening up new possibilities for its application in multifunctional sensing technologies.