Macroscopic supramolecular self-assembly detection based on HALCON machine vision

Abstract

Macroscopic supramolecular self-assembly (MSSA) has emerged as a new area of research in the field of supramolecular chemistry. The construction of macroscopic supramolecular structures using interfacial assembly by modifying functional groups on the surface of macromolecules and exploiting the weak interactions between surface functional groups is gaining more and more attention. With the advancement of gel technology, significant progress has been made in MSSA. However, MSSA still faces challenges such as low detection efficiency and accuracy. In this paper, a MSSA detection technique based on HALCON machine vision is designed. The technique first locates the hydrogel block (HB) by shape-based template matching and then uses machine vision techniques to detect whether the HBs are assembled. Finally, through the self-assembly judgment and detection of 500 groups of HBs, the results show that the technology can efficiently and accurately complete the MSSA detection function, which is of great significance for the development of supramolecular chemistry.