Imaging-Based Study on Control Factors over Self-Sorting of Supramolecular Nanofibers Formed from Peptide- and Lipid-type Hydrogelators.

Multicomponent self-assembly is a fascinating strategy for the construction of smart soft materials. Among them, supramolecular hydrogels comprising self-sorting nanofibers have recently attracted significant attention owing to their rationally incorporated stimulus responsiveness. However, there have been limited investigations of the crucial factors that control the self-sorting phenomena. Here, we describe an imaging-based approach to evaluate the factors that control the formation of self-sorting nanofibers from peptide- and lipid-type hydrogelators. We screened a small library of hydrogelators with distinct chemical properties by direct visualization of their self-assembly behavior by using confocal laser scanning microscopy. Our systematic research identified two important factors that influence the self-sorting behavior of nanofibers: (i) the surface charge of the hydrogelators; and (ii) the hydrophobicity of the side chain on the peptide-type hydrogelators. We determined that the same net/surface charge on the hydrogelators and side chains with a lower hydrophobicity on the peptide-type hydrogelators were preferred. These findings, in combination with the previously reported kinetic factors, were used to design and successfully prepare a three-component orthogonal self-assembly composed of supramolecular nanofibers from peptide- and lipid-type hydrogelators and a cationic organorhodium complex. Our findings would be beneficial for the design of intelligent soft materials based on self-sorting phenomena.