Small Molecule Mediated Self Assembly of Multicomponent Nanocomposites

Hierarchically structured nanocomposites are a class of functional materials that enable structural control across multiple length scales. Their tunability can be leveraged to meet the demands of advanced device designs such as optoelectronics, nanoscale sensors, barrier coatings, and nanoporous filters. Recent insights into multi-blend nanocomposites reveal a pathway to overcome inherent constraints of conventional self assembly. By increasing compositional complexity, mixing entropy offsets unfavorable repulsive interactions, unlocking tunability not achievable by traditional macromolecule controls. These complex blends exhibit enhanced miscibility and reduced interfacial diffusion, allowing nanoscale mobility for programming structure. Here, we demonstrate the self assembly of nanocomposites composed of block copolymers, small molecules, and nanoparticles. In particular, we show that deliberate small molecule selection based on solubility, polarity, and steric considerations enable self assembly in diverse solvents. By decomposing the small molecule into its molecular substructures, we employ statistical analysis and machine learning models to correlate chemical descriptors with assembly behavior, providing a predictive framework for designing next-generation nanocomposite.