Eco-Friendly Synthesis of Aqua-Nanoparticles via e-Beam Induced Self-Assembly and Polymerization

Abstract

Understanding supramolecular nanoparticle formation pathways remains challenging despite their importance in materials science. Although these nanostructures emerge from "encoded" molecular components, the mechanisms governing assembly are poorly understood. We address this gap through a liquid-cell transmission electron microscopy platform that uses electron beam (e-beam) simultaneously as imaging tool and polymerization energy source. This water-based methodology eliminates organic solvents while enabling precise structural control, aligning with green chemistry. Our research utilizes specially designed rod-coil organic molecules that simultaneously self-assemble and polymerize under controlled e-beam irradiation in water. The developed platform enables real-time visualization of dynamic self-assembly kinetics, including diffusion, collision, fusion, and growth processes. This in-situ imaging provides unprecedented insights into the formation mechanisms of hierarchical nanostructures. By precisely tuning molecular parameters and irradiation conditions, we can kinetically control the assembly process to produce uniform nanoparticles with defined dimensions and morphologies. Our findings reveal that e-beam-induced polymerization can either promote or inhibit self-assembly, providing a powerful mechanism for structural control. We have successfully scaled this methodology beyond the microscope environment to develop a practical batch synthesis process that maintains precision and uniformity. This research contributes to understanding complex self-assembly processes while establishing a sustainable platform for producing uniform organic nanoparticles with applications in optoelectronics, energy harvesting, and biomedical fields. By combining molecular design, controlled polymerization, and advanced imaging techniques, we present a comprehensive strategy for synthesizing next-generation nanomaterials that balance maximal performance with minimal environmental impact.