Statistical Modeling of Ligand-Mediated Multimeric Nanoparticle Assembly

Understanding and controlling nanoparticle (NP) assembly have tremendous importance and impact in nanoscience, materials science, physical sciences, and nanobiotechnology. Although NP assembly has been heavily studied and used, a general model that describes the NP assembly process from a monomer to a multimer supported by experimental data has not been established. In this study, we developed a statistical model [NP self-assembly statistical estimation model with blocking and linking efficiency (NSSEMBLE)] to quantitatively describe multimeric NP assembly and provide directional information for forming, analyzing, and utilizing desired assembled nanostructures. The proposed approach is a straightforward probabilistic model considering the distribution of the ligands on NPs, ligand-linking efficiency, and excluded area based on the steric effect between NPs. As a proof of concept, we dem…