(605d) Quantitative Modeling of DNA Grafted Nanoparticle Self-Assembly

Authors: 
Kumar, S. K., Columbia University
Srinivasan, B., Columbia University
Gang, O., Brookhaven National Laboratory
Venkatasubramanian, V., Columbia University



Nanoparticle super-lattice engineering, which seeks to design DNA-grafted NPs that self-assemble into desired structures, is a growing field of research because of its relevance to optical band gap materials, sensors etc. In this protocol, single-stranded DNA sequences are grafted to NPs. This motif corresponds to a central NP core grafted with chains with “sticky” ends. DNA “sticky” ends across two particles with complementary strands can hybridize into double-stranded DNA, thus creating an emergent network of interconnected NPs, which under certain conditions crystallizes into a given lattice structure. A simple, but popular model for the prediction of DNA-grafted NP crystal structure was devised by Macfarlane. This Complementary Contact Model views DNA-NP complexes as “fuzzy spheres” where contacts between NPs lead to permanent DNA hybridization. However, despite its success, the model is limited in its prediction abilities to four broad classes of structure and cannot differentiate between different crystals within those classes. Here, we propose an extension of the model to allow for grafting of two different types of complementary linkers on each particle and incorporate hybridization between particles for both similar and different particles. These modifications enabled us to predict grafting density of DNA linkers on each particle that will result in a transition from a body-centered cubic structure to a face-centered cubic structure formation. Furthermore, the model can now differentiate between different types of crystal structure from the same class such as a disordered FCC, CuAu, and regular FCC structure – in a manner that is apparently in good agreement with the recent experiments of Gang and his coworkers. These new developments allow for a wider selection of design parameters of DNA-NP mixtures and thus can increase the selectivity of the final structure of the system.