Controlling superstructure of binary nanoparticle (NP) mixtures in three dimensions (3D) from self-assembly opens enormous opportunities for the design of novel materials with unique properties for a variety of applications, e.g. energy related, photonic, and phononic, applications. Here, we present a synthetic approach toward such materials from bottom-up type block copolymer (BCP)—metal nanoparticle (NP) co-assembly.

A BCP was used as a structure-directing agent for controlling spatial arrangement of metal NPs. Structure control of functional NPs at the nanoscale, mediated by BCP micro-phase separation, provides facile routes to nanostructured materials. In order to efficiently predict nanostructures of such materials, a novel theoretical approach was developed, allowing a level of complexity usually reserved to more costly molecular simulation treatments. The theory exhibits quantitative agreement with the experiment of a highly ordered 3-dimensional (3D) chiral metal nanoparticle (NP) network, synthesized via triblock terpolymer / ligand-stabilized NP self-assembly, and provides design criteria for controlling a range of NP based nanomaterial structures.

The intimate coupling of synthesis, in-depth electron tomographic characterization, and a recently developed field theory enables exquisite control of superstructure in highly ordered porous 3D continuous networks from single and binary mixtures of metal NPs. Quantitative analysis provided insights into short- and long-range NP-NP correlations, and local and global contributions to structural chirality in the networks. Results provide design rules for next generation mesoporous network superstructures from binary NP mixtures for potential applications in areas including catalysis and plasmonics

Kahyun Hur

Cornell University, Korea Institute of Science and Technology

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