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Metasurface-enhanced Raman spectroscopy is used to characterize theclassical,crossover, andquantumregimes of a colloidal metasurface as a function of gap distance. 

Atomic force microscopy (AFM), in particular force spectroscopy, is a powerful tool for understanding the supramolecular structures associated with polymers grafted to surfaces, especially in regimes of low polymer density where different morphological structures are expected. In this study, we utilize force volume mapping to characterize the nanoscale surfaces of Ag nanocubes (AgNCs) grafted with a monolayer of polyethylene glycol (PEG) chains. Spatially resolved force−distance curves taken for a single AgNC were used to map surface properties, such as adhesion energy and deformation. We confirm the presence of surface octopus micelles that are localized on the corners of the AgNC, using force curves to resolve structural differences between the micelle “bodies” and “legs”. Furthermore, we observe unique features of this system including a polymer corona stemming from AgNC−substrate interactions and polymer bridging stemming from particle−particle interactions. 

Abstract Many-body interactions between polymer-grafted nanoparticles (NPs) play a key role in promoting their assembly into low-dimensional structures within polymer melts, even when the particles are spherical and isotropically grafted. However, capturing such interactions in simulations of NP assembly is very challenging because explicit modeling of the polymer grafts and melt chains is highly computationally expensive, even using coarse-grained models. Here, we develop a many-body potential for describing the effective interactions between spherical polymer-grafted NPs in a polymer matrix through a machine-learning approach. The approach involves using permutationally invariant polynomials to fit two- and three-body interactions derived from the potential of mean force calculations. The potential developed here reduces the computational cost by several orders of magnitude, thereby, allowing us to explore assembly behavior over large length and time scales. We show that the potential not only reproduces previously known assembled phases such as 1D strings and 2D hexagonal sheets, which generally cannot be achieved using isotropic two-body potentials, but can also help discover interesting phases such as networks, clusters, and gels. We demonstrate how each of these assembly morphologies intrinsically arises from a competition between two- and three-body interactions. Our approach for deriving many-body effective potentials can be readily extended to other colloidal systems, enabling researchers to make accurate predictions of their behavior and dissect the role of individual interaction energy terms of the overall potential in the observed behavior. 

Abstract Checkerboard lattices—where the resulting structure is open, porous, and highly symmetric—are difficult to create by self-assembly. Synthetic systems that adopt such structures typically rely on shape complementarity and site-specific chemical interactions that are only available to biomolecular systems (e.g., protein, DNA). Here we show the assembly of checkerboard lattices from colloidal nanocrystals that harness the effects of multiple, coupled physical forces at disparate length scales (interfacial, interparticle, and intermolecular) and that do not rely on chemical binding. Colloidal Ag nanocubes were bi-functionalized with mixtures of hydrophilic and hydrophobic surface ligands and subsequently assembled at an air–water interface. Using feedback between molecular dynamics simulations and interfacial assembly experiments, we achieve a periodic checkerboard mesostructure that represents a tiny fraction of the phase space associated with the polymer-grafted nanocrystals used in these experiments. In a broader context, this work expands our knowledge of non-specific nanocrystal interactions and presents a computation-guided strategy for designing self-assembling materials.