Search for: All records

Conical surfaces pose an interesting challenge to crystal growth: A crystal growing on a cone can wrap around and meet itself at different radii. We use a disk-packing algorithm to investigate how this closure constraint can geometrically frustrate the growth of single crystals on cones with small opening angles. By varying the crystal seed orientation and cone angle, we find that—except at special commensurate cone angles—crystals typically form a seam that runs along the axial direction of the cone, while near the tip, a disordered particle packing forms. We show that the onset of disorder results from a finite-size effect that depends strongly on the circumference and not on the seed orientation or cone angle. This finite-size effect occurs also on cylinders, and we present evidence that on both cylinders and cones, the defect density increases exponentially as circumference decreases. We introduce a simple model for particle attachment at the seam that explains the dependence on the circumference. Our findings suggest that the growth of single crystals can become frustrated even very far from the tip when the cone has a small opening angle. These results may provide insights into the observed geometry of conical crystals in biological and materials applications. 

Many soft and biological materials display so-called ‘soft glassy’ dynamics; their constituents undergo anomalous random motions and complex cooperative rearrangements. A recent simulation model of one soft glassy material, a coarsening foam, suggested that the random motions of its bubbles are due to the system configuration moving over a fractal energy landscape in high-dimensional space. Here we show that the salient geometrical features of such high-dimensional fractal landscapes can be explored and reliably quantified, using empirical trajectory data from many degrees of freedom, in a model-free manner. For a mayonnaise-like dense emulsion, analysis of the observed trajectories of oil droplets quantitatively reproduces the high-dimensional fractal geometry of the configuration path and its associated local energy minima generated using a computational model. That geometry in turn drives the droplets’ complex random motion observed in real space. Our results indicate that experimental studies can elucidate whether the similar dynamics in different soft and biological materials may also be due to fractal landscape dynamics. 

Photonic balls are spheres tens of micrometers in diameter containing assemblies of nanoparticles or nanopores with a spacing comparable to the wavelength of light. When these nanoscale features are disordered, but still correlated, the photonic balls can show structural color with low angle-dependence. Their colors, combined with the ability to add them to a liquid formulation, make photonic balls a promising new type of pigment particle for paints, coatings, and other applications. However, it is challenging to predict the color of materials made from photonic balls because the sphere geometry and multiple scattering must be accounted for. To address these challenges, we develop a multiscale modeling approach involving Monte Carlo simulations of multiple scattering at two different scales: we simulate multiple scattering and absorption within a photonic ball and then use the results to simulate multiple scattering and absorption in a film of photonic balls. After validating against experimental spectra, we use the model to show that films of photonic balls scatter light in fundamentally different ways than do homogeneous films of nanopores or nanoparticles, because of their increased surface area and refraction at the interfaces of the balls. Both effects tend to sharply reduce color saturation relative to a homogeneous nanostructured film. We show that saturated colors can be achieved by placing an absorber directly in the photonic balls and mitigating surface roughness. With these design rules, we show that photonic-ball films have an advantage over homogeneous nanostructured films: their colors are even less dependent on the angle. 

Combining dielectric elastomers with photonic glasses enables homogeneous structural colors that can be rapidly tuned using voltage-triggered shape instabilities.

 

Objects that deform a liquid interface are subject to capillary forces, which can be harnessed to assemble the objects1–4. Once assembled, such structures are generally static. Here we dynamically modulate these forces to move objects in programmable two-dimensional patterns. We 3D-print devices containing channels that trap floating objects using repulsive capillary forces5,6, then move these devices vertically in a water bath. Because the channel cross-sections vary with height, the trapped objects can be steered in two dimensions. The device and interface therefore constitute a simple machine that converts vertical to lateral motion. We design machines that translate, rotate and separate multiple floating objects and that do work on submerged objects through cyclic vertical motion. We combine these elementary machines to make centimetre-scale compound machines that braid micrometre-scale filaments into prescribed topologies, including non-repeating braids. Capillary machines are distinct from mechanical, optical or fluidic micromanipulators in that a meniscus links the object to the machine. Therefore, the channel shapes need only be controlled on the scale of the capillary length (a few millimetres), even when the objects are microscopic. Consequently, such machines can be built quickly and inexpensively. This approach could be used to manipulate micrometre-scale particles or to braid microwires for high-frequency electronics. 

Understanding the pathways by which simple RNA viruses self-assemble from their coat proteins and RNA is of practical and fundamental interest. Although RNA–protein interactions are thought to play a critical role in the assembly, our understanding of their effects is limited because the assembly process is difficult to observe directly. We address this problem by using interferometric scattering microscopy, a sensitive optical technique with high dynamic range, to follow the in vitro assembly kinetics of more than 500 individual particles of brome mosaic virus (BMV)—for which RNA–protein interactions can be controlled by varying the ionic strength of the buffer. We find that when RNA–protein interactions are weak, BMV assembles by a nucleation-and-growth pathway in which a small cluster of RNA-bound proteins must exceed a critical size before additional proteins can bind. As the strength of RNA–protein interactions increases, the nucleation time becomes shorter and more narrowly distributed, but the time to grow a capsid after nucleation is largely unaffected. These results suggest that the nucleation rate is controlled by RNA–protein interactions, while the growth process is driven less by RNA–protein interactions and more by protein–protein interactions and intraprotein forces. The nucleated pathway observed with the plant virus BMV is strikingly similar to that previously observed with bacteriophage MS2, a phylogenetically distinct virus with a different host kingdom. These results raise the possibility that nucleated assembly pathways might be common to other RNA viruses. 

Using a combination of experiment and simulation, we study how two-dimensional (2D) crystals of colloidal nanoparticles grow on cylindrical substrates. The cylindrical geometry allows us to examine growth in the absence of Gaussian curvature but in the presence of a closure constraintthe requirement that a crystal loops back onto itself. In some cases, this constraint results in structures that have been observed previously in theory and nonequilibrium packing experiments: chiral crystals and crystals with linear defects known as “line slips”. More generally, though, the structures we see differ from those that have been observed: the line slips are kinked and contain partial vacancies. We show that these structures arise because the cylinder changes how the crystal grows. After a crystal wraps around the cylinder and touches itself, it must grow preferentially along the cylinder axis. As a result, crystals with a chiral line slip tend to trap partial vacancies. Indeed, we find that line slips that are less aligned with the cylinder axis incorporate more partial vacancies on average than the ones that are more aligned. These results show that crystal growth on a cylinder is frustrated by the closure requirement, a finding that may shed some light on the assembly of biological nanosystems such as tobacco mosaic virus and might inform ways to fabricate chiral optical nano materials. 

A high-yield chemical synthesis approach to making metal-coated nanoclusters results in precisely controlled plasmonic properties.

 

Disordered nanostructures with correlations on the scale of visible wavelengths can show angle-independent structural colors. These materials could replace dyes in some applications because the color is tunable and resists photobleaching. However, designing nanostructures with a prescribed color is difficult, especially when the application—cosmetics or displays, for example—requires specific component materials. A general approach to solving this constrained design problem is modeling and optimization: Using a model that predicts the color of a given system, one optimizes the model parameters under constraints to achieve a target color. For this approach to work, the model must make accurate predictions, which is challenging because disordered nanostructures have multiple scattering. To address this challenge, we develop a Monte Carlo model that simulates multiple scattering of light in disordered arrangements of spherical particles or voids. The model produces quantitative agreement with measurements when we account for roughness on the surface of the film, particle polydispersity, and wavelength-dependent absorption in the components. Unlike discrete numerical simulations, our model is parameterized in terms of experimental variables, simplifying the connection between simulation and fabrication. To demonstrate this approach, we reproduce the color of the male mountain bluebird (Sialia currucoides) in an experimental system, using prescribed components and a microstructure that is easy to fabricate. Finally, we use the model to find the limits of angle-independent structural colors for a given system. These results enable an engineering design approach to structural color for many different applications.