Hydrodynamic coupling melts acoustically levitated crystalline rafts.

Going beyond the manipulation of individual particles, first steps have recently been undertaken with acoustic levitation in air to investigate the collective dynamical properties of many-body systems self-assembled within the levitation plane. However, these assemblies have been limited to two-dimensional, close-packed rafts where forces due to scattered sound pull particles into direct frictional contact. Here, we overcome this restriction using particles small enough that the viscosity of air establishes a repulsive streaming flow at close range. By tuning the particle size relative to the characteristic length scale for viscous streaming, we control the interplay between attractive and repulsive forces and show how particles can be assembled into monolayer lattices with tunable spacing. While the strength of the levitating sound field does not affect the particles' steady-state separation, it controls the emergence of spontaneous excitations that can drive particle rearrangements in an effectively dissipationless, underdamped environment. Under the action of these excitations, a quiescent particle lattice transitions from a predominantly crystalline structure to a two-dimensional liquid-like state. We find that this transition is characterized by dynamic heterogeneity and intermittency, involving cooperative particle movements that remove the timescale associated with caging for the crystalline lattice. These results shed light on the nature of athermal excitations and instabilities that can arise from strong hydrodynamic coupling among interacting particles.

Stress-activated friction in sheared suspensions probed with piezoelectric nanoparticles.

A hallmark of concentrated suspensions is non-Newtonian behavior, whereby the viscosity increases dramatically once a characteristic shear rate or stress is exceeded. Such strong shear thickening is thought to originate from a network of frictional particle-particle contact forces, which forms under sufficiently large stress, evolves dynamically, and adapts to changing loads. While there is much evidence from simulations for the emergence of this network during shear thickening, experimental confirmation has been difficult. Here, we use suspensions of piezoelectric nanoparticles and exploit the strong local stress focusing within the network to activate charge generation. This charging can then be detected in the measured ac conductance and serve as a signature of frictional contact formation. The direct link between stress-activated frictional particle interactions and piezoelectric suspension response is further demonstrated by tracking the emergence of structural memory in the contact network under oscillatory shear and by showing how stress-activated friction can drive mechano-transduction of chemical reactions with nonlinear reaction kinetics. Taken together, this makes the ac conductance of piezoelectric suspensions a sensitive in-situ reporter of the micromechanics associated with frictional interactions.

Acoustic manipulation of multi-body structures and dynamics.

Sound can exert forces on objects of any material and shape. This has made the contactless manipulation of objects by intense ultrasound a fascinating area of research with wide-ranging applications. While much is understood for acoustic forcing of individual objects, sound-mediated interactions among multiple objects at close range gives rise to a rich set of structures and dynamics that are less explored and have been emerging as a frontier for research. We introduce the basic mechanisms giving rise to sound-mediated interactions among rigid as well as deformable particles, focusing on the regime where the particles' size and spacing are much smaller than the sound wavelength. The interplay of secondary acoustic scattering, Bjerknes forces, and micro-streaming is discussed and the role of particle shape is highlighted. Furthermore, we present recent advances in characterizing non-conservative and non-pairwise additive contributions to the particle interactions, along with instabilities and active fluctuations. These excitations emerge at sufficiently strong sound energy density and can act as an effective temperature in otherwise athermal systems.

Dynamic-bond-induced sticky friction tailors non-Newtonian rheology.

Frictional network formation has become a new paradigm for understanding the non-Newtonian shear-thickening behavior of dense suspensions. Recent studies have exclusively focused on interparticle friction that instantaneously vanishes when applied shear is ceased. Herein, we investigate a friction that emerges from dynamic chemical bridging of functionalized particle surfaces sheared into close proximity. This enables tailoring of both friction magnitude and the time release of the frictional coupling. The experiments use dense suspensions of thiol-functionalized particles suspended in ditopic polymers endcapped with benzalcyanoacetamide Michael-acceptors. The subsequent room temperature, catalyst-free dynamic thia-Michael reactions can form bridging interactions between the particles with dynamic covalent bonds that linger after formation and release in the absence of shear. This chemical friction mimics physical friction but is stickier, leading to tunable rheopexy. The effect of sticky friction on dense suspension rheology is explored by varying the electronic nature of the benzalcyanoacetamide moiety, the molecular weight of the ditopic polymers, the amount of a competitive bonding compound, and temperature. These results demonstrate how dynamic-bond-induced sticky friction can be used to systematically control the time dependence of the non-Newtonian suspension rheology.

Tuning the mechanical impedance of disordered networks for impact mitigation.

Disordered-Network Mechanical Materials (DNMM), comprised of random arrangements of bonds and nodes, have emerged as mechanical metamaterials with the potential for achieving fine control over their mechanical properties. Recent computational studies have demonstrated this control whereby an extremely high degree of mechanical tunability can be achieved in disordered networks via a selective bond removal process called pruning. In this study, we experimentally demonstrate how pruning of a disordered network alters its macroscopic dynamic mechanical response and its capacity to mitigate impact. Impact studies with velocities ranging from 0.1 m s-1 to 1.5 m s-1 were performed, using a mechanical impactor and a drop tower, on 3D printed pruned and unpruned networks comprised of materials spanning a range of stiffness. High-speed videography was used to quantify the changes in Poisson's ratio for each of the network samples. Our results demonstrate that pruning is an efficient way to reduce the transmitted force and impulse from impact in the medium strain rate regime (101 s-1 to 102 s-1). This approach provides an interesting alternative route for designing materials with tailored impact mitigating properties compared to random material removal based on open cell foams.

Direct observation of dynamic shear jamming in dense suspensions.

Liquid-like at rest, dense suspensions of hard particles can undergo striking transformations in behaviour when agitated or sheared. These phenomena include solidification during rapid impact, as well as strong shear thickening characterized by discontinuous, orders-of-magnitude increases in suspension viscosity. Much of this highly non-Newtonian behaviour has recently been interpreted within the framework of a jamming transition. However, although jamming indeed induces solid-like rigidity, even a strongly shear-thickened state still flows and thus cannot be fully jammed. Furthermore, although suspensions are incompressible, the onset of rigidity in the standard jamming scenario requires an increase in particle density. Finally, whereas shear thickening occurs in the steady state, impact-induced solidification is transient. As a result, it has remained unclear how these dense suspension phenomena are related and how they are connected to jamming. Here we resolve this by systematically exploring both the steady-state and transient regimes with the same experimental system. We demonstrate that a fully jammed, solid-like state can be reached without compression and instead purely with shear, as recently proposed for dry granular systems. This state is created by transient shear-jamming fronts, which we track directly. We also show that shear stress, rather than shear rate, is the key control parameter. From these findings we map out a state diagram with particle density and shear stress as variables. We identify discontinuous shear thickening with a marginally jammed regime just below the onset of full, solid-like jamming. This state diagram provides a unifying framework, compatible with prior experimental and simulation results on dense suspensions, that connects steady-state and transient behaviour in terms of a dynamic shear-jamming process.

Ultrathin Porous Hydrocarbon Membranes Templated by Nanoparticle Assemblies.

Porous polymer membranes are widely desired as catalyst supports, sensors, and active layers for separation membranes. We demonstrate that electron beam irradiation of freely suspended gold or Fe3O4 nanoparticle (NP) monolayer sheets followed by wet chemical etching is a high-fidelity strategy to template two-dimensional (2D) porous cross-linked hydrocarbon membranes. This approach, which relies on secondary electrons generated by the NP cores, can further be used to transform three-dimensional (3D) terraced gold NP supercrystals into 3D porous hydrocarbon membranes. We utilize electron tomography to show how the number of NP layers (monolayer to pentalayer) controls attenuation and scattering of the primary e-beam, which in turn determines ligand cross-link density and 3D pore structure. Electron tomography also reveals that many nanopores are vertically continuous because of preferential sintering of NPs. This work demonstrates new routes for the construction of functional nanoporous media.

Intrusion into Granular Media Beyond the Quasistatic Regime.

The drag force exerted on an object intruding into granular media is typically assumed to arise from additive velocity and depth dependent contributions. We test this with intrusion experiments and molecular dynamics simulations at constant speed over four orders of magnitude, well beyond the quasistatic regime. For a vertical cylindrical rod we find velocity dependence only right after impact, followed by a crossover to a common, purely depth-dependent behavior for all intrusion speeds. The crossover is set by the timescale for material, forced to well up at impact, to subsequently settle under gravity. These results challenge current models of granular drag.

The role of solvent molecular weight in shear thickening and shear jamming.

The application of stress can drive a dense suspension into a regime of highly non-Newtonian response, characterized by discontinuous shear thickening (DST) and potentially shear jamming (SJ), due to the formation of a frictionally stabilized contact network. Investigating how the molecular weight of the suspending solvent affects the frictional particle-particle interactions, we report on experiments with suspensions of fumed silica particles in polyethylene glycol (PEG). Focusing on the monomer-to-oligomer limit, with n = 1 to 8 ethylene oxide repeat units, we find that increasing n enhances shear thickening under steady-state shear and even elicits rapidly propagating shear jamming fronts, as assessed by high-speed ultrasound imaging of impact experiments. We associate this behavior with a weakening of the solvation layers surrounding the particles as n is increased, which thereby facilitates the formation of frictional contacts. We argue that for n larger than the monomer-to-oligomer limit the trend reverses and frictional interactions are diminished, as observed in prior experiments. This reversal occurs because the polymeric solvent transitions from being enthalpically bound to entropically bound to the particle surfaces, which strengthens solvation layers.

Auxetic metamaterials from disordered networks.

Recent theoretical work suggests that systematic pruning of disordered networks consisting of nodes connected by springs can lead to materials that exhibit a host of unusual mechanical properties. In particular, global properties such as Poisson's ratio or local responses related to deformation can be precisely altered. Tunable mechanical responses would be useful in areas ranging from impact mitigation to robotics and, more generally, for creation of metamaterials with engineered properties. However, experimental attempts to create auxetic materials based on pruning-based theoretical ideas have not been successful. Here we introduce a more realistic model of the networks, which incorporates angle-bending forces and the appropriate experimental boundary conditions. A sequential pruning strategy of select bonds in this model is then devised and implemented that enables engineering of specific mechanical behaviors upon deformation, both in the linear and in the nonlinear regimes. In particular, it is shown that Poisson's ratio can be tuned to arbitrary values. The model and concepts discussed here are validated by preparing physical realizations of the networks designed in this manner, which are produced by laser cutting 2D sheets and are found to behave as predicted. Furthermore, by relying on optimization algorithms, we exploit the networks' susceptibility to tuning to design networks that possess a distribution of stiffer and more compliant bonds and whose auxetic behavior is even greater than that of homogeneous networks. Taken together, the findings reported here serve to establish that pruned networks represent a promising platform for the creation of unique mechanical metamaterials.

Memory in Nonmonotonic Stress Relaxation of a Granular System.

We demonstrate experimentally that a granular packing of glass spheres is capable of storing memory of multiple strain states in the dynamic process of stress relaxation. Modeling the system as a noninteracting population of relaxing elements, we find that the functional form of the predicted relaxation requires a quantitative correction which grows in severity with each additional memory and is suggestive of interactions between elements. Our findings have implications for the broad class of soft matter systems that display memory and anomalous relaxation.

Shear Thickening and Jamming of Dense Suspensions: The "Roll" of Friction.

Particle-based simulations of discontinuous shear thickening (DST) and shear jamming (SJ) suspensions are used to study the role of stress-activated constraints, with an emphasis on resistance to gearlike rolling. Rolling friction decreases the volume fraction required for DST and SJ, in quantitative agreement with real-life suspensions with adhesive surface chemistries and "rough" particle shapes. It sets a distinct structure of the frictional force network compared to only sliding friction, and from a dynamical perspective leads to an increase in the velocity correlation length, in part responsible for the increased viscosity. The physics of rolling friction is thus a key element in achieving a comprehensive understanding of strongly shear-thickening materials.

Interparticle hydrogen bonding can elicit shear jamming in dense suspensions.

Dense suspensions of hard particles in a liquid can exhibit strikingly counter-intuitive behaviour, such as discontinuous shear thickening (DST)1-7 and reversible shear jamming (SJ) into a state where flow is arrested and the suspension is solid-like8-12. A stress-activated crossover from hydrodynamic interactions to frictional particle contacts is key for these behaviours2-4,6,7,9,13. However, in experiments, many suspensions show only DST, not SJ. Here we show that particle surface chemistry plays a central role in creating conditions that make SJ readily observable. We find the system's ability to form interparticle hydrogen bonds when sheared into contact elicits SJ. We demonstrate this with charge-stabilized polymer microspheres and non-spherical cornstarch particles, controlling hydrogen bond formation with solvents. The propensity for SJ is quantified by tensile tests12 and linked to an enhanced friction by atomic force microscopy. Our results extend the fundamental understanding of the SJ mechanism and open avenues for designing strongly non-Newtonian fluids.

Stress Controlled Rheology of Dense Suspensions Using Transient Flows.

Dense suspensions of hard particles in a Newtonian liquid can be jammed by shear when the applied stress exceeds a certain threshold. However, this jamming transition from a fluid into a solidified state cannot be probed with conventional steady-state rheology because the stress distribution inside the material cannot be controlled with sufficient precision. Here we introduce and validate a method that overcomes this obstacle. Rapidly propagating shear fronts are generated and used to establish well-controlled local stress conditions that sweep across the material. Exploiting such transient flows, we can track how a dense suspension approaches its shear-jammed state dynamically and quantitatively map out the onset stress for solidification in a state diagram.

Controlling shear jamming in dense suspensions via the particle aspect ratio.

Dense suspensions of particles in a liquid exhibit rich, non-Newtonian behaviors such as shear thickening (ST) and shear jamming (SJ). ST has been widely studied and is known to be enhanced by increasing the particles' frictional interactions and also by making their shape more anisotropic. SJ however has only recently been understood to be a distinct phenomenon and, while the role of interparticle friction has been investigated, the role of particle anisotropy in controlling the SJ regime has remained unknown. To address this we here synthesize silica particles for use in water/glycerol suspensions. This pairing of hydrogen-bonding particle surfaces and suspension solvent has been shown to elicit SJ with spherical particles. We then vary particle aspect ratio from Γ = 1 (spheres) to Γ = 11 (slender rods), and perform rheological measurements to determine the effect of particle anisotropy on the onset of shear jamming. We also show that the effect on the precursor to SJ, discontinuous shear thickening (DST), is consistent with prior work. We find that increasing aspect ratio significantly reduces φm, the minimum particle packing fraction at which SJ can be observed, to values as low φm = 33% for Γ = 11. The ability to fix the properties of the solvated particle surfaces, and thus the particle interactions at contact, while varying shape anisotropy, yields fundamental insights about the SJ capabilities of suspensions and provides a framework to rationally design and tune these behaviors.

Turning statistical physics models into materials design engines.

Despite the success statistical physics has enjoyed at predicting the properties of materials for given parameters, the inverse problem, identifying which material parameters produce given, desired properties, is only beginning to be addressed. Recently, several methods have emerged across disciplines that draw upon optimization and simulation to create computer programs that tailor material responses to specified behaviors. However, so far the methods developed either involve black-box techniques, in which the optimizer operates without explicit knowledge of the material's configuration space, or require carefully tuned algorithms with applicability limited to a narrow subclass of materials. Here we introduce a formalism that can generate optimizers automatically by extending statistical mechanics into the realm of design. The strength of this approach lies in its capability to transform statistical models that describe materials into optimizers to tailor them. By comparing against standard black-box optimization methods, we demonstrate how optimizers generated by this formalism can be faster and more effective, while remaining straightforward to implement. The scope of our approach includes possibilities for solving a variety of complex optimization and design problems concerning materials both in and out of equilibrium.

Conforming nanoparticle sheets to surfaces with Gaussian curvature.

Nanoparticle monolayer sheets are ultrathin inorganic-organic hybrid materials that combine highly controllable optical and electrical properties with mechanical flexibility and remarkable strength. Like other thin sheets, their low bending rigidity allows them to easily roll into or conform to cylindrical geometries. Nanoparticle monolayers not only can bend, but also cope with strain through local particle rearrangement and plastic deformation. This means that, unlike thin sheets such as paper or graphene, nanoparticle sheets can much more easily conform to surfaces with complex topography characterized by non-zero Gaussian curvature, like spherical caps or saddles. Here, we investigate the limits of nanoparticle monolayers' ability to conform to substrates with Gaussian curvature by stamping nanoparticle sheets onto lattices of larger polystyrene spheres. Tuning the local Gaussian curvature by increasing the size of the substrate spheres, we find that the stamped sheet morphology evolves through three characteristic stages: from full substrate coverage, where the sheet extends over the interstices in the lattice, to coverage in the form of caps that conform tightly to the top portion of each sphere and fracture at larger polar angles, to caps that exhibit radial folds. Through analysis of the nanoparticle positions, obtained from scanning electron micrographs, we extract the local strain tensor and track the onset of strain-induced dislocations in the particle arrangement. By considering the interplay of energies for elastic and plastic deformations and adhesion, we construct arguments that capture the observed changes in sheet morphology as Gaussian curvature is tuned over two orders of magnitude.

Impact-activated solidification of dense suspensions via dynamic jamming fronts.

Although liquids typically flow around intruding objects, a counterintuitive phenomenon occurs in dense suspensions of micrometre-sized particles: they become liquid-like when perturbed lightly, but harden when driven strongly. Rheological experiments have investigated how such thickening arises under shear, and linked it to hydrodynamic interactions or granular dilation. However, neither of these mechanisms alone can explain the ability of suspensions to generate very large, positive normal stresses under impact. To illustrate the phenomenon, such stresses can be large enough to allow a person to run across a suspension without sinking, and far exceed the upper limit observed under shear or extension. Here we show that these stresses originate from an impact-generated solidification front that transforms an initially compressible particle matrix into a rapidly growing jammed region, ultimately leading to extraordinary amounts of momentum absorption. Using high-speed videography, embedded force sensing and X-ray imaging, we capture the detailed dynamics of this process as it decelerates a metal rod hitting a suspension of cornflour (cornstarch) in water. We develop a model for the dynamic solidification and its effect on the surrounding suspension that reproduces the observed behaviour quantitatively. Our findings suggest that prior interpretations of the impact resistance as dominated by shear thickening need to be revisited.

Evolutionary strategy for inverse charge measurements of dielectric particles.

We report a computational strategy to obtain the charges of individual dielectric particles from experimental observation of their interactions as a function of time. This strategy uses evolutionary optimization to minimize the difference between trajectories extracted from the experiment and simulated trajectories based on many-particle force fields. The force fields include both Coulombic interactions and dielectric polarization effects that arise due to particle-particle charge mismatch and particle-environment dielectric contrast. The strategy was applied to systems of free falling charged granular particles in a vacuum, where electrostatic interactions are the only driving forces that influence the particles' motion. We show that when the particles' initial positions and velocities are known, the optimizer requires only an initial and final particle configuration of a short trajectory in order to accurately infer the particles' charges; when the initial velocities are unknown and only the initial positions are given, the optimizer can learn from multiple frames along the trajectory to determine the particles' initial velocities and charges. While the results presented here offer a proof-of-concept demonstration of the proposed ideas, the proposed strategy could be extended to more complex systems of electrostatically charged granular matter.

Measuring the porosity and compressibility of liquid-suspended porous particles using ultrasound.

A key parameter describing the behavior of suspensions is the volume fraction ϕ of the solid particles that are dispersed in the liquid. Obtaining accurate values for ϕ becomes difficult for porous particles, because they can absorb some of the liquid. A prime example are the widely used cornstarch suspensions, for which ϕ usually is only estimated from the mass fraction of particles. Here we present a method to measure the effective porosity and compressibility of porous particles with ultrasound. We obtain the speed of sound in dilute cornstarch suspensions at multiple particle concentrations and with different solvent compressibilities. With the measured particle porosity of 0.31 we are able to calculate the volume fraction of the saturated particles reliably.