An official website of the United States government
Colloidal gels exhibit solid-like behavior at vanishingly small fractions of solids, owing to ramified space-spanning networks that form due to particle–particle interactions. These networks give the gel its rigidity, and with stronger attractions the elasticity grows as well. The emergence of rigidity can be described through a mean field approach; nonetheless, fundamental understanding of how rigidity varies in gels of different attractions is lacking. Moreover, recovering an accurate gelation phase diagram based on the system’s variables has been an extremely challenging task. Understanding the nature of colloidal clusters, and how rigidity emerges from their connections is key to controlling and designing gels with desirable properties. Here, we employ network analysis tools to interrogate and characterize the colloidal structures. We construct a particle-level network, having all the spatial coordinates of colloids with different attraction levels, and also identify polydisperse rigid fractal clusters using a Gaussian mixture model, to form a coarse-grained cluster network that distinctly shows main physical features of the colloidal gels. A simple mass-spring model then is used to recover quantitatively the elasticity of colloidal gels from these cluster networks. Interrogating the resilience of these gel networks shows that the elasticity of a gel (a dynamic property) is directly correlated to its cluster network’s resilience (a static measure). Finally, we use the resilience investigations to devise [and experimentally validate] a fully resolved phase diagram for colloidal gelation, with a clear solid–liquid phase boundary using a single volume fraction of particles well beyond this phase boundary.
more »
« less
Small variations in particle-level interactions lead to large structural heterogeneities in colloidal gels
More Like this
-
-
Linking the macroscopic flow properties and nanoscopic structure is a fundamental challenge to understanding, predicting, and designing disordered soft materials. Under small stresses, these materials are soft solids, while larger loads can lead to yielding and the acquisition of plastic strain, which adds complexity to the task. In this work, we connect the transient structure and rheological memory of a colloidal gel under cyclic shearing across a range of amplitudes via a generalized memory function using rheo-X-ray photon correlation spectroscopy (rheo-XPCS). Our rheo-XPCS data show that the nanometer scale aggregate-level structure recorrelates whenever the change in recoverable strain over some interval is zero. The macroscopic recoverable strain is therefore a measure of the nano-scale structural memory. We further show that yielding in disordered colloidal materials is strongly heterogeneous and that memories of prior deformation can exist even after the material has been subjected to flow.more » « less
-
Abstract The design of hydrogels where multiple interpenetrating networks enable enhanced mechanical properties can broaden their field of application in biomedical materials, 3D printing, and soft robotics. We report a class of self-reinforced homocomposite hydrogels (HHGs) comprised of interpenetrating networks of multiscale hierarchy. A molecular alginate gel is reinforced by a colloidal network of hierarchically branched alginate soft dendritic colloids (SDCs). The reinforcement of the molecular gel with the nanofibrillar SDC network of the same biopolymer results in a remarkable increase of the HHG’s mechanical properties. The viscoelastic HHGs show >3× larger storage modulus and >4× larger Young’s modulus than either constitutive network at the same concentration. Such synergistically enforced colloidal-molecular HHGs open up numerous opportunities for formulation of biocompatible gels with robust structure-property relationships. Balance of the ratio of their precursors facilitates precise control of the yield stress and rate of self-reinforcement, enabling efficient extrusion 3D printing of HHGs.more » « less
-
We measure and model monolayers of concentrated diffusing colloidal probes interacting with polymerized liquid crystal (PLC) planar surfaces. At topological defects in local nematic director profiles at PLC surfaces, we observe time-averaged two-dimensional particle density profiles of diffusing colloidal probes that closely correlate with spatial variations in PLC optical properties. An inverse Monte Carlo analysis of particle concentration profiles yields two-dimensional PLC interfacial energy landscapes on the kT -scale, which is the inherent scale of many interfacial phenomena ( e.g. , self-assembly, adsorption, diffusion). Energy landscapes are modelled as the superposition of macromolecular repulsion and van der Waals attraction based on an anisotropic dielectric function obtained from the liquid crystal birefringence. Modelled van der Waals landscapes capture most net energy landscape variations and correlate well with experimental PLC director profiles around defects. Some energy landscape variations near PLC defects indicate either additional local repulsive interactions or possibly the need for more rigorous van der Waals models with complete spectral data. These findings demonstrate direct, sensitive measurements of kT -scale van der Waals energy landscapes at PLC interfacial defects and suggest the ability to design interfacial anisotropic materials and van der Waals energy landscapes for colloidal assembly.more » « less
-
null (Ed.)Colloidal gels represent an important class of soft matter, in which networks formed due to strong, short-range interactions display solid-like mechanical properties, such as a finite low-frequency elastic modulus. Here we examine the effect of embedded active colloids on the linear viscoelastic moduli of fractal cluster colloidal gels. We find that the autonomous, out-of-equilibrium dynamics of active colloids incorporated into the colloidal network decreases gel elasticity, in contrast to observed stiffening effects of myosin motors in actin networks. Fractal cluster gels are formed by the well-known mechanism of aggregating polystyrene colloids through addition of divalent electrolyte. Active Janus particles with a platinum hemisphere are created from the same polystyrene colloids and homogeneously embedded in the gels at dilute concentration at the time of aggregation. Upon addition of hydrogen peroxide – a fuel that drives the diffusiophoretic motion of the embedded Janus particles – the microdynamics and mechanical rheology change in proportion to the concentration of hydrogen peroxide and the number of active colloids. We propose a theoretical explanation of this effect in which the decrease in modulus is mediated by active motion-induced softening of the inter-particle attraction. Furthermore, we characterize the failure of the fluctuation–dissipation theorem in the active gels by identifying a discrepancy between the frequency-dependent macroscopic viscoelastic moduli and the values predicted by microrheology from measurement of the gel microdynamics. These findings support efforts to engineer gels for autonomous function by tuning the microscopic dynamics of embedded active particles. Such reconfigurable gels, with multi-state mechanical properties, could find application in materials such as paints and coatings, pharmaceuticals, self-healing materials, and soft robotics.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1039/D4SM00316K
