The mobility of polystyrene nanoparticles ranging in diameter from 300 nm to 2 μm was measured in dilute and semidilute solutions of partially hydrolyzed polyacrylamide. In this model system, the ratio of particle to polymer size controls the long-time diffusivity of nanoparticles. The particle dynamics transition from subdiffusive on short time scales to Fickian on long time scales, qualitatively similar to predictions for polymer dynamics using a Rouse model. The diffusivities extracted from the long-time Fickian regime, however, are larger than those predicted by the Stokes−Einstein equation and the bulk zero-shear viscosity and moreover do not collapse according to hydrodynamic models. The sizedependent deviations of the long-time particle diffusivities derive instead from the coupling between the dynamics of the particle and the polymer over the length scale of the particle. Although the long-time diffusivities collapse according to predictions, deviations of the short-time scaling exponents and the crossover time between subdiffusive and Fickian dynamics indicate that the particles are only partially coupled to the relaxation modes of the polymer.T ransport of nanoparticles through non-Newtonian media affects applications ranging from targeted drug delivery 1,2 to oil recovery 3,4 to nanocomposite materials. 5,6 In a homogeneous medium of viscosity η, the diffusivity of a particle with radius R NP is given by the Stokes−Einstein (SE) equation D SE = k B T/6πηR NP . As particle size approaches characteristic length scales in the medium, the continuum assumption underlying the SE relation no longer holds, and deviations from SE predictions appear. 7−10 Attempts to explain these deviations in mixtures of polymers and particles have focused on identifying the length scale that controls particle diffusion.In entangled polymer systems, the length scale controlling particle diffusion is the distance between entanglements. The diffusion of nanoparticles smaller than the entanglement mesh is unaffected by entanglement dynamics, but for larger particles diffusion is dictated by polymer reptation until SE behavior is recovered. 11−14 In unentangled systems, however, different physics must control nanoparticle diffusion. Hydrodynamic models treat the polymer solution as a homogeneous medium in which hydrodynamic interactions are screened over the correlation length between polymer chains ξ. 10,15,16 Scaling models describe the particle mobility in terms of the polymer dynamics, 13,17,18 which are set by the characteristic length scales ξ and the polymer radius of gyration R g . Identifying the relevant physics requires model systems that are compatible with a wide range of particle sizes and span the transition from dilute to semidilute regimes in unentangled solutions. In polyelectrolyte solutions, topological entanglements appear at concentrations orders of magnitude above c*, 19,20 enabling investigations of nanoparticle dynamics across a wide and previously inaccessible range of semidilute concentrations in the abs...
Soft robots, with their agile locomotion and responsiveness to environment, have attracted great interest in recent years. Liquid crystal elastomers (LCEs), known for their reversible and anisotropic deformation, are promising candidates as embedded intelligent actuators in soft robots. So far, most studies on LCEs have focused on achieving complex deformation in thin films over centimeter‐scale areas with relatively small specific energy densities. Herein, using an extrusion process, meter‐long LCE composite filaments that are responsive to both infrared light and electrical fields are fabricated. In the composite filaments, a small quantity of cellulose nanocrystals (CNCs) is incorporated to facilitate the alignment of liquid crystal molecules along the long axis of the filament. Up to 2 wt% carbon nanotubes (CNTs) is introduced into a LCE matrix without aggregation, which in turn greatly improves the mechanical property of filaments and their actuation speed, where the Young's modulus along the long axis reaches 40 MPa, the electrothermal response time is within 10 s. The maximum work capacity is 38 J kg−1 with 2 wt% CNT loading. Finally, shape transformation and locomotion in several soft robotics systems achieved by the dual‐responsive LCE/CNT composite filament actuators are demonstrated.
Bacteria overwhelmingly live in geometrically confined habitats that feature small pores or cavities, narrow channels, or nearby interfaces. Fluid flows through these confined habitats are ubiquitous in both natural and artificial environments colonized by bacteria. Moreover, these flows occur on time and length scales comparable to those associated with motility of bacteria and with the formation and growth of biofilms, which are surface-associated communities that house the vast majority of bacteria to protect them from host and environmental stresses. This review describes the emerging understanding of how flow near surfaces and within channels and pores alters physical processes that control how bacteria disperse, attach to surfaces, and form biofilms. This understanding will inform the development and deployment of technologies for drug delivery, water treatment, and antifouling coatings and guide the structuring of bacterial consortia for production of chemicals and pharmaceuticals.
Nanoparticle dynamics impact a wide range of biological transport processes and applications in nanomedicine and natural resource engineering. Differential dynamic microscopy (DDM) was recently developed to quantify the dynamics of submicron particles in solutions from fluctuations of intensity in optical micrographs. Differential dynamic microscopy is well established for monodisperse particle populations, but has not been applied to solutions containing weakly scattering polydisperse biological nanoparticles. Here we use bright-field DDM (BDDM) to measure the dynamics of protein-rich liquid clusters, whose size ranges from tens to hundreds of nanometers and whose total volume fraction is less than 10(-5). With solutions of two proteins, hemoglobin A and lysozyme, we evaluate the cluster diffusion coefficients from the dependence of the diffusive relaxation time on the scattering wave vector. We establish that for weakly scattering populations, an optimal thickness of the sample chamber exists at which the BDDM signal is maximized at the smallest sample volume. The average cluster diffusion coefficient measured using BDDM is consistently lower than that obtained from dynamic light scattering at a scattering angle of 90°. This apparent discrepancy is due to Mie scattering from the polydisperse cluster population, in which larger clusters preferentially scatter more light in the forward direction.
We measure the mobility of nanoparticles at low concentrations in non-Newtonian semidilute aqueous solutions of high-molecular-weight polyelectrolyte polymers. Using optical microscopy and particle tracking algorithms, we image and track hydrophilic polystyrene nanoparticles of diameter 400 nm moving in aqueous solutions of partially hydrolyzed polyacrylamide of molecular weight 8 000 000 Da and concentration of 0.0424.2 g/L. The effective diffusivity of the nanoparticles in the semidilute polymer solutions, extracted from the long-time limit of the mean-squared displacement using the Stokes–Einstein relation, is greater than that calculated from the zero-shear-rate viscosity measured using bulk rheology. For concentrations c > 0.42 g/L, the mean-square displacements (MSD) of particles measured as a function of lag time revealed that the particle dynamics are subdiffusive at short time scales and are Fickian on long time scales. The time scale for the crossover from subdiffusive to Fickian dynamics increases with increasing polymer concentration; moreover, it is longer than the relaxation time scale for polymer blobs and shorter than that for the chain. Our results suggest that the nanoparticle dynamics are coupled to those of the polymers on a length scale intermediate between the blob size and the end-to-end distance of the polymer.
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