Search for: All records

Chemical concentration fields and flow patterns inside and outside of a spherical active droplet powered by collective chemotaxis. 

The phenomenon of the ‘coil-stretch’ (C-S) transition, wherein a long-chain polymer initially in a coiled state undergoes a sudden configuration change to become fully stretched under steady elongational flows, has been widely recognized. This transition can display intricate hysteresis behaviours under specific critical conditions, giving rise to unique rheological characteristics in dilute polymer solutions. Historically, microscopic stochastic models and Brownian dynamics simulations have shed light on the underlying mechanisms of the transition by uncovering bistable configurations of polymer chains. Following the initial work by Cerf (J. Chem. Phys., vol. 20, 1952, pp. 395–402), we introduce a continuum model in this study to investigate the C-S transition in a constant uniaxial elongational flow. Our approach involves approximating the unfolding process of the polymer chain as an axisymmetric deformation of an elastic particle. We make the assumption that the particle possesses uniform material properties, which can be represented by a nonlinear, strain-hardening constitutive equation to replicate the finite extensibility of the polymer chain. Subsequently, we analytically solve for the steady-state deformation using a polarization method. By employing this reduced model, we effectively capture the C-S transition and establish its specific correlations with material and geometric properties. The hysteresis phenomena can be comprehended through a force-balance analysis, which involves comparing the externally applied viscous forces with the intrinsic elastic responsive forces. We demonstrate that our model, while simple, unveils rich elastohydrodynamics of the C-S transition. 

Abstract Microrobots hold immense potential in biomedical applications, including drug delivery, disease diagnostics, and minimally invasive surgeries. However, two key challenges hinder their clinical translation: achieving scalable and precision fabrication, and enabling non‐invasive imaging and tracking within deep biological tissues. Magnetic particle imaging (MPI), a cutting‐edge imaging modality, addresses these challenges by detecting the magnetization of nanoparticles and visualizing superparamagnetic nanoparticles (SPIONs) with sub‐millimeter resolution, free from interference by biological tissues. This capability makes MPI an ideal tool for tracking magnetic microrobots in deep tissue environments. In this study, “TriMag” microrobots are introduced: 3D‐printed microrobots with three integrated magnetic functionalities—magnetic actuation, magnetic particle imaging, and magnetic hyperthermia. The TriMag microrobots are fabricated using an innovative method that combines two‐photon lithography for 3D printing biocompatible hydrogel structures with in situ chemical reactions to embed the hydrogel scaffold with Fe₃O₄nanoparticles for good MPI contrast and CoFe₂O₄nanoparticles for efficient magnetothermal heating. This approach enables scalable, precise fabrication of helical magnetic hydrogel microrobots. The resulting TriMag microrobots, with the synergistic effects of Fe₃O₄and CoFe₂O₄nanoparticles, demonstrate efficient magnetic actuation for controlled movement, precise imaging via MPI for imaging and tracking in biological fluid and organs, including porcine eye and mouse stomach, and magnetothermal heating for tumor ablation in a mouse model. By combining these capabilities, the fabrication and imaging approach provides a robust platform for non‐invasive monitoring and manipulation of microrobots for transformative applications in medical treatment and biological research. 

Microorganisms can efficiently navigate in anisotropic complex fluids, but the precise swimming mechanisms remain largely unexplored. Their dynamics are determined by the interplay between multiple effects, including the fluid's orientation order, swimmer's undulatory gait, and the finite length. Here we extend the numerical study of the two-dimensional undulatory motions of a flexible swimmer in lyotropic liquid-crystalline polymers (LCPs) by Lin et al. (2021) to the scenarios of arbitrary swimming directions with respect to the nematic director. The swimmer is modeled as a nearly inextensible yet flexible fiber with imposed traveling-wave like actuation. We investigate the orientation-dependent swimming behaviors in nematic LCPs for an infinite long sheet (i.e., Taylor's swimming sheet model) and finite-length swimmers. We demonstrate that the swimmer must be sufficiently stiff to produce undulatory deformations to gain net motions. Moreover, a motile finite-length swimmer can reorient itself to swim parallel with the nematic director, due to a net body torque arising from the asymmetric distribution of the polymer force along the body. 

We have developed a lattice Monte Carlo (MC) simulation based on the diffusion-limited aggregation model that accounts for the effect of the physical properties of small ions such as inorganic ions and large salt ions that mimic ionic liquids (ILs) on lithium dendrite growth. In our cellular automaton model, molecular and atomistic details are largely coarse-grained to reduce the number of model parameters. During lithium deposition, the cations of the salt and ILs form positively charged electrostatic shields around the tip of the dendrites, and the anions of the salt and ILs form negative local potential lumps in adjacent areas to the dendrite. Both of the effects change the distribution of the electrostatic potential and notably inhibit dendrite formation between electrodes. The applied voltage and the physical properties of the salt ions and ILs, such as the size of the ions, the size asymmetry between the cation and anion, the dielectric constant, the excluded volume of the ions, and the model parameter η , notably affect electric-field screening and hence the variation in the local potential, resulting in substantial changes in the aspect ratio and the average height of the dendrites. Our present results suggest that the large salts such as ILs more significantly inhibit the dendrite growth than the small ions, mainly because the ions highly dissociated in ILs can participate in electrostatic shielding to a greater degree. To reduce the computational complexity and burden of the MC simulation, we also constructed a surrogate model with ensemble neural networks.