Michael A. Bevan’s research while affiliated with Johns Hopkins University and other places

Induced‐charge electroosmosis (ICEO) offers a practical approach to drive microscale flows by application of AC electric fields across polarizable surfaces, enabling diverse functions including microfluidic pumping, active cargo transport, and biosensing. While ICEO along pristine surfaces is well‐understood, practical applications of ICEO often require surface modifications that affect ICEO flows in a manner that is poorly understood. Here, this study introduces dielectrophoretic (DEP) polarizability measurement, DPM, as a method to study effects of surface modifications on surface polarizability and ICEO flows. The method entails DEP trapping of probe particles and analysis of their equilibrium motions to measure polarizability. This DPM‐generated polarizability data is then used to predict effects of surface modifications on ICEO flows and reveal the contribution of additional factors affecting ICEO. It compares predictions with experimentally observed changes to the speed of Janus particles traveling by ICEO‐driven induced‐charge electrophoresis. This study shows that DPM enables prediction of decreased particle speed upon protein capture by functional Janus particles and reveals that increased speed of polymer‐modified Janus particles likely arises from hydrodynamic factors. Overall, this work lays the foundation for investigating new ICEO‐driven systems with applications in complex environments, potentially including those encountered in biosensing, remediation, or cargo delivery.

We report a model to predict equilibrium density profiles for different shaped colloids in two-dimensional liquid, nematic, and crystal states in nonuniform external fields. The model predictions are validated against Monte Carlo simulations and optical microscopy experiments for circular, square, elliptical, and rectangular colloidal particles in AC electric fields between parallel electrodes. The model to predict the densities of all states of different shaped particles is based on a balance of the local quasi-2D osmotic pressure against a compressive force due to induced dipole-field interactions. The osmotic force balance employs equations of state for hard ellipse liquid, nematic, and crystal state osmotic pressures, which are extended to additional particle shapes. The resulting simple analytical model is shown to accurately predict particle densities within liquid, liquid crystal, and crystal states for a broad range of particle shapes, system sizes, and field conditions. These findings provide a basis for quantitative design and control of fields to assemble and reconfigure colloidal particles in interfacial materials and devices.

We report total internal reflection microscopy measurements of 3D trajectories of ensembles of micron sized colloidal particles near interfaces with and without adsorbed macromolecules. Evanescent wave scattering reveals nanometer scale motion normal to planar surfaces and sub-diffraction limit lateral motion is resolved via image analysis. Equilibrium and non-equilibrium analyses of particle trajectories reveal self-consistent position dependent energies (energy landscapes) and position dependent diffusivities (diffusivity landscapes) both perpendicular and parallel to interfaces. For bare colloids and surfaces, electrostatic and hydrodynamic interactions are accurately quantified with established analytical theories. For colloids and surfaces with adsorbed macromolecules, conservative forces are accurately quantified with models for interactions between brush layers, whereas directly measured position dependent diffusivities require novel models of spatially varying permeability within adsorbed layers. Agreement between spatially resolved interactions and diffusivities and rigorous simplified models provide a basis to consistently interpret, predict, and design colloidal transport in the presence of adsorbed macromolecules for diverse applications.

Microrobots have the potential for diverse applications, including targeted drug delivery and minimally invasive surgery. Despite advancements in microrobot design and actuation strategies, achieving precise control over their motion remains challenging due to the dominance of viscous drag, system disturbances, physicochemical heterogeneities, and stochastic Brownian forces. Here, a precise control over the interfacial motion of model microellipsoids is demonstrated using time‐varying rotating magnetic fields. The impacts of microellipsoid aspect ratio, field characteristics, and magnetic properties of the medium and the particle on the motion are investigated. The role of mobile micro‐vortices generated is highlighted by rotating microellipsoids in capturing, transporting, and releasing cargo objects. Furthermore, an approach is presented for controlled navigation through mazes based on real‐time particle and obstacle sensing, path planning, and magnetic field actuation without human intervention. The study introduces a mechanism of directing motion of microparticles using rotating magnetic fields, and a control scheme for precise navigation and delivery of micron‐sized cargo using simple microellipsoids as microbots.

We simulate and model diffusion of spherical colloids of radius, a, on spherical surfaces of radius, R, as a function of relative size and surface concentration. Using Brownian dynamics simulations, we quantify diffusion and microstructure at different concentrations ranging from single particles to dense crystalline states. Self-diffusion and structural metrics (pair distribution, local density, and topological charge) are indistinguishable between spheres and planes for all concentrations up to dense liquid states. For concentrations approaching and greater than the freezing transition, smaller spheres with higher curvature show increased diffusivities and nonuniform density/topological defect distributions, which differ qualitatively from planar surfaces. The total topological charge varies quadratically with sphere radius for dense liquid states and linearly with sphere radius for dense crystals with icosahedrally organized grain scars. Between the dense liquid and dense crystal states on spherical surfaces is a regime of fluctuating and interacting defect clusters. We show local density governs self-diffusion in dense liquids on flat and spherical surfaces via the pair distribution. In contrast, dynamic topological defects couple to finite diffusivities through freezing and in low density crystal states on spherical surfaces, where neither exist on flat surfaces.

We report a method to predict equilibrium concentration profiles of hard ellipses in nonuniform fields, including multiphase equilibria of fluid, nematic, and crystal phases. Our model is based on a balance of osmotic pressure and field mediated forces by employing the local density approximation. Implementation of this model requires development of accurate equations of state for each phase as a function of hard ellipse aspect ratio in the range k = 1–9. The predicted density profiles display overall good agreement with Monte Carlo simulations for hard ellipse aspect ratios k = 2, 4, and 6 in gravitational and electric fields with fluid–nematic, fluid–crystal, and fluid–nematic–crystal multiphase equilibria. The profiles of local order parameters for positional and orientational order display good agreement with values expected for bulk homogeneous hard ellipses in the same density ranges. Small discrepancies between predictions and simulations are observed at crystal–nematic and crystal–fluid interfaces due to limitations of the local density approximation, finite system sizes, and uniform periodic boundary conditions. The ability of the model to capture multiphase equilibria of hard ellipses in nonuniform fields as a function of particle aspect ratio provides a basis to control anisotropic particle microstructure on interfacial energy landscapes in diverse materials and applications.

Deposition of silica microparticles on glass substrates was measured as a function of cationic polymer-anionic surfactant composition and shear rate. Particles were initially deposited in quiescent conditions in different polymer-surfactant compositions, which were chosen based on prior measurements of composition-dependent polymer-surfactant interactions and deposition behavior (up to 0.5 wt % polymer and 12 wt % surfactant). Programmed shear and dilution profiles in a flow cell together with optical microscopy observation were used to continuously track particle deposition, detachment, and redeposition. Knowledge of the shear-dependent torque on each particle provides information on adhesive torque mediated by polymer-surfactant complexes. Detachment of colloids initially deposited by depletion interactions occurs at low shear rates (∼100 s-1) due to lack of tangential forces or an adhesive torque. Further dilution produced redeposition of particles that resisted detachment (up to ∼2000 s-1) as the result of strong cationic polymer bridge formation, presumably due to preferential surfactant removal. Dilution from different initial compositions indicates a pathway dependence of polymer-surfactant de-complexation into shear-resistant cationic bridges. These findings demonstrate the ability to program deposition behavior via the informed design of initial polymer-surfactant compositions and shear profiles. The particle trajectory analysis developed in this work provides an assay to screen composition-dependent colloidal deposition in diverse materials and applications.

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.