Reconfigurable artificial microswimmers with internal feedback

Abstract

Self-propelling microparticles are often proposed as synthetic models for biological microswimmers, yet they lack the internally regulated adaptation of their biological counterparts. Conversely, adaptation can be encoded in larger-scale soft-robotic devices but remains elusive to transfer to the colloidal scale. Here, we create responsive microswimmers, powered by electro-hydrodynamic flows, which can adapt their motility via internal reconfiguration. Using sequential capillary assembly, we fabricate deterministic colloidal clusters comprising soft thermo-responsive microgels and light-absorbing particles. Light absorption induces preferential local heating and triggers the volume phase transition of the microgels, leading to an adaptation of the clusters' motility, which is orthogonal to their propulsion scheme. We rationalize this response via the coupling between self-propulsion and variations of particle shape and dielectric properties upon heating. Harnessing such coupling allows for strategies to achieve local dynamical control with simple illumination patterns, revealing exciting opportunities for developing tactic active materials.

Fig. 1. Fabrication of thermo-responsive reconfigurable dumbbells.

a Scheme of the deposition of polystyrene (PS) particles (step 1) and PNIPAM-co-MAA microgels (step 2) onto a PDMS template patterned with 2 × 4 μm² size traps. The arrow indicates the direction of the deposition. Particles are accumulated at the meniscus of the moving droplet and deposited into the traps via capillary forces. b AFM image in the water showing PS-microgel dumbbells in the traps before harvesting. The bright spheres are the PS colloids and the darker ones are the swollen microgels. c, d Schematic representation c and optical micrographs d of the light-driven reconfiguration of a dumbbell. Fluorescent illumination with a power density ρ_FL = 54 mW(mm)⁻² locally increases the temperature above the VPTT of the microgel, causing it to deswell and correspondingly induce a variation of the dumbbell’s geometry and dielectric properties. The transition is reversible upon removing the incident light. Scale bars: 2 μm.

Fig. 2. Experimental realization of adaptive active dumbbells.

a Schematic representation of the experimental cell, illustrating the transverse AC electric field E and the local illumination with fluorescent light, respectively generating motion and causing particle reconfiguration. b Examples of particle trajectories switching ρ_FL between 9 (blue trajectory) and 54 mW(mm)⁻² (magenta trajectory). At ρ_FL = 54 mW(mm)⁻², the PS particle heats the microgel above its volume phase transition temperature (VPTT), causing a motility change. c v (solid circles) and D_r (open triangles) as a function of illumination power density ρ_FL. The inset represents the persistence length (L_p) of the particles' trajectories as a function of ρ_FL. The color scale represents the corresponding temperatures. d Particle velocity as a function of time for two levels of illumination ρ_FL = 9 (shaded areas) and 54 (white area) mW(mm)⁻². Scale bar represents 20 μm. e Particle trajectory (×63 magnification) showing that at ρ_FL = 9 mW(mm)⁻² (blue) the particle swims toward the PS lobe (+v), and at ρ_FL = 54 mW(mm)⁻² (magenta) it changes direction and swims with the microgel in front (−v). The pink and white circles indicate the position of the PS particle and microgel, respectively. f Histogram of particle velocity (45 particles) at low ρ_FL (9 mW(mm)⁻²−gray area) and high ρ_FL (54 mW(mm)⁻²−white area). Error bars in all cases indicate the standard deviation of the data.

Fig. 3. Dielectric spectroscopy measurements.

a ${ϵ}_{\mathrm{eff}}^{\prime }$ and b ${\sigma }_{\mathrm{eff}}^{\prime }$ as a function of frequency f for an aqueous suspension of microgels (1 wt %) measured for T between 22 and 40 °C. The data are corrected to remove electrode polarization. c Permitivitty (${ϵ}_{\text{p}}^{\prime }$, open circles) and conductivity (${\sigma }_{\text{p}}^{\prime }$, open squares) vs. T at f = 1 kHz. d Real ($K^{\prime }$ top, open symbols) and imaginary part (K″ bottom, solid symbols) of the Claussius–Mossotti factor for each particle i, i.e., microgels (gray) and PS particles (pink). The values are obtained for each particle from Eq. (2), using the corresponding values of ${\sigma }_{\text{p}}^{\prime }$ and ${ϵ}_{\text{p}}^{\prime }$. The error bars indicate the standard deviation of the data.

Fig. 4. Feedback between propulsion mechanism and particle reconfiguration.

a EHDF velocities U_i for each particle calculated from Eq. (1) with the fitting parameters β₁ = 0.23 (PS) and β₂ = 4.4 (microgel). The schematics indicate the direction of the EHDFs, being either positive (repulsive) or negative (attractive). b Experimental values (symbols) and theoretical prediction (solid line) of dumbbell velocity as a function of temperature. The inset schemes indicate the EHD flows and final propulsion direction. y-error bars are the standard deviation of the velocity calculated for 45 dumbbells at each temperature. x-error bars correspond to the uncertainty in experimentally determining T. c Theoretical prediction of dumbbell velocity v as a function of T and size ratio between the PS sphere and the collapsed microgel (at 40 °C). The plot is obtained from Eq. (1) using the experimental temperature-dependent system properties (particle size and dielectric properties, solvent viscosity) as inputs and a single-temperature independent prefactor. The dashed red box highlights the experimentally accessible range of T and size ratios (the range of size ratios is estimated from the error bars in Fig. 4b). The red solid horizontal line corresponds to the black solid curve in Fig. 4b.

Fig. 5. Adapting swimming to light patterns.

a Combined transmission and epifluorescent micrograph of self-propelling dumbbells where the fluorescent light (ρ_FL = 0.2 mW(mm)⁻²) is confined within the dashed circle by partly closing the microscope diaphragm. Characteristic trajectories of active particles remaining outside (light blue to dark blue) or inside (red to yellow) the illuminated region, or crossing from one to the other (yellow to green). The trajectories are color-coded based on the instantaneous velocity. Upon entering the illuminated region, the dumbbell clearly slows down. Scale bar: 150 μm. b Particle velocities (absolute values) as a function of time for the three representative particles depicted in (a), using the same colors. Time t = 0 s corresponds to the fluorescent light being turned on. The shaded bands represent the error bars corresponding to the standard deviations of the instantaneous particle velocity over 0.4 s (four frames). c Particle number density inside ϕ_in (red–left axis) and outside the illuminated region ϕ_out (blue–right axis) versus time during on (white) and off (gray) cycles of the fluorescent light. The number density is normalized by the initial number density, $\overline{\varphi }$, of a uniform particle distribution before turning on the fluorescent light. The data are produced by cumulating three independent experiments. d Particle trajectories during the on–off cycles corresponding to the boxed regions in (c) color-coded by instantaneous velocity (averaged over four frames) for 50 frames (I) and 200 frames (II, III, IV). During the on cycles, the particles within the illuminated region significantly slow down and the persistence of their trajectories drops. During the off cycles, they return to their original swimming behavior. The particles outside the illuminated region are not affected. Scale bars represent 40 μm.

Fig. 6. Motion chirality control with L-shaped particles.

a Optical microscopy image of an L-shaped reconfigurable cluster comprising two PS particles and one microgel in MilliQ water at room temperature. The arrow indicates the microgel position b Trajectories of an L-shaped particle at two different levels of fluorescence light power density (ρ_FL = 9 mW(mm)⁻²–blue; ρ_FL = 54 mW(mm)⁻²–magenta). The schematics in the insets show the propulsion direction relative to the PS-microgel combination as a function of ρ_FL and the corresponding angular velocity Ω. Upon changing illumination density, the helical trajectory changes chirality, due to propulsion reversal, and pitch, due to shape reconfiguration. Scale bars: 5 μm. c Orientation angle as a function of time for a self-propelling L-shaped particle at different light illumination levels. Upon tuning ρ_FL up, the rotation changes direction and slows down. The change is fully reversible upon reducing the fluorescent light.