Self-Solidifying Active Droplets Showing Memory-Induced Chirality.

Area of Science:

• Materials Science
• Chemical Engineering
• Robotics

Background:

• Synthetic microswimmers often lack autonomous energy and diverse motion capabilities compared to biological counterparts.
• Current microswimmer designs face challenges in energy supply and complex movement patterns.

Purpose of the Study:

• To develop the first all-aqueous droplet microswimmer powered by self-generated polyelectrolyte gradients.
• To investigate memory-induced chirality and self-solidification in microswimmers.
• To demonstrate efficient toxin removal using autonomous microswimmers.

Main Methods:

• Utilizing an aqueous solution of surface tension-lowering polyelectrolytes that self-solidifies on acidic water.
• Inducing linear self-propulsion through spontaneous symmetry breaking via polyelectrolyte emission.
• Leveraging long-lived chemical trails from low-diffusion polyelectrolytes to induce memory effects and chiral motion.

Main Results:

• Achieved autonomous linear self-propulsion driven by self-generated chemical gradients.
• Demonstrated a transition from linear to chiral motion due to memory effects without external symmetry breaking.
• Showcased highly efficient uranium removal (up to 85%) within 90 minutes through self-propulsion and flow-induced mixing.

Conclusions:

• This work presents a novel route for fueling self-propelled microswimmers using self-generated gradients.
• The developed microswimmer autonomously transitions to chiral motion and can be utilized for environmental remediation.
• The findings pave the way for advanced autonomous agents capable of complex movements and targeted substance collection.