Chemotaxis is the movement of organisms toward or away from a chemical attractant or toxin by a biased random walk process. Here we describe the first experimental example of chemotaxis outside biological systems. Platinum-gold rods 2.0 microm long exhibit directed movement toward higher hydrogen peroxide concentrations through "active diffusion." Brownian dynamics simulations reveal that no "temporal sensing" algorithm, commonly attributed to bacteria, is necessary; rather, the observed chemotaxis can be explained by random walk physics in a gradient of the active diffusion coefficient.

Titanium dioxide (TiO2) possesses high photocatalytic activity, which can be utilized to power the autonomous motion of microscale objects. This paper presents the first examples of TiO2 micromotors and micropumps. UV‐induced TiO2 reversible microfireworks phenomenon was observed and diffusiophoresis has been proposed as a possible mechanism.

Randomness is an inherent property of biological systems. In contrast, randomness has been mostly avoided in designing synthetic or artificial systems. Particularly, in designing micro/nano-motors, some researchers have successfully used external fields to gain deterministic control over the directionality of the objects, which otherwise move in completely random directions due to Brownian motion. However, a partial control that preserves a certain degree of randomness can be very useful in certain applications of micro/nano-motors. In this Perspective we review the current progress in establishing autonomous motion of micro/nano-particles that possess controlled randomness, provide insight into the phenomena where macroscopic order originates from microscopic disorder and discuss the resemblance between these artificial systems and biological emergent/collective behaviors.

One of the more interesting recent discoveries has been the ability to design nano/ microparticles which catalytically harness the chemical energy in their environments to move autonomously. These "nanomotors" can be directed by externally applied magnetic fields, or optical and chemical gradients. Our group has now developed two systems in which chemical secretions from the translating micro/nanomotors initiate long-range, collective interactions among the particles via self-diffusiophoresis. Herein, we discuss two different approaches to model the complex emergent behavior of these particles, the first being a qualitative probability-based model with wide applicability, and the second being a more quantitative Brownian dynamics simulation specific to the self-diffusiophoretic phenomenon.

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