Search for: All records

Increasingly functional microscopic machines are poised to have massive technical influence in areas including targeted drug delivery, precise surgical interventions, and environmental remediation. Such functionalities would increase markedly if collections of these microscopic machines were able to coordinate their function to achieve cooperative emergent behaviors. Implementing such coordination, however, requires a scalable strategy for synchronization—a key stumbling block for achieving collective behaviors of multiple autonomous microscopic units. Here, we show that pulse-coupled complementary metal-oxide semiconductor oscillators offer a tangible solution for such scalable synchronization. Specifically, we designed low-power oscillating modules with attached mechanical elements that exchange electronic pulses to advance their neighbor’s phase until the entire system is synchronized with the fastest oscillator or “leader.” We showed that this strategy is amenable to different oscillator connection topologies. The cooperative behaviors were robust to disturbances that scrambled the synchronization. In addition, when connections between oscillators were severed, the resulting subgroups synchronized on their own. This advance opens the door to functionalities in microscopic robot swarms that were once considered out of reach, ranging from autonomously induced fluidic transport to drive chemical reactions to cooperative building of physical structures at the microscale. 

We propose a design paradigm for multistate machines where transitions from one state to another are organized by bifurcations of multiple equilibria of the energy landscape describing the collective interactions of the machine components. This design paradigm is attractive since, near bifurcations, small variations in a few control parameters can result in large changes to the system’s state providing an emergent lever mechanism. Further, the topological configuration of transitions between states near such bifurcations ensures robust operation, making the machine less sensitive to fabrication errors and noise. To design such machines, we develop and implement a new efficient algorithm that searches for interactions between the machine components that give rise to energy landscapes with these bifurcation structures. We demonstrate a proof of concept for this approach by designing magnetoelastic machines whose motions are primarily guided by their magnetic energy landscapes and show that by operating near bifurcations we can achieve multiple transition pathways between states. This proof of concept demonstration illustrates the power of this approach, which could be especially useful for soft robotics and at the microscale where typical macroscale designs are difficult to implement. 

Microscopic robots controlled by onboard integrated circuits that walk when powered by light are realized.