Cooperative intelligence in swarms of enzyme-nanobots
In nature, systems composed of self-propelling agents display complex behaviors such as signal interpretation, propagation, amplification and engage in collective motion mediated by interactions between different agents and their environment. Examples range from swarming bacteria to schooling fish and flocking birds. These self-organized systems have served as an inspiration for researchers seeking to achieve complexity in artificial systems composed of synthetic agents. A class of agents that has recently been demonstrated is of synthetic nanomachines (nanobots) that can self-propel thanks to the conversion of chemical energy, harvested from the environment, into motion. While most of the artificial nanobots have been explored at individual level, their collective emergent behavior, arising from inter-particle interactions through chemical and hydrodynamic fields, and through environment mediated interactions is yet to be properly studied. Understanding collective effects will be especially useful in biologically relevant environments, where a number of applications for these nanobot systems have been envisioned. 

i-NANOSWARMS aims to realize enzyme-powered nanobot swarms capable to self-propel using biocompatible and bioavailable fuels and display collective and cooperative behaviours through communication among them as well as with the host environment. The proposal is divided in three working packages. In WP1, I will create a toolbox of nanobots based on a library of enzymes and nanoparticle architectures to study communication and long-range signal propagation using enzyme cascades. WP2 will be devoted to the collective behavior of nanobot swarms, exploiting biomimetic strategies such as chemotaxis and stigmergy to guide and recruit other nanobots. WP3 aims at studying, as a proof-of-concept of the applicability of intelligent nanoswarms for biomedical applications, cooperative behavior among nanoswarms for enhanced drug delivery and medical imaging.