We will develop artificial, technological evolution and use it to design functional ecosystems consisting of up to three forms of living technology, namely, artificial chemical life, living microorganisms, and complex chemical reaction networks for the purpose of improved treatment and cleanup of wastewater for energy generation. The goals of this project are i) develop a general, robotic platform, which by using artificial evolution can optimize the performance of a physicochemical or microbial system and its environment and ii) use the robotic platform to evolve improved microbial fuel cells in terms of robustness, longevity, or adaptability. The robot evolutionary platform will take the form of an open-source 3D printer extended with functionality for handling liquids and reaction vessels, and for obtaining feedback from the reaction vessels either using computer vision or task-specific sensors in real-time. The robot platform will optimize parameters such as the environment, hydraulics or real-time interaction with experiments (for instance, timing of injection of nutrients, removal of metabolic products, stirring, etc.) to maximize a desired functionality. Initially, we investigate processes such as fluid-structure-interaction driving bio-aggregate structure and in turn metabolic activity as well as the interaction of nanoparticles and bacterial cells by analyzing the outcome of the evolutionary process using state-of-the-art imaging techniques. We then seek to exploit synergies between these technologies to significantly improve the ability of the living technology, in the form of optimized microbial fuel cells, to cleanup wastewater. Overall, this is a cross-disciplinary project involving state-of-the-art chemistry, imaging, robotics, artificial life, microbiology and bio-energy harvesting for the purpose of enhancing our understanding of living technologies and how to best design and exploit groundbreaking bio-hybrid systems.