Autonomous Research Systems Applied to Carbon Nanotube Synthesis
We have developed a first-of-its-kind Autonomous Research System, ARES, capable of designing, executing, and analyzing its own experiments autonomously using artificial intelligence (AI) and Machine Learning (ML). The closed loop, iterative method enables ARES to design new experiments based on prior results dynamically, after each experiment; a first for materials research.
We are applying this method to understand and control the synthesis of single wall carbon nanotubes, in this case optimizing growth rate in (7) – dimensional parameter space. We use automated in situ Raman spectroscopy characterization of growth rate for CVD synthesis of carbon nanotubes as a metric for a target objective used by our AI planner. We use a random forest learning approach which models experimental results, and a genetic algorithm planner to propose new experiments expected to achieve the targeted growth rate.
We expect ARES to be a disruptive advance in the near future, combining advances in robotics, AI, data sciences and operando methods to enable us to attack high dimensional research problems that were previously intractable by current research processes. We are applying the ARES method to multiple problems, including Additive Manufacturing and defect engineering in graphene. Human-robot research teams have to potential to redefine the research process and lead to a Moore’s Law for the speed of research.
BIO: Dr. Benji Maruyama is the Leader of the Flexible Materials and Processes Research Team and Principal Materials Research Engineer in the Air Force Research Laboratory, Materials & Manufacturing Directorate. His focus area is on the synthesis and processing science of carbon nanotubes. Dr. Maruyama created and is developing a new method research: Autonomous Research Systems for Materials Development, a fully autonomous research robot. He is also the point of contact for carbon materials for the Materials and Manufacturing Directorate. His background and interests include carbon and Low-D nanomaterials, energy storage, field emission, carbon, polymer and metal matrix composites, imaging of complex 3D microstructures and combinatorial experimentation. He is currently involved in the study of the origins of chiral growth for carbon nanotubes, nanostructured materials for battery electrodes, in-situ experimentation, and catalyst development.