Carbon nanotubes have an exciting array of applications which span mechanical, electrical, thermal and chemical/sensing. However, full exploitation is slowed by a lack of control over synthesis. Despite the two decades since the explosion of work in the area, progress in controlled production of nanotubes is impeded by our lack of understanding of the fundamental mechanisms of nucleation and growth. To this end, we have developed a method, Automated Rapid Experimentation and in-situ Spectroscopy (ARES) which speeds the rate of experimentation by 100 times. We are also exploring experimental parameter space autonomously, using the same AI and machine learning approaches used in advanced robotics. Our intent is to integrate computation and simulation explicitly into our closed-loop experimentation system to direct the path of exploration, yielding faster results with better fidelity than conventional approaches. We use this to determine the conditions which discriminate between single wall and multiwall carbon nanotube synthesis.
"Automated Experimentation Applied to Carbon Nanotube Synthesis", Dr. Benji Maruyan, Senior Materials Research Engineer, Air Force Research Laboratory
Thursday, 12 February 2015 - 11:40am