The innovative approach taken by the UNC/CMU team put them ahead of their competition.
"The UNC/CMU team will help build a general data science approach to push polymeric materials research towards properties-based objective functions," said Luke Baldwin, a research chemist and project manager with AFRL. "We are excited about bringing together advanced manufacturing with the aid of continuous flow chemistry, automation, active machine learning and reinforcement learning algorithms. Ultimately, AFRL is excited about the possibility of extending these strategies to new problem areas to accelerate chemistry and materials research across the defense sector."
Next steps for the team are to clearly define the scope, inputs and outputs that go into the work, Leibfarth said.
"This grant requires us to move fast. Because of this, the experimental and data science have to move in parallel," Leibfarth said. "We will continue making and characterizing materials through 3D printing. In parallel, we will iterate with the Isayev group to parameterize the chemical building blocks involved in the project and how they relate to the functional outcomes of the research."
"We plan to connect Leibfarth's robotic and 3D printing equipment with AI 'agent' that first will learn expert chemist skills. After that we will challenge a machine to perform experiment autonomously with a pursuit to exceed a human level capabilities and design polymer materials with record-breaking properties," Isayev added.
The NSIN is a problem-solving network in the U.S. Department of Defense that adapts to the emerging needs of those who serve in the defense of national security. Dedicated to the work of bringing together defense, academic and entrepreneurial innovators, the office collaborates with major universities and the venture community to develop solutions that drive national security innovation.
The results of this work will be broadly available to the research community and hopefully to benefit other projects in chemistry and materials science.