Get the latest tech news
New system dramatically speeds the search for polymer materials
MIT researchers developed a fully autonomous platform that can identify, mix, and characterize novel polymer blends until it finds the optimal blend. This system could streamline the design of new composite materials for sustainable biocatalysis, better batteries, cheaper solar panels, and safer drug-delivery materials.
This workflow could someday facilitate the discovery of polymer blend materials that lead to advancements like improved battery electrolytes, more cost-effective solar panels, or tailored nanoparticles for safer drug delivery. Building the robotic system involved numerous challenges, such as developing a technique to evenly heat polymers and optimizing the speed at which the pipette tip moves up and down. Being a platform technology and given the rapid advancement in machine learning and AI for material science, one can envision the possibility for this team to further enhance random heteropolymer performances or to optimize design based on end needs and usages,” says Ting Xu, a professor at the University of California at Berkeley, who was not involved with this work.
Or read this on r/tech
