Korean researchers have developed a robotic system that evaluates newly developed catalysts faster than humans. The technology's high precision is expected to significantly reduce catalyst development time.
The Korea Institute of Energy Research (KIER) announced on the 12th that a research team led by Dr. Park Ji-chan at the Clean Fuel Research Laboratory has developed a system that fully automates complex and repetitive catalyst performance evaluation experiments.
Developing new catalysts requires large-scale repetitive experiments with frequent changes to catalyst composition and reaction conditions. However, conventional manual experiments are time-consuming, and results often varied even with identical samples when different researchers conducted the tests. While recent research has actively explored using computational science and AI to theoretically predict catalyst performance and automate experiments, certain steps remained difficult to automate, including sample replacement and loading, as well as consumable changes for overnight and extended continuous experiments.
The KIER research team overcame these limitations by developing an automation system using two robots. They divided the catalyst performance evaluation process into two stages, with each robot performing its tasks organically, enabling the entire experiment to proceed without human intervention. The researchers applied optimal integrated control logic allowing both robots to operate simultaneously and maintain continuous operation at each stage.
Using the developed system, the robots completed catalyst performance evaluation experiments in approximately 17 hours—tasks that would take humans about 32 days—demonstrating processing speeds 45 times faster. Experimental result variability decreased by approximately 32% compared to manual work, confirming significantly improved data reliability. This proved that stable operation and precise data collection are possible even in high-volume continuous experimental environments.
The research team has secured a domestic patent for the "Catalyst Performance Evaluation Automation System," enhancing the technology's credibility and establishing a foundation for commercialization. "This research proves that we can secure highly reliable data even in high-volume experimental environments, going beyond full automation of catalyst performance evaluation," said Dr. Park Ji-chan, a principal researcher. "We will expand the application scope to various catalytic reactions and materials research, strengthen the connection between theory and experiment, and advance toward AI-based catalyst development."