Jeonbuk National University (JBNU) Department of Chemistry (Department Chair Seungjae Lee) has introduced a chemistry experiment system that combines a robotic arm and artificial intelligence (AI) into the regular curriculum, leading a paradigm shift in hands-on education.

As AI and automation technologies have recently emerged as central topics in science and technology, the JBNU Department of Chemistry has attracted attention by proactively applying techniques used in advanced research settings to undergraduate education, attempting to innovate laboratory instruction.

Through this system, students are taught how to use AI models to predict experimental results and how to automate repetitive or safety-critical laboratory procedures by controlling a robotic arm.

In practice, automated experiments focus on the basic acid–base reaction. A liquid dispenser quantitatively dispenses acid, base, and indicator solutions, after which the robotic arm carries out the entire process — moving vials, placing them on stirrers, and transferring them to an imaging stage for post-reaction imaging. The captured images are analyzed immediately and used to interpret the reaction outcomes.

Based on data and images accumulated from repeated experiments, AI-based models are constructed for tasks such as pH prediction, optimization of solution compositions, and acid–base titration analysis. Students thus experience the fundamentals of a closed-loop experimental workflow that spans experiment execution, data analysis, and condition optimization.

This allows students to naturally assimilate a future research cycle that combines basic chemistry experiments with robot and AI technologies in the classroom. It is expected to help them grow into next-generation interdisciplinary chemistry professionals who can apply traditional chemical knowledge alongside advanced automation and AI technologies.

JBNU also plans to expand this initiative to support students in acquiring not only traditional chemical knowledge but also AI, automation, and data-driven thinking. The university intends to extend the program to a variety of laboratory courses and develop it into a student-participatory AI laboratory education model.

Seungjae Lee, Department Chair of JBNU's Department of Chemistry, said, 'By introducing a modern program that goes beyond traditional laboratory instruction, we have significantly enhanced students' learning motivation and laid the foundation for training practice-oriented professionals.'

Meanwhile, the educational robot–AI system was developed by Professor Dongyeon Kim of the Department of Chemistry and the AI Education Advancement Team with support from the Ministry of Education's National University Promotion Project and the BK21 Project Division.