Oliver Steinbock, Cottrell Family Professor in the Department of Chemistry and Biochemistry, has previously used AI in his laboratory research to identify chemical compositions of dried salts from images. He is now exploring educational endeavors with the technology through AI-generated songs that explain core chemistry concepts, like thermodynamics and compression, and break down dense equations such as the van der Waals equation.
“I created these chemistry songs as a resource to teach concepts in a different way and create some new interest in the subject matter,” Steinbock said. “These songs can be used by students as at-home study tools, or lecturers could ask students to make their own songs about a topic as an in-class activity and have the students fact-check their songs. It’s just one tool in the toolbox of teaching.”
Steinbock’s 16-song playlist focuses on thermodynamics — the branch of physical chemistry covering interactions among heat, work, temperature and energy — and is available on Suno, a generative AI platform that creates songs based on user prompts. Through different musical genres, Steinbock’s songs teach the laws of thermodynamics, the essential rules of nature that define how energy operates in the universe, which are key foundations for physics and chemistry research.
“Physical chemistry is known as one of the hardest chemistry subjects to learn,” said Wei Yang, chair of the Department of Chemistry and Biochemistry and a professor of biochemistry. “Many students have a love-hate relationship with thermodynamics due to many key equations and concepts that they must comprehend and memorize.”