Abstract: This study explores the innovative application of generative artificial intelligence (AI) in the simulation of acid-base titration images. Through hands-on experimentation, we employed generative AI techniques to develop code for dynamic acid-base titration images, establishing a “code generation and optimization for experimental images” paradigm. This approach is tightly aligned with the practical needs of educational settings, aiming to offer cutting-edge technological support for chemistry educators in experimental teaching. It also aims to create intelligent, interactive learning environments to enhance students’ understanding of chemistry.

Key words: Artificial intelligence, Chemical experiment, Code development, Dynamic image