Xiangxuan Zeng ¹ and Ang Li ², ¹ USA, ² California State Polytechnic University, USA

ChemSynth is an interactive chemistry education platform designed to enhance student engagement and conceptual understanding through hands-on digital exploration. Built using Unity and C#, the game allows users to collect subatomic particles' protons, neutrons, and electrons' and synthesize atoms and molecules in a 3D environment. Unlike traditional learning tools or static periodic tables, ChemSynth enables players to actively construct matter from the nucleus outward, reinforcing foundational chemical principles. The platform also features an integrated AI system for validating atomic combinations and providing real-time feedback. Through experiments, we evaluate the system's accuracy in detecting valid atomic structures and the effectiveness of its periodic table interface in improving student recall. Compared to prior approaches such as quiz-based learning or augmented reality visualization, ChemSynth offers a more immersive and constructive learning experience. The results demonstrate the platform's potential to bridge the gap between abstract theory and practical understanding in early science education.

Machine Learning, Computer Vision, Chemistry, Compoun