Automated Chemistry

To be defined

Science is the rational approach for addressing the unknown. In contrast, process automation requires well-defined systems and boundary conditions.

But can we automate processes where the outcomes are not yet determined?

While automated platforms are increasingly used for lab operations such as reactions, separations, and analytics, most experiments—especially in chemical laboratories—are still performed manually. Despite the exciting promise of self-driving laboratories, automated experimentation remains economically prohibitive, technically complex, and lacks standardized approaches for data handling.

Our goal is to strike a balance between the flexibility essential for scientific discovery and the reliability offered by standardized automated processes. By approaching machine-driven research from physical, chemical, and engineering perspectives, we aim to design a platform that democratizes access to automated experimentation.

Our interests focus on:

• Theoretical modeling and process parameterization
• Designing and optimizing automated experimental platforms (for reaction studies, molecular assembly, and measurement of physicochemical properties)
• Translating reaction kinetics and thermodynamics into workflows for complex molecule synthesis