Bridging decision-making engines and workflow design in self-driving laboratories: A NIMO–IvoryOS integration study

Self-driving laboratories (SDLs) have the potential to accelerate scientific discovery, but their development often requires substantial programming effort. To lower this barrier, we present an integrated orchestration framework that combines NIMO and IvoryOS. In this framework, NIMO provides decision-making algorithms for autonomous experimentation, while IvoryOS offers an intuitive web interface automatically generated from Python code. We demonstrate the utility of this integration through an automated study of the coffee ring effect. The proposed framework offers a practical pathway toward more accessible SDLs.