Automation
Automation
Automation in chemistry accelerates discovery by enabling high-throughput experimentation, precise reaction control, and real-time data analysis. Robotic systems, AI-driven optimization, and automated synthesis platforms enhance reproducibility and efficiency, reducing the time and resources needed for innovation. These advancements are transforming fields from drug discovery to materials science by streamlining complex workflows and enabling new levels of chemical insight. The StealtHub serves as the research and teaching hub for users interesting in designing chemical reactions and other experiments with automation using SMART principles.
SMART experiments ae designed from multiple perspectives:
- Society (from need of the scientific discipline to the world at large)
- Machines (from high throughput lab equipment to self-driving labs)
- Analysis (from mass spectrometry to machine learning methods)
- Reproducibility (following FAIR principles of findable, accessible, interoperable, and reusable data and protocols) and
- Trust.
In other words, every experiment should be designed starting with society and ending with trust!
Members of the IU campus interested in lab automation should contact the director or co-director to join this community.
Directors
Prof. Nicola PohlDirector
Prof. Eric BlochDirector