Chair(s): Leonard Ng Wei Tat (NTU), Beatrice Soh (NUS)
Co-Chair(s): Yang Bai (University of Toronto, Canada)
Symposium Scope/Topics
This symposium will focus on the emerging field of self-driving laboratories: autonomous research platforms that integrate automation and artificial intelligence (AI) to accelerate materials discovery and development. By tightly coupling experiments and theoretical calculations in a closed-loop framework, self-driving labs enable autonomous decision-making and continuous learning via rapid iteration. This dramatically reduces the time and cost associated with traditional materials discovery, across a broad range of materials system from catalysts to inorganics to polymers.
This symposium aims to bring together materials scientists, AI experts and automation specialists to present recent advances and discuss challenges in developing self-driving laboratories. It will provide a forum for showcasing successful case studies and identifying the future directions of autonomous experimentation in materials science.
The following topics are likely to be covered:
- Robotic platforms for high-throughput experimentation
- Integration of AI with automated synthesis and/or characterization workflows
- Development and deployment of digital twins for experimental systems
- Open-source tools and software for self-driving labs
- Ethical and safety considerations in autonomous research
Invited Speakers
To be confirmed
