Presentation
Accelerated Materials and Molecular Discovery with Self-Driving Fluidic Labs
Presenter
DescriptionAccelerating the discovery of new molecules and materials, as well as green and sustainable ways to synthesize and manufacture them, will profoundly impact the worldwide challenges in energy, sustainability, and healthcare. The current human-dependent paradigm of experimental research in chemical and materials sciences fails to identify technological solutions quickly. Recent advances in reaction miniaturization, automated experimentation, and data science provide an exciting opportunity to reshape the discovery and development of new molecules and materials related to energy transition and sustainability. In this talk, I will present a 'self-driving fluidic lab (SDFL)' for autonomous discovery and development of emerging advanced functional materials and molecules through integrating flow chemistry, online characterization, and machine learning (ML). I will discuss how modularization of different chemical synthesis and processing stages in tandem with constantly evolving ML modeling and decision-making under uncertainty can enable resource-efficient navigation through high dimensional experimental design spaces (>1020 possible experimental conditions). Example applications of the SDFL for the autonomous synthesis of quantum dots and specialty chemicals will be presented to illustrate the potential of autonomous robotic experimentation in reducing synthetic route discovery timeframe from >10 years to a few months.
TimeMonday, June 314:30 - 15:00 CEST
LocationHG E 1.1
Event Type
Minisymposium
Chemistry and Materials
Climate, Weather, and Earth Sciences
Engineering
Life Sciences
Physics
Computational Methods and Applied Mathematics