Revolutionizing Catalysis Research: AI-Driven Lab Achieves Breakthrough Speed and Precision

Researchers have unveiled a groundbreaking advancement in catalysis research with the introduction of Fast-Cat, an autonomous lab powered by artificial intelligence (AI) and automated systems. Fast-Cat promises to revolutionize the analysis of catalytic reactions, offering insights at a pace that far surpasses conventional methods.

Published in the journal Nature Chemical Engineering, the research highlights Fast-Cat’s remarkable capability to provide comprehensive analyses of catalytic reactions within a mere five days, a feat that typically requires six months of conventional testing. The focus of Fast-Cat lies in optimizing the yield and selectivity of chemical reactions involving ligands, crucial molecules utilized in various industrial processes.

Dr. Milad Abolhasani, corresponding author of the study and associate professor of chemical and biomolecular engineering at North Carolina State University, underscores the inefficiencies of traditional catalyst discovery methods. He emphasizes that Fast-Cat addresses these challenges by leveraging AI and automation to conduct experiments continuously and independently.

Fast-Cat’s autonomous operation involves running high-temperature, high-pressure gas-liquid reactions while analyzing their outcomes in real-time. By integrating AI, Fast-Cat learns from each experiment it conducts, refining its approach and decision-making process with each iteration.

Users provide Fast-Cat with initial parameters, allowing it to execute a series of experiments to assess how different variables influence reaction outcomes. Through meticulous AI modeling and validation, Fast-Cat ensures scalability and relevance for practical industrial applications.

The efficacy of Fast-Cat has been demonstrated through rigorous proof-of-concept testing, wherein it successfully characterized the catalytic performance of six ligands drawn from existing research literature. Notably, Fast-Cat’s capabilities enable a significant expansion of selectivity and yield endpoints within a remarkably short timeframe.

Industry stakeholders, including Eastman, a global specialty materials company, have lauded the transformative potential of Fast-Cat. Dawn Mason, global external innovation manager at Eastman, underscores the invaluable insights Fast-Cat offers for optimizing catalytic processes in manufacturing.

Jeff Carbeck, vice president of corporate innovation at Eastman, highlights Fast-Cat’s speed, cost-effectiveness, and efficacy in providing essential understanding for industrial applications.

The researchers have made Fast-Cat’s software and hardware publicly available, aiming to facilitate broader adoption across academia and industry. Dr. Abolhasani emphasizes the potential of Fast-Cat to accelerate catalysis discovery and drive innovation in chemical and pharmaceutical industries worldwide.

Co-authors of the paper include Jeffrey Bennett, a postdoctoral researcher at NC State, along with Negin Orouji, Sina Sadeghi, and Muzammil Khan, Ph.D. students and former postdoctoral researchers at NC State, respectively, as well as Jody Rodgers from Eastman.