About this video
High-throughput experimentation (HTE) is a powerful tool in chemistry, allowing exploration of a wide range of reaction conditions, substrates, and other variables and generating datasets of use in applying machine learning methods to chemical prediction. But HTE can sometimes be viewed as inaccessible to the academic chemist, while also presenting unique challenges in data analysis and management. In this panel, Tim Cernak, Dani Schultz, Jacob Janey, and Matthew Gaunt will discuss the myths surrounding HTE (7:52), the challenges and benefits of employing it in academia and industry (22:32), how to get started with HTE (36:36), and the future of the field (44:33).