NYU Researchers Pioneer Machine Learning to Speed Chemical Discoveries, Reduce Waste
BROOKLYN, New York, Thursday, December 13, 2018 – Machine learning algorithms can predict stock market fluctuations, control complex manufacturing processes, enable navigation for robots and driverless vehicles, and much more.
Now, researchers at the NYU Tandon School of Engineering are tapping a new set of capabilities in this field of artificial intelligence, combining artificial neural networks with infrared thermal imaging to control and interpret chemical reactions with precision and speed that far outpace conventional methods. More innovative still is the fact that this technique was developed and tested on novel microreactors that allow chemical discoveries to take place quickly and with far less environmental waste than standard large-scale reactions.
“This system can reduce the decision-making process about certain chemical manufacturing processes from one year to a matter of weeks, saving tons of chemical waste and energy in the process,” said Ryan Hartman, an assistant professor of chemical and biomolecular engineering at NYU Tandon and lead author of a paper detailing the method in the journal Computers & Chemical Engineering.