Machine-learning model enhances CO2 capture efficiency

Scientists at Lawrence Livermore National Laboratory have developed a machine-learning model to enhance CO2 capture using amine-based sorbents. This model reveals that CO2 capture involves forming carbon-nitrogen bonds and complex proton transfer reactions. The research aims to improve direct air capture technologies, which are vital for addressing atmospheric CO2 levels. The findings were published in the journal Chemical Science.