Probing carbon capture, atom-by-atom with machine-learning model

A team of scientists at Lawrence Livermore National Laboratory (LLNL) has developed a machine-learning model to gain an atomic-level understanding of CO2 capture in amine-based sorbents. This innovative approach promises to enhance the efficiency of direct air capture (DAC) technologies, which are crucial for reducing the excessive amounts of CO2 already present in the atmosphere.