Research Shows That Machine Learning Fights Global Warming

Amir Barati Farimani, an assistant mechanical engineering professor at Carnegie Mellon University, has been attempting to find efficient ways to absorb and store carbon dioxide. He has made progress in the identification of ionic liquid molecules using machine learning, which are classes of molten salt that remain in a liquid state at normal temperature and have high CO2 solubility. Barati Farimani has created graph neural networks and fingerprint-based machine learning models that can forecast the CO2 absorption in ionic liquids for the first time, with superior accuracy.