Machine Learning-Boosted Design of Ionic Liquids for CO₂ Absorption and Experimental Verification.

ABSTRACT: Efficient CO₂ capture is indispensable for achieving a carbon-neutral society while maintaining a high quality of life. Since the discovery that ionic liquids (ILs; room-temperature molten salts) can absorb CO₂, various solvents composed of molecular ions have been studied. However, it is challenging to observe the properties of each isolated ion component to control the function of ILs as they are mixtures of ions. Finding the optimal cation-anion combination for the CO₂ absorbent from their enormous chemical space had been impossible in a practical sense. This study applied electronic structure informatics to explore ILs with high CO₂ solubility from 402,114 IL candidates. The feature variables were determined by a set of cheap quantum chemistr

SUBMITTER: Kuroki N 

PROVIDER: S-EPMC10009743 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature