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Article Dans Une Revue Communications Chemistry Année : 2022

Computational screening methodology identifies effective solvents for CO2 capture

Alexey Orlov
Alain Valtz
  • Fonction : Auteur
Xavier Rozanska
  • Fonction : Auteur
Erich Wimmer
  • Fonction : Auteur
Gilles Marcou
Dragos Horvath
Bénédicte Poulain
  • Fonction : Auteur
Alexandre Varnek
Frédérick de Meyer
Daryna Demenko
  • Fonction : Auteur
Charles Bignaud
  • Fonction : Auteur

Résumé

Abstract Carbon capture and storage technologies are projected to increasingly contribute to cleaner energy transitions by significantly reducing CO 2 emissions from fossil fuel-driven power and industrial plants. The industry standard technology for CO 2 capture is chemical absorption with aqueous alkanolamines, which are often being mixed with an activator, piperazine, to increase the overall CO 2 absorption rate. Inefficiency of the process due to the parasitic energy required for thermal regeneration of the solvent drives the search for new tertiary amines with better kinetics. Improving the efficiency of experimental screening using computational tools is challenging due to the complex nature of chemical absorption. We have developed a novel computational approach that combines kinetic experiments, molecular simulations and machine learning for the in silico screening of hundreds of prospective candidates and identify a class of tertiary amines that absorbs CO 2 faster than a typical commercial solvent when mixed with piperazine, which was confirmed experimentally.

Dates et versions

hal-03613428 , version 1 (18-03-2022)

Identifiants

Citer

Christophe Coquelet, Alexey Orlov, Alain Valtz, Xavier Rozanska, Erich Wimmer, et al.. Computational screening methodology identifies effective solvents for CO2 capture. Communications Chemistry, 2022, 5 (1), pp.37. ⟨10.1038/s42004-022-00654-y⟩. ⟨hal-03613428⟩
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