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Evolutionary de novo design of absorbents with optimal CO2 capturing properties


We propose to employ a recently developed de novo design software to develop new absorbents, such as amines, amino acids and ionic liquids, for carbon capture. Our software has been successfully demonstrated to work in catalyst discovery and has the poten tial to boost development of new and more efficient absorbent molecules that are also cheap and easy to synthesize. Our method is based on an evolutionary algorithm (EA), a global optimization method ensuring that absorbents with optimal properties are r eached. New structures are automatically assembled and evaluated by one or several fitness functions, which are here directly related to the observed absorption of CO2 or to theoretically computed properties highly correlated with observations. Central to the method is the development of fitness functions based on highly predictive quantitative structure-property relationship (QSPR) models to make the iterative evolutionary algorithm computationally tractable. The success of the proposed de novo method could be a game-changer for carbon capture as it enables considerable speed-up of the development process and gives cheaper and better absorbent molecules. The economic and environmental impact could be significant.

Project leader: Vishwesh Venkatraman

Started: 2014

Ends: 2019

Category: Universiteter

Sector: UoH-sektor

Budget: 9746000

Institution: Institutt for kjemi

Address: Trondheim