Computer-aided design of organic amine solvents for carbon capture based on reaction kinetics
XIANG Sheng, LIU Qilei, ZHANG Lei, DU Jian
Frontiers Science Center for Smart Materials Oriented Chemical Engineering, Institute of Chemical Process Systems Engineering, School of Chemical Engineering, Dalian University of Technology, Dalian 116024, China
Abstract：[Objective] In recent years, increasing emissions of greenhouse gases from industrial sources have led to extreme weather events. Thus, carbon capture has become an increasingly prominent concern for human society. Organic amines have emerged as popular carbon dioxide (CO2) chemical absorbents. However, currently used organic amine solvents encounter challenges, such as poor reaction kinetics of chemical absorptions, which need to be overcome using organic amines with higher performance. Moreover, there is limited research on the crucial property of Gibbs free energy of activation related to the reaction kinetics of chemical absorptions. The difficulty lies in the fact that the calculation of this property often involves the search for transition states in elementary reactions, and the initial structure of the transition state generally needs to be manually arranged, which greatly hampers the success of this search. To overcome this difficulty, a method for generating transition state initial guess structures is employed herein to automatically generate transition state structures for target organic amine molecules. Based on this generation method of transition state initial guess structures, a computer-aided framework for designing organic amine solvents is proposed by integrating a reaction kinetic model and a mathematical programming method. [Methods] First, the mechanism of the reaction between organic amines and CO2 is investigated based on quantum chemical methods and the transition state theory to construct a reaction kinetic model that can regulate the Gibbs free energy of activation of amine-based CO2 chemical absorptions. Additionally, a conformational isomer search approach is incorporated into the reaction kinetic model to improve the computational accuracy of the transition state energies. Second, by employing the transition state initial guess structure generation method, the reaction kinetic model is successfully integrated with the mathematical programming method to achieve automatic, reverse, and optimal design of organic amine molecular structures that have the lowest Gibbs free energy of activation for carbon capture reactions and satisfy all other property constraints being studied. Finally, the interaction region indicator function is used to verify the rationality of the designed organic amines regarding the reaction kinetics. [Results] Using the mathematical programming method, 45 SMILES (simplified molecular input line entry system) representations that satisfy the design constraints were obtained. Through the transition state initial guess structure generation method, the corresponding transition state structures of organic amine molecules were obtained, and the Gibbs free energies of activation of these molecules were calculated by the reaction kinetic model. The final design results showed that the organic amine with the best performance had faster reaction kinetics than the primary amine used commonly in the industry, namely MEA (monoethanolamine), and its Gibbs free energy of activation for CO2 chemical absorption was 10.7% less than that of MEA. [Conclusions] In summary, the integration of the reaction kinetic model and the conformational isomer search approach yields molecular conformations with lower energies that are more realistic, resulting in more accurate calculations of Gibbs free energy of activation. The transition state initial guess structure generation method can automatically and rapidly generate initial molecular structures for transition states to calculate Gibbs free energy of activation, significantly improving the success rate of transition state searches. From the final design results, it is clear that the method proposed herein can discover promising monoamine molecules within a large chemical space.
向晟, 刘奇磊, 张磊, 都健. 基于反应动力学的计算机辅助碳捕集有机胺溶剂设计[J]. 清华大学学报（自然科学版）, 2024, 64(3): 520-527.
XIANG Sheng, LIU Qilei, ZHANG Lei, DU Jian. Computer-aided design of organic amine solvents for carbon capture based on reaction kinetics. Journal of Tsinghua University(Science and Technology), 2024, 64(3): 520-527.
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2024, Vol. 64 
