机器学习辅助固体胺CO2吸附剂的设计与优化,ACS Sustainable Chemistry & Engineering

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机器学习辅助固体胺CO2吸附剂的设计与优化
ACS Sustainable Chemistry & Engineering ( IF 7.1 ) Pub Date : 2022-09-22 , DOI: 10.1021/acssuschemeng.2c04492
Shichao Zhang _{1,

2} , Hang Dong ₃ , An Lin ₃ , Chaofeng Zhang _{2,

4} , Hong Du ₂ , Junju Mu ₂ , Jianyu Han ₂ , Jian Zhang ₂ , Feng Wang ₂

Affiliation

在固体胺类CO ₂吸附剂的开发中，具有各种新型多孔载体或胺结构改性的胺功能化吸附剂对CO _{2的吸附性能得到了广泛的研究。}然而，缺乏系统研究限制了胺官能化CO ₂吸附剂的工业应用，特别是由廉价且容易获得的商业多孔载体制备的吸附剂。在这项工作中，机器学习（ML）被用来探索胺功能化吸附剂的CO ₂吸附性能如何与五个因素相关：胺负载、胺类型、孔体积、孔径和比表面积。我们发现胺负载对 CO 的影响最大₂吸附量，其次是孔容。孔径是影响胺效率的最重要因素，而吸附剂的循环稳定性基本上与胺的类型有关，并通过ML探讨了影响因素之间的相互作用。此外，通过ML预测TEPA/KXY和PEI/KYX吸附剂的CO ₂吸附能力，ML预测结果与我们的实验结果一致。此外，我们通过雷达图构建了45TEPA/KYX和60PEI/KYX吸附剂对CO _{2吸附性能的“五合一”综合比较，认为45TEPA/KYX吸附剂对CO}_{2的综合吸附性能更好。}吸附性能。_{我们的研究为使用商业多孔载体开发和优化固体胺 CO 2}吸附剂提供了见解。

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Design and Optimization of Solid Amine CO2 Adsorbents Assisted by Machine Learning

In the development of solid amine CO₂ adsorbents, the CO₂ adsorption performance of amine-functionalized adsorbents, with various novel porous supports or modification of the amine structure, has been widely studied. However, a lack of systematic research limits the industrial application of amine-functionalized CO₂ adsorbents, especially the adsorbents prepared from inexpensive and readily available commercial porous supports. In this work, machine learning (ML) was employed to explore how the CO₂ adsorption performance of amine-functionalized adsorbents is correlated with five factors: amine loading, amine type, pore volume, pore size, and specific surface area. We found that amine loading contributed the most to the effect of CO₂ adsorption capacity, followed by pore volume. Pore size was the most important factor affecting amine efficiency, while the cycle stability of the adsorbent was basically related to the amine type, and the interaction effect between the influencing factors was explored by ML. In addition, the CO₂ adsorption capacities of TEPA/KXY and PEI/KYX adsorbents were predicted by ML, and the results of ML prediction were consistent with our experimental results. Furthermore, we constructed a “five-in-one” comprehensive comparison of the CO₂ adsorption performance of 45TEPA/KYX and 60PEI/KYX adsorbents through a radar diagram, and it was considered that the 45TEPA/KYX adsorbent had a better comprehensive CO₂ adsorption performance. Our study provides insights into the development and optimization of solid amine CO₂ adsorbents using commercial porous supports.

更新日期：2022-09-22

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