Predicting the solubility of CO2 and N2 in ionic liquids based on COSMO-RS and machine learning.

IF 3.8 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY Frontiers in Chemistry Pub Date : 2024-10-31 eCollection Date: 2024-01-01 DOI:10.3389/fchem.2024.1480468
Hongling Qin, Ke Wang, Xifei Ma, Fangfang Li, Yanrong Liu, Xiaoyan Ji
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Abstract

As ionic liquids (ILs) continue to be prepared, there is a growing need to develop theoretical methods for predicting the properties of ILs, such as gas solubility. In this work, different strategies were employed to obtain the solubility of CO2 and N2, where a conductor-like screening model for real solvents (COSMO-RS) was used as the basis. First, experimental data on the solubility of CO2 and N2 in ILs were collected. Then, the solubility of CO2 and N2 in ILs was predicted using COSMO-RS based on the structures of cations, anions, and gases. To further improve the performance of COSMO-RS, two options were used, i.e., the polynomial expression to correct the COSMO-RS results and the combination of COSMO-RS and machine learning algorithms (eXtreme Gradient Boosting, XGBoost) to develop a hybrid model. The results show that the COSMO-RS with correction can significantly improve the prediction of CO2 solubility, and the corresponding average absolute relative deviation (AARD) is decreased from 43.4% to 11.9%. In contrast, such an option cannot improve that of the N2 dataset. Instead, the results obtained from coupling machine learning algorithms with the COSMO-RS model agree well with the experimental results, with an AARD of 0.94% for the solubility of CO2 and an average absolute deviation (AAD) of 0.15% for the solubility of N2.

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基于 COSMO-RS 和机器学习预测二氧化碳和 N2 在离子液体中的溶解度。
随着离子液体(ILs)的不断制备,人们越来越需要开发预测离子液体特性(如气体溶解度)的理论方法。在这项工作中,采用了不同的策略来获得 CO2 和 N2 的溶解度,并以实际溶剂的导体类筛选模型(COSMO-RS)为基础。首先,收集了二氧化碳和二氧化氮在惰性气体中溶解度的实验数据。然后,根据阳离子、阴离子和气体的结构,使用 COSMO-RS 预测二氧化碳和 N2 在 IL 中的溶解度。为了进一步提高 COSMO-RS 的性能,采用了两种方案,即用多项式表达式修正 COSMO-RS 的结果,以及将 COSMO-RS 与机器学习算法(eXtreme Gradient Boosting, XGBoost)相结合建立混合模型。结果表明,修正后的 COSMO-RS 可以显著改善二氧化碳溶解度的预测,相应的平均绝对相对偏差(AARD)从 43.4% 降至 11.9%。相比之下,这一方案无法改善 N2 数据集的预测结果。相反,将机器学习算法与 COSMO-RS 模型相结合所得到的结果与实验结果非常吻合,二氧化碳溶解度的平均绝对相对偏差(AARD)为 0.94%,而 N2 溶解度的平均绝对偏差(AAD)为 0.15%。
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来源期刊
Frontiers in Chemistry
Frontiers in Chemistry Chemistry-General Chemistry
CiteScore
8.50
自引率
3.60%
发文量
1540
审稿时长
12 weeks
期刊介绍: Frontiers in Chemistry is a high visiblity and quality journal, publishing rigorously peer-reviewed research across the chemical sciences. Field Chief Editor Steve Suib at the University of Connecticut is supported by an outstanding Editorial Board of international researchers. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to academics, industry leaders and the public worldwide. Chemistry is a branch of science that is linked to all other main fields of research. The omnipresence of Chemistry is apparent in our everyday lives from the electronic devices that we all use to communicate, to foods we eat, to our health and well-being, to the different forms of energy that we use. While there are many subtopics and specialties of Chemistry, the fundamental link in all these areas is how atoms, ions, and molecules come together and come apart in what some have come to call the “dance of life”. All specialty sections of Frontiers in Chemistry are open-access with the goal of publishing outstanding research publications, review articles, commentaries, and ideas about various aspects of Chemistry. The past forms of publication often have specific subdisciplines, most commonly of analytical, inorganic, organic and physical chemistries, but these days those lines and boxes are quite blurry and the silos of those disciplines appear to be eroding. Chemistry is important to both fundamental and applied areas of research and manufacturing, and indeed the outlines of academic versus industrial research are also often artificial. Collaborative research across all specialty areas of Chemistry is highly encouraged and supported as we move forward. These are exciting times and the field of Chemistry is an important and significant contributor to our collective knowledge.
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