Multiple machine learning models for prediction of CO2 solubility in potassium and sodium based amino acid salt solutions

• 主要な著者: Guanwei Yin, Fouad Jameel Ibrahim Alazzawi, Dmitry Bokov, Haydar Abdulameer Marhoon, A.S. El-Shafay, Md Lutfor Rahman, Su, Chia-Hung, Lu, Yi-Ze, Hoang, Chinh Nguyen
• フォーマット: 論文
• 言語: English; English
• 出版事項: Elsevier Science 2021
• 主題: Q1-390 Science (General); QD1-999 Chemistry
• オンライン･アクセス: https://eprints.ums.edu.my/id/eprint/32941/1/Multiple%20machine%20learning%20models%20for%20prediction%20of%20CO2%20solubility%20in%20potassium%20and%20sodium%20based%20amino%20acid%20salt%20solutions.pdf; https://eprints.ums.edu.my/id/eprint/32941/2/Multiple%20machine%20learning%20models%20for%20prediction%20of%20CO2%20solubility%20in%20potassium%20and%20sodium%20based%20amino%20acid%20salt%20solutions1.pdf; https://eprints.ums.edu.my/id/eprint/32941/; https://www.sciencedirect.com/science/article/pii/S1878535221006237; https://doi.org/10.1016/j.arabjc.2021.103608

In this work, we developed artificial intelligence-based models for prediction and correlation of CO2 solubility in amino acid solutions for the purpose of CO2 capture. The models were used to correlate the process parameters to the CO2 loading in the solvent. Indeed, CO2 loading/-solubility in the...