Development of hybrid machine learning model for simulation of chemical reactors in water treatment applications: Absorption in amino acid

• Main Authors: Yanjie Zhang, Lakshmi Thangavelu, Talib Zeedan Taban, Walid Kamal Abdelbasset, Wanich Suksatan, Mohd Sani Sarjadi, Md Lutfor Rahman, Shaheen M. Sarkar, May Alashwal, Mohammed Zwawi, Mohammed Algarni
• Format: Article
• Language: English; English
• Published: Elsevier B.V. 2022
• Subjects: GE1-350 Environmental sciences; Q1-390 Science (General)
• Online Access: https://eprints.ums.edu.my/id/eprint/32659/1/Development%20of%20hybrid%20machine%20learning%20model%20for%20simulation%20of%20chemical%20reactors%20in%20water%20treatment%20applications.pdf; https://eprints.ums.edu.my/id/eprint/32659/2/Development%20of%20hybrid%20machine%20learning%20model%20for%20simulation%20of%20chemical%20reactors%20in%20water%20treatment%20applications1.pdf; https://eprints.ums.edu.my/id/eprint/32659/; https://www.sciencedirect.com/science/article/pii/S2352186422000761; https://doi.org/10.1016/j.eti.2022.102417
• Institution: Universiti Malaysia Sabah

Separation and capture of CO2 from gas mixtures is of great importance from environmental point of view which can be effectively achieved using amino acids as new class of chemical absorbents. However, screening the proper absorbent with desired separation properties using experimental measurements...