Current advancements towards the use of nanofluids in the reduction of CO2 emission to the atmosphere

被引:10
作者
Chen, Ying [1 ]
Abed, Azher M. [2 ]
Raheem, Al-Behadili Faisal [3 ]
Altamimi, Abdulmalik S. [4 ]
Yasin, Yaser [5 ]
Sheekhoo, Waheed Abdi [6 ]
Smaisim, Ghassan Fadhil [7 ,8 ]
Ghabra, Amer Ali [9 ]
Naseer, Nesreen Ahmed [10 ]
机构
[1] Chongqing Acad Governance, Chongqing 400039, Peoples R China
[2] Al Mustaqbal Univ Coll, Air Conditioning & Refrigerat Tech Engn Dept, Hillah, Iraq
[3] Univ Ahl Al Bayt, Karbala, Iraq
[4] Prince Sattam Bin Abdulaziz Univ, Coll Pharm, Dept Pharmaceut Chem, POB 173, Alkharj 11942, Saudi Arabia
[5] Al Farahidi Univ, Coll Med Technol, Baghdad, Iraq
[6] AlNoor Univ Coll, Dept Opt Tech, Bartella, Iraq
[7] Univ Kufa, Fac Engn, Dept Mech Engn, Kufa, Iraq
[8] Univ Kufa, Fac Engn, Nanotechnol & Adv Mat Res Unit NAMRU, Kufa, Iraq
[9] Al Amarah Univ Coll, Al Amarah, Iraq
[10] Mazaya Univ Coll, Nasiriyah, Iraq
关键词
Nanofluids; CO2; separation; Greenhouse gases emission; Enhancement mechanisms; CARBON-DIOXIDE CAPTURE; HEAT-TRANSFER; ABSORPTION ENHANCEMENT; MASS-TRANSFER; THERMAL-CONDUCTIVITY; GAS-ABSORPTION; LIQUID ABSORBENTS; SILICA NANOFLUID; MEMBRANE; REMOVAL;
D O I
10.1016/j.molliq.2022.121077
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Development of novel, efficient and cost-effective strategies to diminish the permanent emission of greenhouse gases (GHGs) to the atmosphere has been an indisputable concern for scientists. CO2 is known as the most prominent GHG, which its abnormal amount in the atmosphere accelerates the occurrence of unfavorable environmental events such as acid rain, ocean acidification, global warming, and soil degradation. Nowadays, application of various nanofluids for increasing separation efficiency of CO2 has been an attractive subject due to their certain privileges such as chemical compatibility and great specific area. This paper tries to provide an up-to-date overview of the commonly-employed nanofluids accompanying with their properties and applications to enhance the separation efficiency of CO2. Moreover, important mechanisms toward improving the mass transfer rate and the separation proficiency of CO2 through the nanofluids are comprehensively discussed and summarized. Single material nanofluids (SMNFs) and hybrid nanofluids (HNFs) are considered as major categorizations of commonlyemployed nanofluids in the scientific scope of membrane-based gas separation process (MGSP), which are aimed to be discussed in this paper. True recognition of nanofluids application in the CO2 separation process leads to finding its advantages/disadvantages in comparison with other conventional procedures. (c) 2022 Elsevier B.V. All rights reserved.
引用
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页数:7
相关论文
共 103 条
[1]   Applications of Artificial Intelligence in Transport: An Overview [J].
Abduljabbar, Rusul ;
Dia, Hussein ;
Liyanage, Sohani ;
Bagloee, Saeed Asadi .
SUSTAINABILITY, 2019, 11 (01)
[2]   Application of Nanofluids in CO2 Absorption: A Review [J].
Aghel, Babak ;
Janati, Sara ;
Alobaid, Falah ;
Almoslh, Adel ;
Epple, Bernd .
APPLIED SCIENCES-BASEL, 2022, 12 (06)
[3]   A Review on Nanofluids: Fabrication, Stability, and Thermophysical Properties [J].
Ali, Naser ;
Teixeira, Joao A. ;
Addali, Abdulmajid .
JOURNAL OF NANOMATERIALS, 2018, 2018
[4]   Simulation of Nonporous Polymeric Membranes Using CFD for Bioethanol Purification [J].
Asadollahzadeh, Mehdi ;
Raoufi, Nahid ;
Rezakazemi, Mashallah ;
Shirazian, Saeed .
MACROMOLECULAR THEORY AND SIMULATIONS, 2018, 27 (03)
[5]   Thermal prediction of turbulent forced convection of nanofluid using computational fluid dynamics coupled genetic algorithm with fuzzy interface system [J].
Babanezhad, Meisam ;
Behroyan, Iman ;
Nakhjiri, Ali Taghvaie ;
Rezakazemi, Mashallah ;
Marjani, Azam ;
Shirazian, Saeed .
SCIENTIFIC REPORTS, 2021, 11 (01)
[6]   Computational Modeling of Transport in Porous Media Using an Adaptive Network-Based Fuzzy Inference System [J].
Babanezhad, Meisam ;
Behroyan, Iman ;
Nakhjiri, Ali Taghvaie ;
Marjani, Azam ;
Shirazian, Saeed .
ACS OMEGA, 2020, 5 (48) :30826-30835
[7]  
Babanezhad M, 2020, SCI REP-UK, V10, DOI [10.1038/s41598-020-74858-4, 10.1038/s41598-020-78277-3, 10.1038/s41598-020-78388-x]
[8]   Influence of number of membership functions on prediction of membrane systems using adaptive network based fuzzy inference system (ANFIS) [J].
Babanezhad, Meisam ;
Masoumian, Armin ;
Nakhjiri, Ali Taghvaie ;
Marjani, Azam ;
Shirazian, Saeed .
SCIENTIFIC REPORTS, 2020, 10 (01)
[9]   Pattern recognition of the fluid flow in a 3D domain by combination of Lattice Boltzmann and ANFIS methods [J].
Babanezhad, Meisam ;
Nakhjiri, Ali Taghvaie ;
Marjani, Azam ;
Shirazian, Saeed .
SCIENTIFIC REPORTS, 2020, 10 (01)
[10]   Developing Intelligent Algorithm as a Machine Learning Overview over the Big Data Generated by Euler-Euler Method To Simulate Bubble Column Reactor Hydrodynamics [J].
Babanezhad, Meisam ;
Nakhjiri, Ali Taghvaie ;
Rezakazemi, Mashallah ;
Shirazian, Saeed .
ACS OMEGA, 2020, 5 (32) :20558-20566