Recent progress on advanced solid adsorbents for CO2 capture: From mechanism to machine learning

被引:10
作者
Khosrowshahi, Mobin Safarzadeh [1 ]
Aghajari, Amirhossein Afshari [2 ]
Rahimi, Mohammad [3 ]
Maleki, Farid [4 ]
Ghiyabi, Elahe [5 ]
Rezanezhad, Armin [6 ]
Bakhshi, Ali [1 ]
Salari, Ehsan [7 ]
Shayesteh, Hadi [8 ]
Mohammadi, Hadi [9 ]
机构
[1] Iran Univ Sci & Technol IUST, Sch Adv Technol, Nanotechnol Dept, Tehran 16846, Iran
[2] Texas A&M Univ, Zachry Dept Civil & Environm Engn, Dwight Look Engn Bldg, College Stn, TX 77840 USA
[3] McMaster Univ, Dept Mech Engn, Hamilton, ON, Canada
[4] Amirkabir Univ Technol, Dept Polymer Engn & Color Technol, 424 Hafez St, Tehran, Iran
[5] Univ Tabriz, Fac Elect & Comp Engn, Dept Biomed Engn, Tabriz, Iran
[6] Univ Tabriz, Fac Mech Engn, Dept Mat Engn, Tabriz 5166616471, Iran
[7] Sahand Univ Technol, Inst Polymer Mat, POB 51335-1996, Sahand New Town, Tabriz, Iran
[8] Iran Univ Sci & Technol IUST, Fac Chem Engn, Tehran 16846, Iran
[9] Univ Tehran, Coll Engn, Sch Civil Engn, Tehran, Iran
关键词
CO; 2; capture; Adsorption; Solid adsorbents; Machine learning; Physisorption; Porous materials; METAL-ORGANIC FRAMEWORKS; WALLED CARBON NANOTUBES; ENRICHED POROUS CARBONS; HIGH-SURFACE-AREA; ACTIVATED CARBON; BORON-NITRIDE; ADSORPTION MECHANISM; DIOXIDE CAPTURE; WATER-VAPOR; NITROGEN;
D O I
10.1016/j.mtsust.2024.100900
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Environmental pollution has become a serious issue due to the rapid development of urbanization, industrialization, and vehicle traffic. Notably, fossil fuel combustion significantly contributes to rising atmospheric CO2 levels. To address this problem, various carbon capture and storage (CCS) technologies have been developed, aiming to reduce CO2 emissions and mitigate their impact on climate change. Absorption using aqueous amines has long been recognized as a method for removing diluted CO2 from gas streams, but it comes with drawbacks such as high energy intensity and corrosion issues. The use of solid adsorbents, however, is now being seriously considered as a potential alternative, offering a possibly less energy-intensive separation method. The primary focus of this study is to outline the recent development of advanced solid adsorbents, including zeolites, carbonbased materials, MOFs, COFs, boron nitride, magnetic nanoparticles, and mesoporous silica, along with their CO2 uptake behavior. In CO2 capture procedures, selecting the appropriate adsorbent is crucial, yet it's not a straightforward task to determine the most promising sorbent beforehand due to various factors affecting performance and economy. In recent years, machine learning (ML) algorithms, particularly artificial neural networks (ANN) and convolutional neural networks (CNN) have emerged as valuable tools for predicting physical properties, expediting the selection of optimal adsorbents for CO2 capture, optimizing synthesis conditions of adsorbents, and understanding advantageous variables for gas-solid interaction. The secondary objective of this review is to establish a correlation between recent advancements and potential future breakthroughs in the domain of machine learning-assisted CO2 adsorbents. In summary, this review aims to provide a comprehensive guideline for selecting tailored solid adsorbent materials according to recently reported research to achieve highperformance CO2 capture. By exploring various materials, their properties, and the mechanisms that influence their effectiveness, this review intends to facilitate informed decisions and innovative solutions for CO2 adsorbents.
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页数:34
相关论文
共 322 条
  • [1] Transformation of a copper-based metal-organic polyhedron into a mixed linker MOF for CO2 capture
    Abbas, Muhammad
    Maceda, Amanda M.
    Xiao, Zhifeng
    Zhou, Hong-Cai
    Balkus, Kenneth J.
    [J]. DALTON TRANSACTIONS, 2023, 52 (14) : 4415 - 4422
  • [2] Modeling of CO2 adsorption capacity by porous metal organic frameworks using advanced decision tree-based models
    Abdi, Jafar
    Hadavimoghaddam, Fahimeh
    Hadipoor, Masoud
    Hemmati-Sarapardeh, Abdolhossein
    [J]. SCIENTIFIC REPORTS, 2021, 11 (01)
  • [3] Simulating and Comparing CO2/CH4 Separation Performance of Membrane-Zeolite Contactors by Cascade Neural Networks
    Abdollahi, Seyyed Amirreza
    Andarkhor, AmirReza
    Pourahmad, Afham
    Alibak, Ali Hosin
    Alobaid, Falah
    Aghel, Babak
    [J]. MEMBRANES, 2023, 13 (05)
  • [4] Activated carbons from biomass-based sources for CO2 capture applications
    Abuelnoor, Nada
    AlHajaj, Ahmed
    Khaleel, Maryam
    Vega, Lourdes F.
    Abu-Zahra, Mohammad R. M.
    [J]. CHEMOSPHERE, 2021, 282
  • [5] Coal and biomass combustion with CO2 capture by CLOU process using a magnetic Fe-Mn-supported CuO oxygen carrier
    Adanez-Rubio, Inaki
    Sampron, Ivan
    Izquierdo, Maria Teresa
    Abad, Alberto
    Gayan, Pilar
    Adanez, Juan
    [J]. FUEL, 2022, 314
  • [6] A systematic review on CO2 capture with ionic liquids: Current status and future prospects
    Aghaie, Mahsa
    Rezaei, Nima
    Zendehboudi, Sohrab
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2018, 96 : 502 - 525
  • [7] Synthesis of mesoporous magnesium silicate from coal gangue for efficient CO2 adsorption at room temperature
    Ai, Jiajia
    Li, Fu
    Wu, Yu
    Yin, Yukun
    Wu, Zhaojun
    Zhang, Jianbin
    [J]. FUEL, 2023, 341
  • [8] Aimikhe V.J., 2022, Biomass Conversion and Biorefinery, P1
  • [9] Design of Nanostraws in Amine-Functionalized MCM-41 for Improved Adsorption Capacity in Carbon Capture
    Ajumobi, Oluwole
    Wang, Borui
    Farinmade, Azeem
    He, Jibao
    Valla, Julia A.
    John, Vijay T.
    [J]. ENERGY & FUELS, 2023, 37 (16) : 12079 - 12088
  • [10] Accelerating discovery of COFs for CO2 capture and H2 purification using structurally guided computational screening
    Aksu, Gokhan Onder
    Erucar, Ilknur
    Haslak, Zeynep Pinar
    Keskin, Seda
    [J]. CHEMICAL ENGINEERING JOURNAL, 2022, 427