TY - JOUR
T1 - Carbon capture solvents for the applicability of rotating packed bed for industrial applications
T2 - Recent advancements, challenges and future recommendations
AU - Danbatta, Mohammadu Bello
AU - Al-Azri, Nasser Ahmed
AU - Qyyum, Muhammad Abdul
AU - Al-Rawahi, Nabeel
N1 - Publisher Copyright:
© 2025
PY - 2025/6
Y1 - 2025/6
N2 - Solvent selection is a critical aspect for industrial carbon capture, Rotating Packed Bed (RPB) is a promising technology that can be integrated to existing infrastructures, because of its compactness and enhanced mass transfer compare to traditional column beds. However, solvent cost, capture efficiency and energy regeneration is vital for industrial feasibility. Reviewing SCOPUS literature on carbon capture in RPB technology, findings reveal that 83.0 % of studies utilized Carbon dioxide without other pollutants, predominantly using Monoethanolamine as solvent. Across studies, capture efficiencies of 99.0 % reported under varying parameters; Methyldiethanolamine, a tertiary amine, has 99.8 % efficiency and blended amines such as Diethylenetriamine-Piperazine and Methylmonoethanolamine-Piperazine have efficiencies of 99.6 % and 99.4 %, respectively. Identifying the most promising solvents for each industry is crucial. However, there is a significant gap in the selection of optimum solvent for specific industrial application. While amines are commonly used, systematic studies that evaluate a broader range of solvents under diverse operational conditions for specific industrial applications are lacking. The application of Artificial Intelligence (AI) in solvent screening for carbon capture can accelerate adoption and drive commercial utilization. AI solvent screening integration in RPB for industrial use remains underexplored. Addressing these gaps is crucial for identifying solvents that maximize capture efficiency and lower regeneration energy cost. This review presents the current state of solvents in RPB, reflects on challenges, possible scientific developments and future recommendations.
AB - Solvent selection is a critical aspect for industrial carbon capture, Rotating Packed Bed (RPB) is a promising technology that can be integrated to existing infrastructures, because of its compactness and enhanced mass transfer compare to traditional column beds. However, solvent cost, capture efficiency and energy regeneration is vital for industrial feasibility. Reviewing SCOPUS literature on carbon capture in RPB technology, findings reveal that 83.0 % of studies utilized Carbon dioxide without other pollutants, predominantly using Monoethanolamine as solvent. Across studies, capture efficiencies of 99.0 % reported under varying parameters; Methyldiethanolamine, a tertiary amine, has 99.8 % efficiency and blended amines such as Diethylenetriamine-Piperazine and Methylmonoethanolamine-Piperazine have efficiencies of 99.6 % and 99.4 %, respectively. Identifying the most promising solvents for each industry is crucial. However, there is a significant gap in the selection of optimum solvent for specific industrial application. While amines are commonly used, systematic studies that evaluate a broader range of solvents under diverse operational conditions for specific industrial applications are lacking. The application of Artificial Intelligence (AI) in solvent screening for carbon capture can accelerate adoption and drive commercial utilization. AI solvent screening integration in RPB for industrial use remains underexplored. Addressing these gaps is crucial for identifying solvents that maximize capture efficiency and lower regeneration energy cost. This review presents the current state of solvents in RPB, reflects on challenges, possible scientific developments and future recommendations.
KW - Artificial intelligence
KW - Commercial readiness level
KW - Policy recommendations
KW - Solvent efficiency
KW - Solvent selection
KW - Technology readiness level
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U2 - 10.1016/j.ccst.2025.100426
DO - 10.1016/j.ccst.2025.100426
M3 - Article
AN - SCOPUS:105004573069
SN - 2772-6568
VL - 15
JO - Carbon Capture Science and Technology
JF - Carbon Capture Science and Technology
M1 - 100426
ER -