The absorption/desorption performance of carbon dioxide (CO2) in aqueous 5 M monoethanolamine (MEA) solutions in the presence of various solution regeneration promoters was comprehensively investigated using a multiple rapid screening method. The promoters considered were N-methyldiethanolamine (MDEA), N,N-dimethylethanolamine (DMEA), N,N-diethylethanolamine (DEEA), 1-dimethylamino-2-propanol (1DMA2P), 1-diethylamino-2-propanol (1DEA2P), 3-dimethylamino-1-propanol (3DMA1P), 2-(dimethylamino)-2-methyl-1-propanol (2DMA2M1P), triethanolamine (TEA), 3-(dimethylamino)-1,2-propanediol (3DMA-1,2-PD), and 3-(diethylamino)-1,2-propanediol (3DEA-1,2-PD). The molar concentration of these promoters added into 5 M MEA was set to 1 mol/L. At the atmospheric pressure, the absorption and stripping experiments were carried out at 313.15 and 353.15 K, respectively. Especially, the CO2 partial pressure was controlled at constant 15 kPa for absorption experiments. In addition, the equilibrium solubility of CO2 was also determined in order to evaluate the driving force of each amine system. The results showed that the highest CO2 equilibrium solubility of 0.5548 mol CO2/mol amine was obtained by MEA/1DEA2P, whereas both the fastest absorption and regeneration rates were achieved for aqueous blended MEA/1DMA2P solution which made MEA/1DMA2P to exhibit the highest CO2 cyclic capacity of 1.6710 mol CO2/L.
Abstract In this work, the radial basis function neural network (RBFNN) and random forest (RF) algorithms were employed to develop generic AI models predicting mass transfer coefficient in amine‐based CO 2 absorber. The models with operating parameters as input gave quite different prediction performance in different CO 2 absorption systems. To secure better applicability, extra parameters related to amine type and packing characteristics were introduced to reasonably describe mass transfer behaviors, respectively. Moreover, the generic models were proposed by considering all influencing factors of mass transfer in CO 2 absorber column. Furthermore, the performance of BPNN, RBFNN, and RF models was completely compared and fully discussed in terms of AARE. All three generic models could predict mass transfer coefficient of CO 2 absorber very well. It was found that the BPNN models provide the best predication with AAREs of below 5%. The developed generic model could serve as a fast and efficient tool for preliminary selection and evaluation of potential amines for CO 2 absorption. The framework of generic ML model development was also clearly presented, which could provide theoretical basis and practical guidance for the implementation and application of ML models in the carbon capture field.
In this work, the tertiary amine, 1DMA2P, was employed to study the concentrations of 1DMA2P, 1DMA2PH+, HCO3-, CO32 when it is loaded with different CO2 loadings as determined using the 13C NMR technique at 1 M concentration of 1DMA2P, temperature of 301K, and CO2 loading in the range of 0-0.83 mol CO2/mol amine. The ion speciation (1DMA2P, 1DMA2PH+, HCO3-, CO32−) plots of 1DMA2P-H2O-CO2 system were developed in the study.
In this work, the reaction kinetics of carbon dioxide (CO2) with diethylenetriamine (DETA) and 1-amino-2-propanol (1-AP) in methanol and ethanol systems were measured using the stopped flow technique over a temperature range of 293–313 K in terms of pseudo-first-order rate constant (k0). Concentration in the range of 10 to 50 mol/m3 for diethylenetriamine, and 20 to 100 mol/m3 for 1-amino-2-propanol were studied. The experimental data show that the pseudo-first-order rate constants (k0) increase with the increase of both amine concentration and temperature. The zwitterion mechanism and the termolecular mechanism were used to represent the data for DETA in methanol and ethanol systems with excellent ADDs of 3.5% and 2.4%, respectively, and 1-AP in methanol and ethanol systems with excellent ADDs of 2.4% and 2.6%, respectively. In comparison with EDA and AEEA in terms of k2, DETA exhibits a better reaction kinetics performance for capturing CO2. Those results will be useful in finding an efficient method for the removal of CO2 from industrial gases.
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