Densities, viscosities, and diffusivities of loaded and unloaded aqueous CO2/H2S/MDEA mixtures: A molecular dynamics simulation study

Diffusivity of CO2 in H2O: A Review of Experimental Studies and Molecular Simulations in the Bulk and in Confinement

“…This study further revealed that the temperature dependence of the self-diffusivities in 10 wt % aqueous MEA solutions are higher than that in 50 wt % solutions. Similar observations were made by Yiannourakou et al for CO 2 in 30 wt % aqueous N -methyldiethanolamine (MDEA) solutions, demonstrating an increase in self-diffusivities from 2.50 × 10 –9 m 2 s –1 at 300 K to 1.03 × 10 –8 m 2 s –1 at 400 K. Polat et al expanded the exploration to unloaded and loaded aqueous MDEA mixtures, showing that CO 2 diffusion is 3.5 times faster in 10 wt % than in 50 wt % aqueous MDEA solutions within a temperature range of 288–333 K. Polat et al attributed the slower diffusion of CO 2 in concentrated MDEA solutions to stronger interactions between CO 2 and surrounding molecules (both water and MDEA). Additionally, investigations into the self-diffusivities of CO 2 in loaded 50 wt % aqueous MDEA solutions revealed a decrease with increasing CO 2 loading, indicating that the CO 2 capture with aqueous MDEA solutions slows down as CO 2 loading increases.…”

“…The versatility of MD simulations has been proven in literature for computing the self-diffusivity of CO 2 in various solvents, such as aqueous alkanolamine solutions, ,, ionic liquids, , and deep eutectic solvents. , MD simulation is a powerful method for the computation of diffusion coefficients of CO 2 in H 2 O that can compliment experimental measurements and provide useful insight into the physical mechanisms governing diffusion at the nanoscale. MD often take less time and are less expensive than experiments, providing researchers with quicker means of studying diffusion phenomena. , MD simulations eliminate safety concerns associated with high-pressure and high-temperature experimental setups. , Furthermore, MD simulations provide the flexibility to ignore reactions between CO 2 and H 2 O, enabling the focus on the diffusion without considering reaction products. ,, Nevertheless, MD simulation results should always be validated against experimental data to ensure accuracy and reliability in predicting diffusion coefficients under different conditions. To validate computed diffusivities, comparisons with availalble experimental data are performed.…”

“…To validate computed diffusivities, comparisons with availalble experimental data are performed. In the absence of experimental diffusivities, researchers often resort to assessing agreement between the computed and readily accessible experimentally obtained thermodynamic and transport properties, such as densities and viscosities. ,, …”

“…In most of the studies investigating the diffusivities of CO 2 in H 2 O, the concentration of CO 2 in the solvent is very low (1–5 molecules of CO 2 in 216–4124 water molecules), as the solubility of CO 2 in H 2 O under ambient conditions is quite low. At infinite dilution, the intradiffusivity of CO 2 is practically equal to transport diffusion coefficients. ,, A comprehensive study of transport diffusivities in aqueous solutions of CO 2 was performed by Zhao et al These authors computed the MS and Fick diffusivities (along with intradiffusivities) of aqueous solutions containing various gases, including CO 2 , for a temperature range of 673–973 K and a CO 2 mole fraction range of 0.01–0.30. While the authors concluded that temperature and the concentration of CO 2 in the solution significantly influence the MS and intradiffusivities, the interpretation of MS diffusivity trends with changing CO 2 concentration remains challenging due to considerable scatter and uncertainties in the presented data (except for the data set at 673 K where a clear trend of increasing MS diffusivities with increasing CO 2 concentration can be seen).…”

“…Alternatively, approaches such as MD simulations can provide detailed physical insight; , the downside being that they are significantly more computationally demanding compared to engineering models. During the past three decades years, MD has become a reliable and widely used approach for obtaining diffusivities of pure components and mixtures. ,,− This development is the direct result of a number of factors including: (i) the increase of available computational power, (ii) the availability and wide use of optimized open-source software, , and (iii) the development of accurate force fields. − The data obtained from MD simulations can be further used to devise engineering models and validate the semiempirical approaches. ,, Macro-scale modeling approaches involving an equation-of-state such as PC-SAFT coupled with Stokes–Einstein equation or entropy scaling to compute self-diffusivities have been reported in literature, although, to the best of our knowledge, such methods have not been used to compute diffusivity of CO 2 in H 2 O. − …”