Abstract
Some specific examples are presented showing the possibilities offered by molecular modelling tools to obtain relevant data at process conditions while also gaining molecular insights on the techniques used for CO2 capture and separation. Two different technologies, absorption with amine-based systems and adsorption on porous materials, were explored, using the molecular-based equation of state, soft-SAFT, and Grand Canonical Monte Carlo simulations, respectively. The aqueous monoethanolamine (MEA) system was used as the benchmark for absorption and compared to the performance of eight alternative amine-based systems, while sixteen adsorbents belonging to different families (zeolites, Metal Organic Frameworks, silicas and activated carbons), bare or functionalized with alkylamines, were investigated for the separation of CO2 by adsorption. In addition to obtaining molecular information on the CO2 capture process, the models were further used to examine the CO2 capture performance in terms of cyclic working capacity and energy index as key performance indicators, allowing the identification of promising systems that can improve the current ones to be further evaluated for separation in non-power industries. Results show that for the same total amine mass concentration, non-aqueous amine solvents possess a 5–10% reduction in cyclic working capacity, with a 10-30% decrease in the energy index compared to their aqueous counterparts, due to lower heat of vaporization and sensible heat. It has also been obtained that M-MOF-74 and zeolites NaX and NaY structures offer the best results for adsorption in TSA processes. Some adsorbent structures achieved similar values of energy requirement to the ones obtained for alternative amine-based systems (2-2.5 MJ∙kgCO2-1), although the disadvantage of the TSA process versus absorption should be taken into account. These results confirm the reliability of the molecular modelling approach as an attractive and valuable screening tool for CO2 capture and separation processes.
Highlights
Since the nineteenth century, the planet’s average temperature has risen ∼0.9◦C, a change driven largely by the increased emissions into the atmosphere of anthropogenic carbon dioxide and other greenhouse gases (GHGs; Santer et al, 2003; Sreedhar et al, 2017), as a consequence of the energy intensive and industrialized society in which we live
Since the available experimental data for amines with physical solvents systems studied such as glycols and glymes is very scarce or inexistent, we have taken advantage of the molecular nature of soft-Statistical Associating Fluid Theory (SAFT) to predict the behavior over a broad range of conditions (T, Pi)
We have shown, through some specific cases, how molecular modeling techniques can be used to obtain thermophysical properties of alternative selected solvents and adsorbents for CO2 capture, allowing a systematic comparison of the effect of the molecular structure on the performance of both technologies
Summary
The planet’s average temperature has risen ∼0.9◦C, a change driven largely by the increased emissions into the atmosphere of anthropogenic carbon dioxide and other greenhouse gases (GHGs; Santer et al, 2003; Sreedhar et al, 2017), as a consequence of the energy intensive and industrialized society in which we live. A further step includes data generation and data collection for novel systems obtained from these models at typical conditions used in industrial processes Within this approach, it is possible to evaluate the theoretical limits of the energy requirements to capture CO2 under different specific conditions. In soft-SAFT, substances are treated as spherical LJ (12–6) segments or LJ chains characterized by a specific set of molecular parameters, accounting for the different interactions governing the behavior of the fluid A cutoff radius of 12.5 Å was applied to the LJ interactions, while the longrange electrostatic interactions were calculated by using Ewald summation, and Lorentz–Berthelot combining rules were used to calculate adsorbate/framework and the LJ crossed parameters
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