(203al) Simuation and Assessment of CO2 Capture By Ionic Liquid-Based Solvents | AIChE

(203al) Simuation and Assessment of CO2 Capture By Ionic Liquid-Based Solvents

Authors 

Huang, Y. - Presenter, Institute of Process Engineering, Chinese Academy of Sciences
Zhang, X., Institute of Process Engineering, Chinese Academy of Sciences
Zhang, S., Institute of Process Engineering, Chinese Academy of Sciences
Dong, H., Institute of Process Engineering, Chinese Academy of Sciences
Xu, Y., Institute of Process Engineering, Chinese Academy of Sciences



Carbon dioxide (CO2) capture from flue gases is drawing increasing interest as an important method for the control of greenhouse gas emissions. As an emerging absorbent, ionic liquids (ILs) have been paid much attention because of their negligible vapor pressure with potentials of lower regeneration energy and solvent losses1. Although current studies have reported various CO2 capture performances of pure ionic liquids, including conventional and task-specific ionic liquids, and ionic liquid-based mixtures, lacking the assessment and comparison of the new various ionic liquid-based capture systems restricts their large scale application and commercialization. 
    It was known that a series of properties of solvents have impact on the performance of capture process, such as absorption capacity, kinetics and heat of absorption. In this work, we focused on the performance assessment of CO2 capture process by IL-based solvents, including three IL systems with physical absorption, two IL systems with chemical absorption and some IL-amine blended solvents. The conventional 30%wt Monoethanolamine(MEA) solvent is simulated as a reference capture system. The process configuration of chemical absorption with IL system and IL-amine blended system are similar to conventional MEA process. The process configuration of physical absorption system is mainly composed of a high pressure absorber and vacuum flash regenerator.
    Reliable thermodynamic models are the basis for a process simulation and optimization. With regard to CO2-amine solution system, the physical properties, chemical equilibrium and vapor-liquid phase equilibrium (VLE) can be precisely predicted using the Kent-Eisenberg electrolyte method as maturely implemented by Aspen Technology. While for CO2-IL systems, the physical properties and VLE models should be modified since they are less mature and rarely used in a commercial simulation software. We have successfully estimated the physicochemical properties of ILs using the FCCS method2. SRK equation of state was used for predicting the solubility CO2 in IL. The binary parameters of NRTL activity model for VLE of IL-amine and IL-H2O were regressed from experimental data. Based on these thermodynamic models, all the capture systems are simulated and calculated to get the values of these following key parameters: energy consumption, quantity of solvent recycling, total plant investment, annual variable operating and maintenance cost. Based on the assessment result of each kind of IL-based capture process, it will become straightforward to figure out a capture system with benefits both on energy consumption and economic cost. The primary results show that IL-amine mixture solvent is quite an applicable selection for large scale CO2 capture. Besides, other properties of solvents such as toxicity, volatility, degradation and corrosivity will be considered during the process assessment in the future work.

Acknowledge

This work was financially supported by Key Program of National Natural Science Foundation of China (No. 21036007), by the National High Technology Research and Development Program of China (No. 2011AA050606), and by the Petrochemical Joint Funds of NSFC-CNPC (No. U1162105).

References

1.    Zhang X, Dong H, Zhao Z, Zhang S, Huang Y. Carbon capture with ionic liquids: overview and progress. Energy & Environmental Science. 2012;5:6668-6681.
2.    Huang Y, Dong H, Zhang X, Li C, Zhang S. A new fragment contribution-corresponding states method for physicochemical properties prediction of ionic liquids. AIChE Journal. 2013; 59 (4): 1348-1359.