(158e) Material Screening and Process Optimization for Cost-Effective Adsorption-Based CO2 Capture

Hasan, M. M. F., Princeton University
First, E. L., Princeton University
Floudas, C. A., Princeton University

Elecrticity generation in power plants account for more than 73% of the total stationary CO2 emissions in the United States [1]. While carbon capture, utilization and storage (CCUS) is an enabling technology to reduce CO2 emissions from power plants, the costs of CO2 capture and compression, which  represent 60–70% of the total CCUS cost, are estimated to exceed $58/tonne of CO2 avoided with current technology, leading to about a 63% increase in the levelized electricity cost [2].

Adsorption-based CO2 capture using zeolites and metal-organic frameworks (MOFs) with large internal surfaces are promising technologies to separate CO2 from power plant flue gases. In a typical adsorption process, CO2 is selectively adsorbed onto a solid sorbent while the clean flue gas passes through. The adsorbed CO2 is released or desorbed by lowering the pressure. While pressure swing adsorption (PSA) process shows promise, the cost of PSA-based CO2 capture is still high.

We have identified novel materials for cost-effective CO2 capture by combining in silico screening of microporous materials and PSA process optimization for the first time. Our hierarchical computational approach [3-4] efficiently screens large databases of zeolites, based on three dimensional pore characterization [5-6], shape selectivity [7-10], size selectivity, and adsorption selectivity. Next, process optimization is introduced to generate a rank-ordered list based on total cost of capture and compression. The purity, recovery, energy penalty and the cost of capture and compression are obtained by a detailed nonlinear algebraic and partial differential equation (NAPDE) model [11] that describes the PSA process. We not only select the most cost-effective materials, but we also attain the optimal process conditions while satisfying purity, recovery, and other process constraints.

The top zeolites can capture and compress CO2 to 150 bar from a mixture of 14% CO2 and 86% N2 at less than $30 per ton of CO2 captured and compressed. This is a significant reduction in cost, compared to the costs of absorption and membrane processes [12-14], and other adsorption processes which use zeolite 13X [11]. Several zeolites have moderate selectivities, yet they cost-effectively capture CO2 with 90% purity and 90% recovery using a 4-step adsorption process. Our results show that no single materials-centric metric is sufficient to always select optimal materials, since both material and process considerations play a role. A combined atomistic, geometric, and process understanding is necessary to achieve the design specifications for a cost-effective and optimal CO2 capture process.


[1]. DOE/NETL. Carbon Sequestration Atlas of the United States and Canada, 2012.
[2]. Finkenrath, M. I. Cost and performance of carbon dioxide capture from power generation, EIA Report, 2011.
[3]. Hasan, M. M. F.; First, E. L.;  Floudas, C. A. Cost-effective CO2 capture based on in silico screening of zeolites and process optimization. Submitted for publication, 2013.
[4]. U.S. Provisional Patent Application #61/761,436 and #61/765,284.
[5]. First, E. L.; Gounaris, C. E.; Wei, J.; Floudas, C. A. Computational characterization of zeolite porous networks: an automated approach. Phys. Chem. Chem. Phys. 2011, 13:17339-17358.
[6]. First, E. L.; Floudas, C. A. MOFomics: Computational pore characterization of metal-organic frameworks. Micropor. Mesopor. Mater. 2013, 165:32-39.
[7]. Gounaris, C. E.; Floudas, C. A.; Wei, J. Rational design of shape selective separation and catalysis-I: Concepts and analysis. Chem. Eng. Sci. 2006, 61:7933-7948.
[8]. Gounaris, C. E.; Wei, J.; Floudas, C. A. Rational design of shape selective separation and catalysis-II: Mathematical model and computational studies. Chem. Eng. Sci. 2006, 61:7949-7962.
[9]. Gounaris, C. E.; Wei. J.; Floudas, C. A.; Ranjan, R.; Tsapatsis, M. Rational design of shape selective separations and catalysis: Lattice relaxation and effective aperture size. AIChE J. 2009, 56:611-632.
[10]. First, E. L.; Gounaris, C. E.; Floudas, C. A. Predictive framework for shape-selective separations in three-dimensional zeolites and metal-organic frameworks. Langmuir. 2013, 29:5599-5608.
[11]. Hasan, M. M. F.; Baliban, R. C.; Elia, J. A.; Floudas, C. A. modeling, simulation, and optimization of postcombustion CO2 capture for variable feed concentration and flow rate. 2. Pressure swing adsorption and vacuum swing adsorption processes. Ind. Eng. Chem. Res. 2012b, 51,15665-15682.
[12]. Hasan, M. M. F.; Baliban, R. C.; Elia, J. A.; Floudas, C. A. modeling, simulation, and optimization of postcombustion CO2 capture for variable feed concentration and flow rate. 1. Chemical absorption and membrane processes. Ind. Eng. Chem. Res. 2012a, 51, 15642-15664.
[13]. DOE/NETL-2010/1397. Cost and performance baseline for fossil energy plants. Vol. 1: Bituminous coal and natural gas to electricity, revision 2. U.S. Department of Energy National Energy Technology Laboratory: Pittsburgh, PA, August 2007.
[14]. Rubin, E.; Zhai, H. The cost of carbon capture and storage for natural gas combined cycle power plants. Environ. Sci. Technol. 2012, 46, 3076-3084.