Abstract
Membrane technology is considered a high-efficiency separation and purification technology due to its low carbon footprint and low energy consumption. In this work, carbon molecular sieve (CMS) membranes for the selective separation of CO2 from methane and nitrogen were successfully fabricated. A gas permeation setup was employed to test CO2/N2, CO2/CH4 perm-selectivities, and CO2 permeances of the CMS membranes. To study the impact of temperature and pressure, the experiments have been carried out at a temperature range from 20 to 350 °C and pressure from 1 to 40 bar. Furthermore, a novel multistage membrane process design was proposed to test the feasibility of the fabricated membranes for CO2 separation from different sources of carbon emission. Three major sweetening processes are considered, including CO2 capture from coal-fired flue gas, biogas upgrading (BG), and natural gas (NG). A structural optimization approach is applied to determine the most efficient membrane strategy from the point of view of gas separation cost. By varying the membrane properties and separation targets, the effect of these parameters on capital expenditure (CAPEX), operating expenditure (OPEX), and energy consumption was studied. The economic assessment revealed a superior potential for CO2/N2 separation with a capture cost of 41.8 €/ton of CO2 and energy consumption of 1.9 GJ/ton CO2. The use of the optimal two-stage membrane configuration resulted in a competitive CO2/CH4 separation cost of 4.2 €/ton of sweet NG and 23 €/ton of BG for natural gas and biogas upgrading, respectively.
Original language | English |
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Pages (from-to) | 19116-19132 |
Number of pages | 17 |
Journal | Industrial and Engineering Chemistry Research |
Volume | 62 |
Issue number | 45 |
Early online date | 2 Jul 2023 |
DOIs | |
Publication status | Published - 15 Nov 2023 |
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Reports from Eindhoven University of Technology Add New Data to Findings in Engineering (Carbon Molecular Sieve Membranes for Selective Co2/ch4 and Co2/n-2 Separation: Experimental Study, Optimal Process Design, and Economic Analysis)
Gallucci, F., Rahimalimamaghani, A. & Ramezani, R.
27/07/23
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