Rate-Based Absorption Modeling for Postcombustion CO2 Capture with Additively Manufactured Structured Packing
Carbon capture using amine-based solvents in an absorption process is a leading candidate for reducing greenhouse gas emissions in industrial flue gas streams. To reduce operating costs and associated parasitic energy of these processes, process intensification utilizing additively manufactured stru...
Saved in:
Published in | Industrial & engineering chemistry research Vol. 60; no. 41; pp. 14845 - 14855 |
---|---|
Main Authors | , |
Format | Journal Article |
Language | English |
Published |
United States
American Chemical Society
20.10.2021
American Chemical Society (ACS) |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Carbon capture using amine-based solvents in an absorption process is a leading candidate for reducing greenhouse gas emissions in industrial flue gas streams. To reduce operating costs and associated parasitic energy of these processes, process intensification utilizing additively manufactured structured packing has emerged as a new technology to manage exothermic reactions during absorption while improving CO2 capture. A rate-based model framework has been developed for these novel packings that incorporates the mass and heat transfer phenomena for amine-based absorption of CO2. The rate-based model framework is first benchmarked using available solubility data and pilot plant data for aqueous monoethanolamine. The model validation shows accurate prediction of both CO2 equilibrium partial pressures and ion speciation for solubility data as well as CO2 capture, temperature profile, and solvent composition for pilot plant data in the absorption column. The model framework is then applied toward predicting the CO2 capture performance of additively manufactured structured packing. Simulations agree with experimental data in predicting the CO2 capture and the capture performance increase due to cooling within the structured packing device. Advantages of this rate-based model framework are the utilization of correlations that may predict mass transfer and heat transfer coefficients of the packing based on the geometric properties of the device and the implementation of the model framework in open-source programming. |
---|---|
Bibliography: | USDOE Office of Fossil Energy (FE) AC05-00OR22725 |
ISSN: | 0888-5885 1520-5045 |
DOI: | 10.1021/acs.iecr.1c02756 |