Development of an energy-efficient and cost-effective catalytic regeneration system in the post-combustion CO2 capture process models


Key facts about this Flexible Funding research project

Institution: University of Hull
Department: Chemical Engineering
Start date: 1st July 2021
Principal investigator: Dr Eni Oko, University of Hull
Co-Investigators: Dr Alex Ibhadon, University of Hull
Amount awarded by UKCCSRC: £29,966

Why is this research needed?

Carbon capture is predicted to help deliver about 19% of the cumulative global CO2 emissions reduction from the power sector by 2050[1]. However, post-combustion CO2 capture (PCC), the most matured carbon capture technology, is energy-intensive, typically > 4GJ/tonCO2 and require a huge solvent circulation rate at least 2 times the gas flowrate (w/w)[2]. The implication is a high cost of capture, >$48/tonCO2[3]  and large process time inertia leading to a sluggish response characteristic with impact on the load following capability of their host power plants[4]. One way to address this challenge is to develop an innovative catalysed solvent regeneration system for the PCC process[5].  Considering that PCC constitutes 75-80% of the total cost of the complete carbon capture and storage (CCS) process[6], it is therefore predicted that the total cost of the CCS process could be reduced substantially by employing catalysed solvent regeneration.

The aim of the project is to identify and test new catalysts for catalysed solvent regeneration in the post-combustion CO2 capture process with the target to achieve up to 50% higher CO2 desorption rate and 30-40% lower total cost for the complete process. This project will test around 100 catalysts for this purpose using a computational approach and a few selected catalysts further tested in the lab. The outcome of the computational test will be a critical dataset of the properties of the catalyst including the reaction kinetics which are crucial for designing and modelling catalysed solvent regeneration process using the catalysts. A process model of the post-combustion capture process with catalysed solvent regeneration will also be developed to establish their techno-economic performance metrics.

This project covers computational catalyst screening, process modelling/simulation and validation, technical and economic analysis for post-combustion CO2 capture process with catalysed solvent regeneration. The multi-disciplinary research includes experts in catalysis and CO2 capture process development via Process Systems Engineering. The project has a strong industrial link as UNIPER, a global energy company and partner in the project have expressed a strong interest in exploring the outcome of the research. In addition, this project has access to experimental facilities at the University of Regina, Canada where lab tests will be used to validate computational results from the work at the University of Hull.

What is this research investigating?

To achieve the project’s aim, the following project objectives have been set out:

(a) Computational catalyst screening based on the density functional theory model. Computational catalyst screening is cost-effective and time-saving compared to experimental lab-based screening. It will therefore enable the researchers to screen more catalyst options – it is expected to screen around 100 catalyst options – and build a vital database of the reaction kinetic information of the catalysts. These data, which are currently not available for the majority of currently identified catalysts, are useful for modelling and design of the catalysed solvent regeneration process.

(b) Laboratory testing of selected catalysts to confirm results from the computational assessment. This will test will stability test via characterisation using X-ray diffraction (XRD), thermogravimetric analysis (TGA), scanning electron microscope (SEM), and transmission electron microscope (TEM) and Raman spectroscopy to investigate the catalytic effect of the selected catalysts on both sorption and desorption.

(c) Modelling and validation of the complete post-combustion CO2 capture process with catalysed regeneration.

The model, which will be validated with data from the project partner in Canada (University of Regina) will form the basis for a detailed analysis of the process.

(d) Techno-economic analysis of the complete PCC process with catalysed regeneration.

The model to be developed and validated in this project will be used to perform benchmark techno-economic analysis of the process. This analysis will produce a critical dataset that will support decision-making for policymakers and technology developers.

What does the research hope to achieve?

The proposed project is predicted to deliver a 30-40% cost reduction of the PCC process.

Identified benefits to various groups will include:

(a) The researchers will publish a dataset of the properties of 100 catalysts (derived from molecular simulation model) on open access, which may benefit other researchers worldwide. This will support ongoing research in this subject by other researchers. The process model will also provide useful insight for other researchers.

(b) The techno-economic data including the cost of capture, energy penalty and so on, that will come from this research will support decision-making by policymakers.

(c) This work will provide useful insight for technology developers on catalysed regeneration.

(d) The cost impact of low carbon technology transition will be borne by the wider society. The proposed project offers a cheaper route for reaching low carbon transition goals and therefore lessen the cost burden for the wider society.

[1] [Accessed April 2021]

[2] Canepa, R., Wang, M., Biliyok, C. and Satta, A. 2013. Thermodynamic analysis of combined cycle gas turbine power plant with post-combustion CO2 capture and exhaust gas recirculation. Proc IMechE Part E: J Process Mechanical Engineering 227(2); 89–105

[3] Rubin, E.S., Davison, J.E. and Herzog, H.J. 2015. The cost of CO2 capture and storage. International Journal of Greenhouse Gas Control 40; 378-400.

[4] Liao, P., Li, Y., Wu, X., Wang, M. and Oko, E. 2020. Flexible operation of large-scale coal-fired power plant integrated with solvent-based post-combustion CO2 capture based on neural network inverse control. International Journal of Greenhouse Gas Control 95; 102985.

[5] Shi, H., Naami, A., Idem, R. and Tontiwachwuthikul, P. 2014. Catalytic and non-catalytic solvent regeneration during absorption-based CO2 capture with single and blended reactive amine solvents. International Journal of Greenhouse Gas Control 26; 39-50.

[6] Davison, J. 2007. Performance and costs of power plants with capture and storage of CO2. Energy 32; 1163–1176

Research updates

This research is ongoing, so not all research papers and datasets have yet been published.

However, check below for recent updates and resources on this research project: we will add these when they are available.