Search

Pandya proposed the first steady-state rate-based model for the chemical absorption process in a packed column using the aqueous CO2–MEA system. Later several modeling studies are also reported based on Pandya’s approach but limited to low pressure (≈1 bar) and low CO2loadings (<0.5 mol/mol). Recently, the interest in processing CO2-rich natural gas at high-pressure conditions has been increased. Therefore, in this study, the Pandya model is modified to simulate the packed absorption column using an aqueous CO2–MEA system for the high-pressure and high-CO2loading range. The sequential chemical reactions, along with the respective mass transfer resistances that occur at low (<0.5 mol/mol) and high (>0.5 mol/mol) CO2loadings, are added. This is achieved by theoretically segmenting the packed column into two sections. This strategy simplifies the computation of subsequent fast and slow reaction regimes that occur over a high-CO2loading range. The gas–liquid nonideal behavior is described using the Peng–Robinson (EOS) and Kent Eisenberg models. The developed model is effectively validated using the experimental data at low- (≈1.03 bar) and high- (50 bar) pressure conditions over a wide CO2loading range (≈0–1.0 mol/mol). In a parity plot between measured and simulated CO2concentration, R2is found to be 0.99 and 0.97, respectively, for the low- (≈1.03 bar) and high- (50 bar) pressure systems. This indicates that the proposed model can accurately predict the critical design parameters at the high-pressure and high-CO2loading conditions, with minimum computational intricacy.

The sorption-enhanced steam methane reforming (SE-SMR) process, which integrates methane steam reforming with in situ CO2capture, represents a breakthrough technology for clean hydrogen production. This comprehensive review thoroughly explores the SE-SMR process, emphasizing its ability to efficiently combine carbon capture with hydrogen generation. The review evaluates the mechanisms of SE-SMR and evaluates a range of innovative sorbent materials, such as CaO-based, alkali-ceramic, hydrotalcite, and waste-derived sorbents. The role of catalysts in improving hydrogen production within SE-SMR processes is also discussed, along with considering bi-functional materials. In addition to examining reaction kinetics and advanced process configurations, this review touches on the techno-economic aspects of SE-SMR. While the analysis does not provide an in-depth economic evaluation, key factors such as potential capital costs (CAPEX), operational expenses (OPEX), and scalability are considered. The review outlines the potential of SE-SMR to offer more efficient hydrogen production, with the added benefit of in situ carbon capture simplifying the process design. Although a detailed economic comparison with other hydrogen production technologies was not the focus, this review emphasizes SE-SMR's promise as a scalable and flexible solution for clean energy. With its integrated design, SE-SMR offers pathways to industrial-scale hydrogen production. This review provides a valuable overview for researchers, policymakers, and industry experts engaged in advancing sustainable and efficient hydrogen production technologies.

Carbon dioxide separation has gained immense importance since its detrimental effects towards our environment has been realized. Commercially, CO2 has been captured by absorption in alkanolamines such as diethanolamine (DEA), since many years. The thermodynamics and kinetics of the process is a key factor towards its efficiency and significantly depends on its qualitative and quantitative speciation. In this work, the analysis of speciation for CO2 loaded aqueous DEA has been performed by Raman spectroscopy. Experimentally determined CO2 loading data and modified Kent Eisenberg equation was used to quantify the chemical species present. The speciation results were fitted with the respective characteristic Raman peaks of (CO3-, HCO3-, DEACOO-, DEA, DEA+, CO2) by Principal Component Regression (PCR). The fitted results showed good agreement with thermodynamically predicted chemical species.

Carbon dioxide (CO2) capturing has been an important issue for decades. Alkanoamines, such as diethanolamine (DEA) have been widely used for CO2 separation by absorption process. During this process, CO2 loading measurement is an imperative action for a proper process control. Currently used methods are titration based which requires a long processing time. In this work Raman spectroscopy is used to model and predict the CO2 loading in wide range (0-0.97 CO2 mole/amine mole). The models are developed by using Raman peak ratios to minimize the error due to peaks fluctuations. The Raman peak ratio of 1022 cm-1/1461cm-1 has been found as a good fit with the coefficient of determination (R2) of 0.92 and mean squared error (MSE) of 0.00656 CO2 mole2/ amine mole2 in prediction of CO2 loading.