Physicochemical data for amine based CO2 capture process

Abstract

Amine based post-combustion carbon capture is a highly discussed CO2 removal method from flue gas. Large-scale CO2 capture facilities with effective solvents are required to make a significant impact on reducing CO2 emissions from power plants and existing facilities. Physical properties of solvents play a major role in designing process equipment. Measured properties like density, viscosity and surface tension are used in mathematical models developed for mass transfer and interfacial area that are used in designing absorption columns. Further, developed correlations to represent measured physical properties are useful in process simulations.

This work presents measured density and viscosity data of both CO2 loaded and non-loaded aqueous amine mixtures at different amine concentrations, temperatures and CO2 loadings. Density and viscosity increase with the increase of CO2 loading and decrease with the increase of temperature. The excess volume of binary and ternary aqueous amine mixtures was calculated from measured density data and correlated using a Redlich-Kister type polynomial. A density correlation proposed by Aronu was adopted to correlate densities of MEA + H2O mixtures. A correlations based on density deviation 𝜌𝛾 were proposed for MDEA + H2O, DMEA + H2O and DEEA + H2O mixtures. Aronu’s density correlation was modified to fit densities of MEA + H2O + CO2 mixtures. For AMP + MEA + H2O + CO2 mixtures, density was correlated using a modified Weiland’s correlation and a Setschenow type correlation. The accuracies of density data fits were satisfactory as the average absolute relative deviation (AARD) was typically less than 1% and correlations are suitable to perform engineering calculations.

Eyring’s viscosity model based on Eyring’s absolute rate theory was adopted to calculate the free energy of activation for viscous flow ∆𝐺0+ of CO2 loaded and non-loaded aqueous amine mixtures. Further, the excess free energy of activation for viscous flow ∆𝐺0𝐸+ was calculated and a Redlich-Kister type polynomial was proposed to fit the measured viscosities of aqueous amine mixtures. For the mixtures of MEA + H2O + CO2 and AMP + MEA + H2O + CO2, empirical correlations were proposed to fit calculated ∆𝐺0+ from Eyring’s viscosity model and then the correlation was used to represent the measured viscosities. The viscosity deviation 𝜂𝐸 was determined for aqueous amine mixtures to investigate types of intermolecular interactions in the mixtures. Further, a modified Weiland’s correlation and a Setschenow type correlation were proposed to correlate viscosities of AMP + MEA + H2O + CO2 mixtures. The accuracies of the viscosity data fits were typically less than 2% AARD and the proposed correlations can be recommended to use in engineering calculations.

The approach of using feedforward backpropagation artificial neural networks (ANNs) to represent densities and viscosities of CO2 loaded and non-loaded aqueous amine solutions gained high accuracies in data fit compared to the conventional empirical correlations. The ANNs are with multiple inputs of mole fractions of amines, CO2 and temperature of the mixtures, one hidden layer and one output that is either density or viscosity of the mixtures. The optimum number of neurons in the hidden layer was found by calculating Mean Squared Error (MSE) over thirty neurons.

The experiments performed in a CO2-rig located at USN Porsgrunn illustrates the variations of density and viscosity at the top and the bottom of the absorber column at different liquid flow rates. The density of the solvent increased although the temperature increased due to the exothermal reaction between CO2 and MEA. The influence of temperature increase caused to decrease the viscosity at the bottom of the column even the CO2 loading is higher than at the top of the column. Process simulations were performed to predict the variations of density and viscosity of the column.