Javascript must be enabled to continue!
Amine Structure-Foam Behavior Relationship and Its Predictive Foam Model Used for Amine Selection for Design of Amine-based Carbon Dioxide (CO2) Capture Process
View through CrossRef
Background:
The use of an amine solution to capture CO2 from flue gases is one of the
methods applied commercially to clean up the exhaust gas stream of a power plant. One of the
issues in this process is foaming which should be known in order to select a suitable amine for
design.
Objectives:
In this work, all possible types of amines used for CO2 capture, namely, alkanolamines,
sterically hindered alkanolamines, multi-alkylamines and cyclic amines, were investigated to elucidate
their chemical structure–foaming relationships.
Methods:
Foam volume produced by each type of 2M amine solution with its equilibrium CO2
loading was measured at 40°C using 94 mL/min of N2 flow.
Results:
Amines with a higher number or a longer chain of the alkyl group exhibited higher foam
volume because of alkyl group’s ability to decrease the surface tension while increasing the viscosity
of the solution. An increase in the number of hydroxyl or amino groups in the amine led to the
reduction of foam formation due to the increase in surface tension and a decrease in viscosity of the
solution. The predictive foam models for non-cyclic and cyclic-amines developed based on the
structural variations, surface tension and viscosity of 29 amines predicted the foam volume very
well with average absolute deviations (AAD) of 12.7 and 0.001%, respectively. The model accurately
predicted the foam volume of BDEA, which was not used in model development with 13.3
%AD.
Conclusion:
This foam model is, therefore, indispensable in selecting a suitable amine for an
amine-based CO2 capture plant design and operation.
Bentham Science Publishers Ltd.
Title: Amine Structure-Foam Behavior Relationship and Its Predictive Foam Model Used for Amine Selection for Design of Amine-based Carbon Dioxide (CO2) Capture Process
Description:
Background:
The use of an amine solution to capture CO2 from flue gases is one of the
methods applied commercially to clean up the exhaust gas stream of a power plant.
One of the
issues in this process is foaming which should be known in order to select a suitable amine for
design.
Objectives:
In this work, all possible types of amines used for CO2 capture, namely, alkanolamines,
sterically hindered alkanolamines, multi-alkylamines and cyclic amines, were investigated to elucidate
their chemical structure–foaming relationships.
Methods:
Foam volume produced by each type of 2M amine solution with its equilibrium CO2
loading was measured at 40°C using 94 mL/min of N2 flow.
Results:
Amines with a higher number or a longer chain of the alkyl group exhibited higher foam
volume because of alkyl group’s ability to decrease the surface tension while increasing the viscosity
of the solution.
An increase in the number of hydroxyl or amino groups in the amine led to the
reduction of foam formation due to the increase in surface tension and a decrease in viscosity of the
solution.
The predictive foam models for non-cyclic and cyclic-amines developed based on the
structural variations, surface tension and viscosity of 29 amines predicted the foam volume very
well with average absolute deviations (AAD) of 12.
7 and 0.
001%, respectively.
The model accurately
predicted the foam volume of BDEA, which was not used in model development with 13.
3
%AD.
Conclusion:
This foam model is, therefore, indispensable in selecting a suitable amine for an
amine-based CO2 capture plant design and operation.
Related Results
Lab Evaluation of Long-Distance Propagation of CO2 Foam for Deep Mobility Control
Lab Evaluation of Long-Distance Propagation of CO2 Foam for Deep Mobility Control
Abstract
Long-distance foam propagation is crucial and necessary for deep mobility-control applications of foam in geological formations. The long-distance propag...
Solar fuels via two-step thermochemical redox cycles for power and fuel production
Solar fuels via two-step thermochemical redox cycles for power and fuel production
With the issue of the rise of anthropogenic CO2, global warming and rise of the primary energy demand, strong measures for the energy transition and the diversification with renewa...
Evaluation of Kaolinite and activated carbon performance for CO2 capture
Evaluation of Kaolinite and activated carbon performance for CO2 capture
Global climate change is one of the major threats facing the world today and can be due to increased atmospheric concentrations of greenhouse gases (GHGs), such as carbon dioxide (...
Foam Injection Test in the Siggins Field, Illinois
Foam Injection Test in the Siggins Field, Illinois
A pilot test in this tired, old field, confirmed the laboratory-derived conclusion that foam can do more than soften a beard or ruin a river. It can decrease the mobility of gas an...
Design And Operation Of The Levelland Unit CO2 Injection Facility
Design And Operation Of The Levelland Unit CO2 Injection Facility
Abstract
The Levelland CO2 Facility provides CO2 storageand handling capacity for the five CO2 injection pilots located in the Levelland Unit. Facilities pilots l...
Rapid Large-scale Trapping of CO2 via Dissolution in US Natural CO2 Reservoirs
Rapid Large-scale Trapping of CO2 via Dissolution in US Natural CO2 Reservoirs
Naturally occurring CO2 reservoirs across the USA are critical natural analogues of long-term CO2 storage in the subsurface over geological timescales and provide valuable insights...
Indirect Effects of Non-CO2 Forcings on Carbon Budgets in Overshoot pathways
Indirect Effects of Non-CO2 Forcings on Carbon Budgets in Overshoot pathways
Overshoot pathways involve exceeding a specific temperature target temporarily and returning to it using deliberate carbon dioxide removal methods. Quantifying the overshoot carbon...
ecision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predi
ecision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predi
The scope of sensor networks and the Internet of Things spanning rapidly to diversified domains but not limited to sports, health, and business trading. In recent past, the sensors...

