Multivariate Calibration of CO2 solubility in Methyldiethanolamine (MDEA) using Raman Spectroscopy
For decades, Carbon dioxide (CO2) capturing process had been an important issues since it is one of the major greenhouse gas (GHG) contributors which leads to the global warming. Alkanolamines such as Methyldiethanolamine (MDEA) had been widely used for CO2 capturing by absorption process. A stud...
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| Main Author: | |
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| Format: | Final Year Project |
| Language: | English |
| Published: |
IRC
2015
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| Subjects: | |
| Online Access: | http://utpedia.utp.edu.my/16288/1/15641.Hafiz%20Mokhtar.FYPdessertation.Sept2015.pdf http://utpedia.utp.edu.my/16288/ |
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| Summary: | For decades, Carbon dioxide (CO2) capturing process had been an important issues since
it is one of the major greenhouse gas (GHG) contributors which leads to the global
warming. Alkanolamines such as Methyldiethanolamine (MDEA) had been widely used
for CO2 capturing by absorption process. A study on carbon dioxide (CO2) solubility was
done inside aqueous MDEA solution by using Raman Spectroscopy with the goal of
calculating the CO2 loading. This is because, there was still no direct measurement to
calculate the CO2 loading inside the MDEA solution. Therefore, a sensor or a
measurement device is needed to calculate the CO2 loading. After a three careful
experiment had been run on three different MDEA concentrations which are 10%, 20%
and 30% concentration, the raw data from the Raman Spectrum had been obtained.
Matlab simulation was used to construct a statistical calibration and validation models
between the CO2 loading and the peak of Raman Shift by using Partial Least-Squares
method (PLS). Results shows that lower MDEA concentration produce better
Coefficient of Determination (R2) and Mean Square Error (MSE) for calibration models
while the combination of the three MDEA concentrations has found as a good fit with
R2 of 0.9651 and MSE of 0.0347 in CO2 loading prediction. |
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