Abstract
Four developed machine learning algorithms are proposed to prognosticate the CO2 solubility in amino acid salt solutions, blended with amine solutions as additives, in broad ranges of temperature and pressure. From literature 375 experimental data points for CO2 solubility were collected. The results from the applied algorithms indicated that the CO2 solubility is estimated acceptably close to the experimental values. In the best case, the developed network estimates CO2 solubility in the stated solutions with an average relative deviation of 6.53 % and a correlation coefficient of 0.9892.
| Original language | English |
|---|---|
| Pages (from-to) | 253-261 |
| Number of pages | 9 |
| Journal | Chemical Engineering and Technology |
| Volume | 47 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jan 2024 |
| Externally published | Yes |
ASJC Scopus Subject Areas
- General Chemistry
- General Chemical Engineering
- Industrial and Manufacturing Engineering
Keywords
- Amine
- Amino acid salt
- Artificial intelligence
- CO capture
- Global warming
- CO2 capture
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