Estimation of CO2 Absorption by a Hybrid Aqueous Solution of Amino Acid Salt with Amine

被引：3

作者：

Amirkhani, Farid ^{[1
]}

Dashti, Amir ^{[1
]}

Abedsoltan, Hossein ^{[2
]}

Mohammadi, Amir H. ^{[3
,4
]}

机构：

[1] Univ Kashan, Fac Engn, Dept Chem Engn, Kashan, Iran

[2] Univ Toledo, Dept Chem Engn, Toledo, OH USA

[3] Inst Rech Genie Chim & Petrolier IRGCP, Paris, France

[4] Univ KwaZulu Natal, Sch Engn, Discipline Chem Engn, Howard Coll Campus,King George 5 Avenue, ZA-4041 Durban, South Africa

来源：

CHEMICAL ENGINEERING & TECHNOLOGY | 2024年 / 47卷 / 02期

关键词：

Amine; Amino acid salt; Artificial intelligence; CO2; capture; Global warming; ARTIFICIAL NEURAL-NETWORK; MIXED-GAS SEPARATION; CARBON-DIOXIDE; IONIC LIQUIDS; MOLECULAR DESCRIPTORS; H2S SOLUBILITY; PREDICTION; OPTIMIZATION; PIPERAZINE; CAPTURE;

D O I：

10.1002/ceat.202200469

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

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.

引用

页码：253 / 261

页数：9

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