Experimental measurements of CO2 solubility, viscosity, density, sound velocity and evaporation rate for 2-(2-aminoethoxy)ethanol (DGA) + 1-methylpyrrolidin-2-one (NMP) / water + ionic liquid systems

Ebrahiminejadhasanabadi, Mojgan; Nelson, Wayne Michael; Naidoo, Paramespri; Mohammadi, Amir H.

doi:10.1016/j.fluid.2022.113475

Cited by 9 publications

(14 citation statements)

References 62 publications

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“…In order to determine the Henry's constants (H 1,2 ) for methane (1) or ethane (1) in NMP (2), the data were fitted to the Krichevsky-Kasarnovsky equation: 48…”

Section: Data Modelingmentioning

confidence: 99%

“…21 Results in the literature show that mixing amines with physical solvents in hybrid solvents for CO 2 solubility decreases the corrosion rate of process equipment, 22 reduces heat consumption, 23−27 improves reaction kinetics and absorption rate, 16,17,28−31 and increases absorption capacity. 1,32,33 A previous study measured the solubility of CO 2 in conventional aqueous monoethanolamine (MEA) solvents and hybrid solvents of MEA and n-methyl-2-pyrrolidone (NMP). 32 Results indicated that replacing water with NMP in the aqueous MEA solvent with MEA mass fraction of 0.1 greatly increases CO 2 solubility by almost 81% at pressures between 0.21 to 2 MPa.…”

Section: Introductionmentioning

confidence: 99%

“…Absorption processes containing hybrid solvents of amine solvents and physical solvents couple the properties of chemical solvents and physical solvents to increase the efficiency of the process and minimize the disadvantages of individual processes . Results in the literature show that mixing amines with physical solvents in hybrid solvents for CO 2 solubility decreases the corrosion rate of process equipment, reduces heat consumption, − improves reaction kinetics and absorption rate, ,,− and increases absorption capacity. ,, …”

Section: Introductionmentioning

confidence: 99%

“…Compared to oil and coal, natural gas has a lower environmental impact and emits fewer air pollutants. − It primarily consists of methane, typically between 50 and 90%, and ethane, usually between 0.5 and 20%, with the composition dependent on the type, depth, and location of the underground reservoirs, the porosity of the sedimentary deposits, and the geology of the area. This fuel also contains heavier hydrocarbons and a variety of impurities, including the acidic gases carbon dioxide (CO 2 ) and hydrogen sulfide (H 2 S). − They are corrosive, reduce the heating value of natural gas, can crystallize and block pipeline systems leading to transportation breakdowns, and make more air pollutants during combustion.…”

Section: Introductionmentioning

confidence: 99%

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Investigation of the Solubility of Methane and Ethane in Hybrid Sweetening Solutions of 2-Aminoethanol and 1-Methylpyrrolidin-2-one/Water

Ebrahiminejadhasanabadi

Nelson

Naidoo

2023

J. Chem. Eng. Data

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Hydrocarbons of natural gas are captured by the solvent in the gas-sweetening absorption process and added to losses in production. Therefore, knowledge of hydrocarbon solubilities in solvents is required to assess and overcome these losses. In this study, the solubility of the main components of natural gas, methane and ethane, in n-methyl-2-pyrrolidone and monoethanolamine-based solvents was determined at the temperature of 313.15 K and pressures up to 2.366 MPa. Mass fractions of 0.10, 0.20, and 0.30 amine in the solutions were used in measurements that were performed using a static-synthetic method. The experimental data were modeled using the Soave−Redlich−Kwong Equation of State. Experimental results showed that the replacement of the aqueous part of conventional monoethanolamine solvents with n-methyl-2-pyrrolidone increased the solubility of desirable components of natural gas which is a negative side effect. The addition of monoethanolamine to n-methyl-2-pyrrolidone outperformed the Purisol solvent in terms of carbon dioxide absorption and decreased hydrocarbon solubility.

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“…In order to determine the Henry's constants (H 1,2 ) for methane (1) or ethane (1) in NMP (2), the data were fitted to the Krichevsky-Kasarnovsky equation: 48…”

Section: Data Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Investigation of the Solubility of Methane and Ethane in Hybrid Sweetening Solutions of 2-Aminoethanol and 1-Methylpyrrolidin-2-one/Water

Ebrahiminejadhasanabadi

Nelson

Naidoo

2023

J. Chem. Eng. Data

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“…Under identical conditions, the viscosity of the carbon dioxide aqueous solution, as measured with a viscometer, is presented in Figure 9 [40].…”

Section: Physical Properties and Seepage Characteristic Parametersmentioning

confidence: 99%

A Case Study on the CO2 Sequestration in Shenhua Block Reservoir: The Impacts of Injection Rates and Modes

Tang,

Ding,

Song

et al. 2023

Energies

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Carbon capture and storage (CCS) is the most promising method of curbing atmospheric carbon dioxide levels from 2020 to 2050. Accurate predictions of geology and sealing capabilities play a key role in the safe execution of CCS projects. However, popular forecasting methods often oversimplify the process and fail to guide actual CCS projects in the right direction. This study takes a specific block in Shenhua, China as an example. The relative permeability of CO2 and brine is measured experimentally, and a multi-field coupling CO2 storage prediction model is constructed, focusing on analyzing the sealing ability of the block from the perspective of injection modes. The results show that when injected at a constant speed, the average formation pressure and wellbore pressure are positively correlated with the CO2 injection rate and time; when the injection rate is 0.5 kg/s for 50 years, the average formation pressure increases by 38% and the wellbore pressure increases by 68%. For different injection modes, the average formation pressures of various injection methods are similar during injection. Among them, the pressure increases around the well in the decreasing injection mode is the smallest. The CO2 concentration around the wellbore is the largest, and the CO2 diffusion range continues to expand with injection time. In summary, formation pressure increases with the increase in injection rate and injection time, and the decreasing injection mode has the least impact on the increase in formation pressure. The CO2 concentration is the largest around the well, and the CO2 concentration gradually decreases. The conclusion helps determine the geological carrying capacity of injection volumes and provides insights into the selection of more appropriate injection modes. Accurate predictions of CO2 storage capacity are critical to ensuring project safety and monitoring potentially hazardous sites based on reservoir characteristics.

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Quantitative structure‐property relationshiptechniques for predicting carbon dioxide solubility in ionic liquids using machine learning methods

Benmouloud,

Euldji,

Si‐Moussa

et al. 2024

Int J of Quantum Chemistry

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Ionic liquids (ILs) are considered unique and attractive types of solvents with great potential to capture carbon dioxide (CO2) and reduce its emissions into the atmosphere. On the other hand, carrying out experimental measurements of CO2 solubility for each new IL is time‐consuming and expensive. Whereas, the possible combinations of cations and anions are numerous. Therefore, the preparation and design of such processes requires simple and accurate models to predict the solubility of CO2 as a greenhouse gas. In the present study, two different models, namely: artificial neural network (ANN) and support vector machine optimized with dragonfly algorithm (DA‐SVM) were used in order to establish a quantitative structure–property relationship (QSPR) between the molecular structures of cations and anions and the CO2 solubility. More than 10 116 CO2 solubility data measured in various ionic liquids (ILs) at different temperatures and pressures were collected. 13 significant PaDEL descriptors (E2M, MATS8S, TDB6I, TDB1S, ATSC4V, MATS8M, ATSC7V, Gats2S, Gats5S, Gats5C, ATSC6V, DE, and Lobmax), temperature and pressure were considered as the model input data. For the test set data (2023 data point), the estimated mean absolute error (MAE) and R2 for the ANN model are of 0.0195 and 0.9828 and 0.0219 and 0.9745 for the DA‐SVM model. The results obtained showed that both models can reliably predict the solubility of CO2 in ILs with a slight superiority of the ANN model. Examination of sensitivity and outlier diagnosis examinations confirmed that the QSPR model optimized using the ANN algorithm is better suited to correlate and predict this property.

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Experimental measurements of CO2 solubility, viscosity, density, sound velocity and evaporation rate for 2-(2-aminoethoxy)ethanol (DGA) + 1-methylpyrrolidin-2-one (NMP) / water + ionic liquid systems

Cited by 9 publications

References 62 publications

Investigation of the Solubility of Methane and Ethane in Hybrid Sweetening Solutions of 2-Aminoethanol and 1-Methylpyrrolidin-2-one/Water

Investigation of the Solubility of Methane and Ethane in Hybrid Sweetening Solutions of 2-Aminoethanol and 1-Methylpyrrolidin-2-one/Water

A Case Study on the CO2 Sequestration in Shenhua Block Reservoir: The Impacts of Injection Rates and Modes

Quantitative structure‐property relationshiptechniques for predicting carbon dioxide solubility in ionic liquids using machine learning methods

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