Gas solubilities of nitrogen or oxygen in benzene, divinylbenzene, styrene and of an equimolar (N2:O2) mixture in styrene at (293–313) K

Tsuji, T.; Ohya, Kohei; Lai, Andrea Jia Xin; Manaf, Norhuda binti Abdul; Hoshina, Takuya; Oba, Shigeo

doi:10.1016/j.fluid.2019.03.016

Cited by 14 publications

(6 citation statements)

References 23 publications

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“…PR / PRSV equation showed good reproducibility not only for N2 and O2 solubility in styrene but also for N2 solubility in MMA [7,8]. Table 1 lists the parameters for N2 and MMA for PR / PRSV equation.…”

Section: Correlation For N2 Solubility In Mmamentioning

confidence: 97%

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Peng-Robinson Cubic Equation of State Based on Key Group Contribution and Calculation of Nitrogen Gas Solubility in MMA Dimer

Mohamed

Chong

Lai

et al. 2021

ARFMTS

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Previously authors have reported facts that nitrogen (N2) and oxygen solubilities in styrene is the same as those in benzene and divinylbenzene at 303 K. Though the three compounds have an atomic composition, (CH)n (n=6, 8 and 10), the gas solubilities are thought to depend on the number of aromatic carbons in the solution. Then, authors named it ‘a key group in solubility’. In this research, the key group was investigated for N2 solubility in methyl methacrylate (MMA) and its dimer, ethylene glycol dimethacrylate (EGDMA). Therefore, the calculations were carried out by Peng-Robinson (PR) equation of state based on group contribution methods. The experimental data employed were those of Lai et al., where N2 solubility are reported in MMA at 303 K. The N2 solubility in EGDMA was assumed to be double of that in MMA at 303 K, because EGDMA has two MMA units in the molecule. Two types of group contribution methods were proposed to calculate N2 solubility in EGDMA. One was for the critical temperature and pressure proposed by Joback and Reid. Using these properties, the attractive and excluded volume parameters in PR equation were evaluated for EGDMA. Other was similar to a method proposed by Orbey and Sandler. The excluded volume parameter in PR equation can be evaluated from those of MMA by multiplying the number of repeating units, and the attractive by multiplying the squared number. Instead of the method, the powers were proposed to be 3/4 and 3/2 for the excluded volume and attractive perimeters, respectively. The powers were come from a scaling theory by de Gennes. The binary parameter for N2 – EGDMA was also set to k12 = 0.224, which was the same as that for N2 –MMA. The calculated N2 solubility in EGDMA was far smaller than the hypothetical N2 solubility in EGDMA at 303 K. Otherwise, to reproduce the hypothetical N2 solubility, a quite different value, k12 = -0.044, was necessary for the method by Joback and Reid. The results suggested that a key group for gas solubility will not be accepted in MMA.

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Section: Correlation For N2 Solubility In Mmamentioning

confidence: 97%

“…For the design of the polymerization process, gas solubility data are necessary. In the previous research, the authors have reported N2 and O2 solubility in benzene, styrene and divinyl benzene at (293-303) K [7].…”

Section: Introductionmentioning

confidence: 99%

Peng-Robinson Cubic Equation of State Based on Key Group Contribution and Calculation of Nitrogen Gas Solubility in MMA Dimer

Mohamed

Chong

Lai

et al. 2021

ARFMTS

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“…This nding can be explained that the C-O bonds are more thermally stable than the C]O bonds. 58,59 The formation of the oxygen functional groups on the CNP surface during SPP could be attributed to two possible causes: (i) the interaction between reactive carbon species and oxygen dissolved in benzene during synthesis 60,61 and (ii) surface exposure to ethanol and air during washing and drying processes.…”

Section: Surface Composition and Chemical Bonding Statesmentioning

confidence: 99%

Introducing micropores into carbon nanoparticles synthesized via a solution plasma process by thermal treatment and their charge storage properties in supercapacitors

et al. 2023

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“…Despite its satisfactory accuracy for gas solubility in lighter n-alkanes, the SRK EOS typically produces significantly poorer results than the PC-SAFT EOS 44 . Tsuji et al 45 investigated N 2 and oxygen gas solubilities in benzene, divinylbenzene, and styrene. For a particular isotherm, gas solubility in liquids had a linear pressure dependency and declined with rising temperature.…”

Section: Introductionmentioning

confidence: 99%

“…For a particular isotherm, gas solubility in liquids had a linear pressure dependency and declined with rising temperature. Ultimately, PR-EOS was implemented to predict gas solubilities 45 . Aguilar-Cisneros et al 46 determined the solubility of N 2 , CO 2 , and CH 4 in petroleum fluids using the PR-EOS in conjunction with various mixing rules in systems including bitumens, heavy oils, refinery cuts, and coal liquids.…”

Section: Introductionmentioning

confidence: 99%

Modeling of nitrogen solubility in normal alkanes using machine learning methods compared with cubic and PC-SAFT equations of state

Madani

Mohammadi

Atashrouz

et al. 2021

Sci Rep

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Accurate prediction of the solubility of gases in hydrocarbons is a crucial factor in designing enhanced oil recovery (EOR) operations by gas injection as well as separation, and chemical reaction processes in a petroleum refinery. In this work, nitrogen (N2) solubility in normal alkanes as the major constituents of crude oil was modeled using five representative machine learning (ML) models namely gradient boosting with categorical features support (CatBoost), random forest, light gradient boosting machine (LightGBM), k-nearest neighbors (k-NN), and extreme gradient boosting (XGBoost). A large solubility databank containing 1982 data points was utilized to establish the models for predicting N2 solubility in normal alkanes as a function of pressure, temperature, and molecular weight of normal alkanes over broad ranges of operating pressure (0.0212–69.12 MPa) and temperature (91–703 K). The molecular weight range of normal alkanes was from 16 to 507 g/mol. Also, five equations of state (EOSs) including Redlich–Kwong (RK), Soave–Redlich–Kwong (SRK), Zudkevitch–Joffe (ZJ), Peng–Robinson (PR), and perturbed-chain statistical associating fluid theory (PC-SAFT) were used comparatively with the ML models to estimate N2 solubility in normal alkanes. Results revealed that the CatBoost model is the most precise model in this work with a root mean square error of 0.0147 and coefficient of determination of 0.9943. ZJ EOS also provided the best estimates for the N2 solubility in normal alkanes among the EOSs. Lastly, the results of relevancy factor analysis indicated that pressure has the greatest influence on N2 solubility in normal alkanes and the N2 solubility increases with increasing the molecular weight of normal alkanes.

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Gas solubilities of nitrogen or oxygen in benzene, divinylbenzene, styrene and of an equimolar (N2:O2) mixture in styrene at (293–313) K

Cited by 14 publications

References 23 publications

Peng-Robinson Cubic Equation of State Based on Key Group Contribution and Calculation of Nitrogen Gas Solubility in MMA Dimer

Peng-Robinson Cubic Equation of State Based on Key Group Contribution and Calculation of Nitrogen Gas Solubility in MMA Dimer

Introducing micropores into carbon nanoparticles synthesized via a solution plasma process by thermal treatment and their charge storage properties in supercapacitors

Modeling of nitrogen solubility in normal alkanes using machine learning methods compared with cubic and PC-SAFT equations of state

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