Solubility Of H2S Research Articles

Exploring the Efficiency of Caprylic Acid and Quaternary Ammonium Salt-Based Deep Eutectic Solvents for Separation of CO2 and H2S from Gas Mixtures Using Molecular Dynamics Simulations and COSMO-RS

In the present study, quaternary ammonium salts (QAS) and caprylic acid based deep eutectic solvents (DES) were employed for the separation of CO2 and H2S from natural gas (NG). To understand the extraction mechanisms of H2S from NG, we utilized MD simulations to understand intermolecular interactions between the gases and the eutectic solvents. Our detailed analysis for better understanding of QAS absorption capability in H2S extractions included combined distribution functions (CDFs), which encompass radial distribution functions (RDFs), angular distribution functions (ADFs), hydrogen-bonding networks, density profiles, spatial distribution functions (SDFs), and the non-bond energies between H2S and the DES components, all measured at 310 K. Additionally, we calculated the solubility of H2S and CO2 gases as well as the solubility selectivity and diffusivity selectivity parameters to evaluate the performance of the QAS-based DES in sweetening processes of NG. The results represent that eutectic solvents based on quaternary ammonium chloride are effective for H2S adsorption and show selectivity for H2S in gas mixtures. Furthermore, the COSMO-RS model was used to predict the solubility of various gases (H2S/CO2) in the QAS-based DES, providing further insights into their effectiveness.

An interpretable surrogate model for H2S solubility forecasting in ionic liquids based on machine learning

Here we investigated four different ML-based models, i.e., gaussian process regression (GPR), extreme gradient boosting (i.e., XGBoost), random forest (RF), and support vector machine (SVM), for predicting the solubility of H2S in various ionic liquids (ILs). The dataset was divided into training and testing sets in an 80:20 ratio while the model performance for all models were evaluated using the coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE). Overall, all models effectively predicted H2S solubility, albeit with varying degrees of performance. The GPR provides the best performance, with R2 of 0.9918, MAE of 0.0090, and RMSE of 0.0147. Following this is the XGBoost model with an R2 value of 0.9827, MAE of 0.0155, and RMSE of 0.0213. The RF model displayed slightly lower performance, with an R2 value of 0.9395, MAE of 0.0261, and RMSE of 0.0398 while the lowest performance was demonstrated by the SVM model, which gave an R2 value of 0.9036, MAE of 0.0402, and RMSE of 0.0508. We used SHAP analysis and identified the pressure, temperature, Estate_VSA3, Estate_VSA5, and MinEStateIndex as the top five dominant input features in our model interpretation. In a nutshell, this work presents new insights into the molecular characteristics that affect the solubility of H2S in ILs, paving future research path in this field.

Experimental study of hydrogen sulfide (H2S) behavior in brine/n-decane mixtures under HPHT conditions

This research investigates the dynamic behavior of hydrogen sulfide (H2S) under oil reservoir conditions, focusing on their interplay within both aqueous and organic phases. Surprising findings emerge, notably the heightened solubility of H2S at 250°C compared to 150°C, with values of 19.9 mg to 41.5 and 12.8 mg to 16.4 mg in 100ml of solution, respectively, diverging from conventional expectations, due to organosulfur compounds generated at the water/n-decane interface under high pressure and temperature conditions. Through an examination of Henry's Law and the calculation of Henry's constants across several temperatures, insights into these observations are gained. In the organic phase, temperature is observed to catalyze the formation of organosulfur compounds from n-decane and H2S. Notable compounds identified include aromatic hydrocarbons bearing sulfur substituents. highlighting the presence of 2-Propyldibenzothiophene (2 – 392 mg/mL), which represents between 57 and 95% of the total concentration of organosulfur compounds found in the organic fraction, being more abundant at 250°C. These findings underscore the intricate interplay between temperature, pressure, and phase composition, elucidating the nuanced solubility patterns and reaction dynamics of sulfur and organosulfur compounds.

Efficient, selective and reversible capture of hydrogen sulfide by [Emim]Cl-Acetamide deep eutectic solvents

There is a particular demand to explore low-volatility and structurally tunable absorbents for efficiency, selectivity and reversibility in capturing H2S. For the first time, the performance of deep eutectic solvents (DESs) composed of 1-ethyl-3-methylimidazolium chloride ([Emim]Cl) and acetamide (AA) were examined as physical absorbents for H2S capture. The physical properties of [Emim]Cl-AA DESs, and solubilities of both H2S and CO2 in them were measured. Relevant experimental results demonstrated that the solubilities of H2S in [Emim]Cl-AA DESs (1.1 mol/kg at 298.2 K and 1.023 bar) significantly exceed those of CO2 (0.040 mol/kg at 298.2 K and 1.027 bar). [Emim]Cl-AA DESs exhibit higher H2S solubilities and superior ideal H2S to CO2 selectivities (e.g., the ideal H2S/CO2 selectivity of [Emim]Cl-AA (1:0.5) is 28.5 at 298.2 K) than those physical absorbents ever reported. The recyclability of [Emim]Cl-AA DESs for H2S selective capture was also evaluated, which was found to be very stable in ten continuous absorption and regeneration cycle experiments. The mechanism of H2S capture by [Emim]Cl-AA DESs was finally illustrated at the molecular level with the support of theoretical calculations.

Prediction of solubility of CO2, H2S, and their mixture in ionic liquids using the Cubic Two State equation of state

In this work, the capability of the Cubic Two State (CTS) equation of state (EoS) has been evaluated using the solubility of carbon dioxide (CO2), hydrogen sulfide (H2S), and their mixture in ionic liquids (ILs). The imidazolium-based ILs with [BF4], [PF6], and [Tf2N] anions have been studied. The self-association between IL molecules, CO2, and H2S molecules has been considered to optimize the pure model parameters. In addition to self-association between similar molecules, the cross-association between CO2-IL and H2S-IL in the binary mixtures has been considered. The results show that the CTS EoS can predict (kij=0.0) the solubility of H2S and CO2 in ILs ranging from 1 to 1000 bar satisfactory. The average ARD value for binary CO2-IL and H2S-IL systems has been obtained 20.3 % and 9.02, respectively. The CTS model has been used to predict the phase behavior of ternary systems containing CO2H2S-[C4mim][PF6], CO2H2S-[C8mim][PF6], and CO2H2S-[C8mim][Tf2N] at various temperatures. Finally, the CTS results have been compared to soft-SAFT and PC-SAFT EoSs. The results show that simple association contribution and the cubic term of the CTS EoS can model the molecular interactions between gases and ILs satisfactory. The CTS model can be considered as a robust and efficient thermodynamic model for the prediction of separation of CO2 and H2S using ILs.

Proposing novel predictive group and atomic contribution models for hydrogen sulfide absorption by Deep Eutectic Solvents

Hydrogen sulfide (H2S) is one of the most dangerous impurities of natural gas which cause human and environmental issues. Thus, the main process of gas sweetening plants is H2S removal from natural gas. Amine solutions are the commonly used solvents for gas-sweetening processes in petroleum industries. However, amin solutions are not safe and cause many environmental issues especially in the post-process treatment of used amine. Thus, the issue of proposing green sustainable solvents for gas sweetening is vital for petroleum industries. Deep Eutectic Solvents (DESs) are the most recently introduced green solvents which have shown good capability for H2S absorption. Thus, DESs are one of the most possible candidates for green solvents to replace amine solutions. Experimental studies to choose suitable solvents is a tough challenge because working with H2S is very dangerous and requires expensive facilities. Therefore, an accurate and global thermodynamic model is necessary to predict the solubilities of H2S in DESs without the requirement of experimental data. This study for the first time in open literature, proposes two accurate and global thermodynamic models of group contribution (GC) and atomic contribution (AC) for predicting the H2S solubilities in various nature DESs. The largest and most updated data bank for H2S solubility in DESs was developed from open literature, including 415 solubility data of 37 different nature DESs. The proposed GC and AC models were developed according to the gathered data bank and their results were analyzed by statistical parameters. Both GC and AC models show normal behavior and promising results concerning experimental data by the calculated AARD% of 9.64, and 12.86, respectively.

A comparative study on the solubility of CH3SH and H2S in imidazolium-based ionic liquids: A connectionist approach between free volume and thermodynamics

Sulfur contaminants in industrial gas streams, such as hydrogen sulfide and mercaptans, must be eliminated due to safety and environmental considerations. Ionic liquids, as a new class of chemical compounds, are an alternative to conventional aqueous alkanolamine solutions currently used in absorption gas treatment processes. In this work, the solubilities of methyl mercaptan (CH3SH) and hydrogen sulfide gases in 1-butyl-3-methylimidazolium-based ionic liquids with tetrafluoroborate ([C4mim][BF4]), hexafluorophosphate ([C4mim][PF6]), trifluoromethanesulfonate ([C4mim][OTf]), and bis(trifluoromethylsulfonyl)imide ([C4mim][Tf2N]) anions have been studied using molecular dynamics (MD) simulation and a recently developed OPLS all-atom (OPLS-AA-0.8) force field. A new concept, the induced free volume, has been introduced in this work, which provides a realistic and precise connection between the thermodynamic entropic contributions to the dissolution process of CH3SH and H2S in the ionic liquids, on one hand, and the microscopic free/void volume induced as a result of the entrance of a gas solute molecule into the liquid structure, on the other hand. The thermodynamic energetic contributions were correlated to the CH3SH/H2S interaction with the ionic species of the ionic liquids. Quantum chemical energy decomposition analysis (EDA) was employed to calculate and analyze the binding interaction and nature of CH3SH/H2S interactions with the ionic species of ionic liquids. It was found that the van der Waals contributions to the interaction of CH3SH with ionic liquids are more significant compared to that of H2S, while the opposite conclusion could be deduced for the corresponding electrostatic contributions. Both CH3SH and H2S established equivalent hydrogen bonding interactions with the ionic liquids studied in this work. The diffusion coefficients of the ionic species, as well as the excess chemical potentials and Henry’s constants for the dissolution of CH3SH and H2S in the ionic liquids, were calculated by free energy perturbation technique (FEP) and compared with the MD simulated and experimental data, reported in the literature. It was concluded that the OPLS-AA-0.8 force field yields Henry’s constants and diffusivities that are in better agreement with the reliable experimental data corresponding to other OPLS versions reported to date.

Solubility of H2S-CH4 mixtures in calcium chloride solution: Insight from molecular dynamics simulations

This study uses equilibrium molecular dynamics (EMD) simulations to gain microstructural insight into and predict crucial properties of gas-brine mixtures affecting sour gas reservoir development. The effects of pressure, temperature, gas composition and salinity on the solubility and density of H2S-CH4 mixtures in pure water and CaCl2 brine were investigated at industrially relevant conditions (temperature range of 280 − 340 K, pressures up to 20 MPa, and a salinity range of 4.78 − 17.32 wt%). The force fields used in the MD simulations were validated using experimental data for pure H2S and CH4. The results showed that the solubility of pure H2S and CH4 in pure water increases with pressure, with the latter having a higher solubility. For H2S-CH4 mixtures, the solubility of H2S increased while that of CH4 fell with increasing H2S mole fraction, with the solubilities of the two gases intersecting at an H2S mole fraction of 0.28. Further, the solubility of H2S shows a greater pressure dependence than that of CH4, and H2S gas tends to reach saturation in pure water. In calcium chloride solution, the gas solubility decreases as the ions reduce the interaction between water and gas molecules. The solubility of H2S gas is a stronger function of the ion concentration compared with CH4, and increases 6-fold as the H2S mole fraction increases from 0.5 to 0.8. The overall solubility ranges were 0.45 to 3.48 mol/kg for H2S and 0.15 to 0.25 mol/kg for CH4.

Absorption characteristics and molecular mechanism of a low viscosity iron-based ionic liquid for removing H2S

Aiming at the problem of by-product salt and volatile solvent component in industrial liquid redox process of H2S removal. A new absorbent, a 1-butyl-3-methylpyridine iron-based ionic liquid (rFeCl3/[BMP]Cl) with three iron-pyridine ratios (r=0.6, 0.8, and 1.0), was synthesized. The physicochemical properties and H2S solubility of rFeCl3/[BMP]Cl were measured and modeled. The molecular mechanism of chemical absorption of H2S by iron-based ionic liquids was explained from the interaction energy, reduced density gradient (RDG) and atoms in molecules (AIM) topology analysis, and standard reaction equilibrium constant by quantum chemical calculation. It was found that rFeCl3/[BMP]Cl have low viscosity, high solubility, and good thermal stability. Its Bronsted acidity avoids by-product salts produced in the absorption of H2S. The hydrophobicity makes the ionic liquid not diluted by the generated water during the absorption. The results of quantum chemical calculations show that rFeCl3/[BMP]Cl-H2S has moderate intermolecular interaction and large reactivity, which is consistent with the experimental results of the Henry's coefficient and reaction equilibrium constant.

Modeling H2S solubility in aqueous MDEA, MEA and DEA solutions by the electrolyte SRK-CPA EOS

In this study, an electrolyte cubic plus association equation of state (e-CPA EOS) has been proposed to predict the vapor–liquid equilibrium of (H2S) in aqueous solutions of monoethanolamine (MEA), diethanolamine (DEA), and methyldiethanolamine (MDEA). This EOS is composed of repulsive forces, short-range interactions, short-range ionic interactions, association term, long-range ionic interactions, and Born term. The Soave– Redlich– Kwong EOS is used as a non-electrolyte part. A new iterative procedure based on the Jacobi method is introduced to obtain the compositions of all species in the liquid phase. The genetic algorithm (GA) is used to find the optimal values of binary interaction coefficients between molecules and ions. Compared with experimental data, the e-CPA EOS model successfully describes the vapor–liquid equilibrium of H2S in the aqueous solutions of MEA, DEA, and MDEA. The average absolute deviations for 313 data of MEA-H2S-H2O, 156 data of DEA-H2S-H2O, and 145 data of MDEA-H2S-H2O systems were obtained as 8.20 %, 8.04 %, and 9.41 %, respectively. In addition, for some similar cases, the capability of the e-CPA EOS was compared with the Clegg–Pitzer, N-Wilson-NRF, e-NRTL, and e-CTS models. The results indicated that the e-CPA EOS has less error than the four other models.

Double H-bonds multimer absorbent design for H2S absorption

A double H-bonds multimer absorbent for hydrogen sulfide (H2S) absorption was designed via intermolecular self-assembly using 1,8-Diazabicyclo-[5.4.0]-undec-7-ene (DBU) and ethylene glycol (EG) under the guidance of quantum chemical calculation (QCC). The formation mechanisms of multimer absorbents and the absorption mechanisms between those absorbents and H2S were explored by QCC and experiments. It was found that the formed multimer absorbent at the DBU/EG molar ratio of 1:2 has two intermolecular H-bonds with different strengths between DBU and EG, which can combine with H2S via strong intermolecular forces. Furthermore, the characteristics analysis of multimer absorbents and complexes confirmed the above mechanisms. Experimental results indicated that the DBU-2EG has a higher H2S solubility of 5.8 mol/kg multimer absorbent with a low viscosity value of 15.12 mPa·s at 25 °C and better regeneration performance. The multimer absorbent exhibits great potential in the H2S capture process.

Highly efficient capture and removal of H2S by multi-amine functionalized ionic liquids

With the increasing awareness of environmental protection, H2S removal in natural gas has attracted more attention. In this study, three multi-amino functionalized ionic liquids (MFILs) were prepared with a one-step reaction. The solubility of H2S was measured at temperatures of 298.2 K to 328.2 K. Among them, diethylenetriamine imidazole ([DETAH][Im]) presented the unprecedented H2S solubility of 7.82 mol/kg (1.34 mol/mol) at 298.2 K and 0.1 bar H2S partial pressure, surpassing all the reported absorbent under the experimental condition. The H2S removal ability was determined with the interference of CO2, and the highest H2S removal efficiency reached 99.32% during four-hour absorption. The mechanism was elucidated by NMR, FT-IR, and DFT calculation. Moreover, five consecutive absorption–desorption cycles were performed to evaluate the regeneration efficiency. These MFILs represent apparent viscosity and absorption performance superiority over previously reported absorbents. These MFILs are a class of promising absorbents for sweetening natural gas.

Absorption characteristics, model, and molecular mechanism of hydrogen sulfide in morpholine acetate aqueous solution

Absorption characteristics, model, and molecular mechanism of hydrogen sulfide in morpholine acetate aqueous solution

Molecular simulations of hybrid cross-linked membranes for H2S gas separation at very high temperatures and pressure: Binary 90%/10% N2/H2S and CH4/H2S, ternary 90%/9%/1% N2/CO2/H2S and CH4/CO2/H2S mixtures

Molecular dynamics (MD) simulations have previously identified four hybrid inorganic-organic membranes based on POSS or OAPS silsesquioxanes hyper-cross-linked with small PMDA or 6FDA imides, which are able to maintain reasonable CO2/N2 and CO2/CH4 permselectivities at very high temperatures (300 °C and 400 °C) and pressure (60 bar). Experimentally, the polyPOSS-imides are known to degrade above 300 °C while the polyOAPS-imides can resist up to above 400 °C. In the present work, the same four model polyOAPS/POSS-imide networks are further tested for their gas separation abilities of H2S-containing mixtures. Indeed, hydrogen sulfide is a hazardous gas present in many gas feeds, and, within the context of a toxic penetrant under harsh conditions, simulations are a useful task to perform before embarking on difficult experiments.The separations of H2S with respect to N2, CH4 and CO2 by the polyOAPS/POSS-imide matrices were studied at 300 °C, 400 °C and at 60 bar, firstly with H2S as a single-gas in order to obtain its ideal permselectivities, secondly as part of binary 90%/10% N2/H2S and CH4/H2S feeds and thirdly as part of ternary 90%/9%/1% N2/CO2/H2S and CH4/CO2/H2S feeds. They were compared to separations of binary 90%/10% N2/CO2 and CH4/CO2 feeds under exactly the same conditions.At 300 °C, H2S is much more soluble in the networks than the other three penetrants. It is the only one leading to a non-negligible volume swelling at 60 bar, although this does not happen for the mixed-gas feeds due to their low H2S partial pressures. Differences are attenuated at 400 °C because of the decrease in solubilities upon heating. The linear N2 and CO2 move faster than the non-linear CH4 and H2S penetrants, but the diffusion selectivities are moderate. As such, the ideal permselectivities under harsh conditions are mainly governed by the solubility selectivities. With binary 90%/10% N2/H2S, CH4/H2S, N2/CO2 and CH4/CO2 feeds, the transport parameters of the major N2 or CH4 components remain similar to their ideal values, whereas the solubilities of the minor H2S and CO2 components increase. This leads to some of the real separation factors for H2S being different from their ideal permselectivities, and approximately twice as high as those with CO2. In the ternary 90%/9%/1% N2/CO2/H2S and CH4/CO2/H2S mixtures, replacing 1% CO2 by 1% H2S in the feeds leads to small changes but, in pratice, these are not significant enough to make a difference. Under the conditions tested, the ternary separation factors are the same than for the 90%/10% binary mixtures.In all cases, the denser polyPOSS-imides show better sieving properties than the more open polyOAPS-imides. As such, the former should preferably be used in applications up to 300 °C, i.e. in the temperature range below their degradation. However, it is also possible to use the polyOAPS-imides at higher temperatures, since they still manage maintaining separation factors between 2 and 6 for CO2 and H2S at 400 °C, which is outstanding for polymer-based membranes at such high temperatures.

Quality conversion of H2S into β-mercaptopropionic acid by CETSA-based ionic liquid

With respect to the detrimental hydrogen sulfide (H2S), a whole new range of hydrophilic ionic liquids (ILs) could conveniently catalyze into more widely needed chemical reagents. ILs could be beneficial to increase the solubility and ionization of H2S, resulting in the Michael addition reaction with acrylic acid to produce β-mercaptopropionic acid. In this study, four kinds of hydrophilic ILs were synthesized by using carboxyethiosuccinic acid (CETSA), which contains three carboxyl groups with different chemical properties, as anions and combined with basic cations. The effect of the structure and reaction conditions of ILs on the catalytic activity of the system was studied. The result showed that the CETSA-based ILs with N, N, N′, N' -tetramethyl-1, 6-hexamethylenediamine (TMHDA) as cation had the best catalytic effect. ILs catalyst can greatly improve the selectivity and yield of the target product in addition reaction, which could be used for eight times at least without a noticeable decrease in its activity and conversion. In the absence of H2S cylinders, the conversion of acrylic acid can reach 99.21%, and the selectivity and yield of mercaptopropionic acid can reach 92.57% and 91.84% with [TMHDAH]CETSA. The ILs was characterized by FTIR, 1H NMR, 13C NMR and MS in order to determine the structure of the ILs. The thermal stability of ILs in the reaction system was observed by TG and DSC, and the ionization of ILs in solvent was measured by pH meter.

Solubilities of CO2, CH4, C2H6, CO, H2, N2, N2O, and H2S in commercial physical solvents from Monte Carlo simulations

ABSTRACT The removal of acid gas impurities from synthesis gas or natural gas can be achieved using several physical solvents. Examples of solvents applied on a commercial scale include methanol (Rectisol), poly(ethylene glycol) dimethyl ethers (Selexol), n-methyl-2-pyrrolidone (Purisol), and propylene carbonate (Fluor solvent). Continuous Fractional Component Monte Carlo (CFCMC) simulations in the osmotic ensemble were used to compute the Henry coefficients of the pure gases CO, CH, CH, CO, H, N, NO, and HS in the aforementioned solvents. The predicted Henry coefficients are in good agreement with the experimental results. The Monte Carlo method correctly predicts the gas solubility trend in these physical solvents, which obeys the following order: HS > CO > CH > CH > CO > N > H. The gas separation selectivities for the precombustion process and the natural gas sweetening process are calculated from the pure gas Henry coefficients. The CO/NO analogy is verified for the solubility in these solvents.

A promising artificial intelligence-based tool to simulate the efficient and sustainable hydrogen sulfide elimination using deep eutectic solvents

This work applies artificial intelligence (AI) methodologies and relevance tests to investigate the hydrogen sulfide (H2S) elimination capacity of a wide range of DESs (deep eutectic solvents). A great deal of effort is made to deploy a practical model to predict the H2S removal ability of eighteen different DESs as a function of DES chemistry, equilibrium conditions, and H2S-DES interaction. Multiple linear regression and Pearson’s correlation methods are employed to measure the direction and relative influence of hydrogen bond acceptor (HBA), hydrogen-bond donor (HBD), the HBA and HBD concentration, water dose, pressure, temperature, and absorption enthalpy on the DES capacity to absorb H2S molecules. Both tests approve that absorption enthalpy (ΔH) of H2S by DESs, hydrogen bond acceptor (HBA), pressure, and temperature mainly control the considered separation process. The relevance tests also identify that the H2S solubility in DESs improves by either a decrease in ΔH, HBA molecular weight, and temperature or an increase in pressure. Then, five diverse AI types are applied to estimate H2S molality in DESs as a function of the involved explanatory variables, and their accuracy is compared. The sensitivity analysis clarifies that the cascade neural network (CNN) with only 20 hidden nodes is the most reliable AI tool to simulate the considered problem. Further investigations approve that the CNN tool provides more accurate predictions for H2S solubility in DESs when it is equipped with the logarithm and tangent sigmoid transfer functions in the hidden and output neuronic layers. Also, amongst eleven checked training algorithms, the Levenberg-Marquardt presented the best performance. This structure-regulated CNN tool can predict 512 actual H2S solubility records in DESs with the MSE = 0.0031, MAE = 0.02, RAE = 2.03%, AARE = 3.03%, and multiple-R = 0.99943.

An insight into the analogy between solute-solvent binding energy and solubility of acid gases in ionic liquids: Thermodynamic modeling versus molecular dynamic simulation

Ionic Liquids (ILs) have emerged as a promising generation of solvents for the absorption of acid gases (e.g., CO2 and H2S) due to their unparalleled physiochemical properties. This study focuses on thermodynamic modeling and molecular dynamic simulation approaches to estimate the solubility and interaction energies of CO2 and H2S gases in/with different frequently-used ILs. For thermodynamic modeling, the GE/EOS method was employed. This method allows for combining activity-coefficient models in the structure of the cubic equation of states. In the GE/EOS method, the modified Peng-Robinson equation of state (MPR2) together with the LCVM mixing rules was used. Excess Gibbs free energy models of Wilson, NRTL, and UNIQUAC were also applied for combination with the GE/EOS models. The prediction results of the combined models were compared with the experimental solubility data. The results demonstrated the capability of these models to predict the thermodynamic behavior of the acid gas-ILs systems. The results uncovered that the MPR2-LCVM-Wilson model can tabulate the highest correlation with the experimental data compared to the other model combinations. Results of the sensitivity analysis on the principal operational variables (temperature and pressure), showed superior effect of pressure on the gas solubility. In addition, the results of the molecular dynamic (MD) simulation disclosed an agreement between the trends of the solubility of acid gases in ILs with those of the released interaction energies of acid gases absorbed by the ILs. MD results also confirmed that the solubility of acid gases in ILs increases with an increase in the binding energy of the molecules with the ILs.

Optimizing Sour Gas Qualification Testing—Modeling the Effects of Temperature and Total Pressure on H2S Fugacity, Activity, and Solubility Coefficients up to 138 MPa and 204°C

Traditionally, the sour severities of high-pressure high-temperature (HPHT) oil and gas production wells were assessed by H2S partial pressure (PH2S): The mole fraction of H2S in the gas (yH2S) multiplied by the total pressure (PT). However, PH2S usually over-predicts the actual sour severity of HPHT systems, leading to suboptimal material selection choices. To reflect recent advances in thermodynamic modeling and to avoid over-conservatism, after careful deliberation, ANSI/NACE MR0175-2021/ISO 15156-2:2022 recently expanded the number of sour severity metrics to four: PH2S, fugacity (fH2S), chemical activity (aH2S), and dissolved concentration (CH2S) of the aqueous phase. The new metrics are often computationally derived and account for thermodynamic nonidealities, which are significant at HPHT conditions. Regardless of the preferred metric, quantifying the sensitivity of each metric to a wide range of temperatures and total pressures is critical when conducting H2S service assessments. In this article, the effect of increasing temperature and total pressure on the thermodynamically derived apparent H2S solubility (KH2S = CH2S/PH2S) was investigated. KH2S is a critical parameter for quantifying changes in H2S phase behavior/sour severity of HPHT systems. Apparent KH2S values were calculated by two different thermodynamic models and benchmarked to two publicly available H2S/H2O datasets up to 120°C and 10.3 MPa equilibrated in a brine containing 165,000 mg/L Cl−. The model that provided the best match to the experimental data was later used in a much broader thermodynamic sensitivity study of the H2S/CH4/H2O/NaCl “oilfield” system. For this sensitivity analysis, changes in fH2S, aH2S, CH2S, and KH2S were individually modeled between 4°C and 204°C, at total pressures up to 138 MPa, and in brines containing up to 25 wt% NaCl (180,000 mg/L Cl−). Lastly, a comparison of the predicted sour severity by pseudo-PH2S, fH2S, and CH2S metrics, over the same temperature and total pressure parameter space, is presented.

Modeling of H2S solubility in ionic liquids: comparison of white-box machine learning, deep learning and ensemble learning approaches

In the context of gas processing and carbon sequestration, an adequate understanding of the solubility of acid gases in ionic liquids (ILs) under various thermodynamic circumstances is crucial. A poisonous, combustible, and acidic gas that can cause environmental damage is hydrogen sulfide (H2S). ILs are good choices for appropriate solvents in gas separation procedures. In this work, a variety of machine learning techniques, such as white-box machine learning, deep learning, and ensemble learning, were established to determine the solubility of H2S in ILs. The white-box models are group method of data handling (GMDH) and genetic programming (GP), the deep learning approach is deep belief network (DBN) and extreme gradient boosting (XGBoost) was selected as an ensemble approach. The models were established utilizing an extensive database with 1516 data points on the H2S solubility in 37 ILs throughout an extensive pressure and temperature range. Seven input variables, including temperature (T), pressure (P), two critical variables such as temperature (Tc) and pressure (Pc), acentric factor (ω), boiling temperature (Tb), and molecular weight (Mw), were used in these models; the output was the solubility of H2S. The findings show that the XGBoost model, with statistical parameters such as an average absolute percent relative error (AAPRE) of 1.14%, root mean square error (RMSE) of 0.002, standard deviation (SD) of 0.01, and a determination coefficient (R2) of 0.99, provides more precise calculations for H2S solubility in ILs. The sensitivity assessment demonstrated that temperature and pressure had the highest negative and highest positive affect on the H2S solubility in ILs, respectively. The Taylor diagram, cumulative frequency plot, cross-plot, and error bar all demonstrated the high effectiveness, accuracy, and reality of the XGBoost approach for predicting the H2S solubility in various ILs. The leverage analysis shows that the majority of the data points are experimentally reliable and just a small number of data points are found beyond the application domain of the XGBoost paradigm. Beyond these statistical results, some chemical structure effects were evaluated. First, it was shown that the lengthening of the cation alkyl chain enhances the H2S solubility in ILs. As another chemical structure effect, it was shown that higher fluorine content in anion leads to higher solubility in ILs. These phenomena were confirmed by experimental data and the model results. Connecting solubility data to the chemical structure of ILs, the results of this study can further assist to find appropriate ILs for specialized processes (based on the process conditions) as solvents for H2S.