Mole Fraction Of Component Research Articles

Process swing adsorption with selective purge gas recirculation (PSA-SPUR): Adsorption process technology optimised for separation of heavy component from a gas mixture and its design for CO2 capture through Equilibrium Theory analysis

PSA-SPUR (Pressure Swing Adsorption with Selective Purge Gas Recirculation) has been developed aimed at separating the most strongly adsorbing component from a gas mixture at high product purity and recovery. The innovative strategy for designing a Pressure Swing Adsorption system features recycling its purge gas stream exiting the column and mixing it back into the feed. This operation enriches the mixed feed with an elevated fraction of the heavy component during the adsorption step, thus enhancing the PSA’s performance greatly. Reusing the purge gas helps significantly increase the product recovery compared to conventional methods where purge gas is simply discarded or taken as a low-quality product. For theoretical analysis of a PSA-SPUR system, a bespoke Equilibrium Theory model was developed and solved successfully, providing valuable insights into the performance of the PSA-SPUR system designed for capturing CO2 from a flue gas. The study revealed that there exists an optimum extent of purging that maximises the heavy component mole fraction in the mixed feed, leading to the best possible feed throughput of the adsorption system. Furthermore, the effects of the desorption pressure and feed composition on the PSA-SPUR system’s performance were investigated. The results indicate that the CO2 capture PSA-SPUR system using commercial zeolite 13X has excellent potential to achieve very high product purity and recovery, being allowed to operate at moderate vacuum pressures without having to compress the flue gas feed, even when the gas feed contains less than 10 mol% CO2.

Thermodynamic analysis of a novel gas separator based on molecular exchange flow

An energy analysis model and several evaluation indexes are established for a novel gas separator employing molecular exchange flow as working principle. The influences of several important factors on energy consumption and thermal efficiency are investigated. As temperature difference increases, both energy consumption and thermal efficiency rise linearly. As Knudsen number increases, total work decreases while minimum separation work and thermal efficiency initially increase and subsequently decrease. When inlet velocity increases, total work increases but minimum separation work and thermal efficiency go down. Furthermore, both energy consumption and thermal efficiency initially rise and then decline with an increasing mole fraction of the lighter molecular weight component. The results indicate that energy consumption and separation performance should be taken into consideration when selecting temperature differences. In addition, it is preferable to choose the Knudsen number corresponding to optimal separation performance and the intermediate value for component mole fraction. Moreover, it had better employ a lower inlet velocity as long as the separation requirements are satisfied. This study presents a method to optimize the performance of the novel separator based on molecular exchange flow from the perspective of energy conversion and utilization.

Ensuring metrological traceability of reference materials of gas mixtures composition

The modern concept of metrological assurance for gas analytical measuring instruments with the use of reference materials of gas mixtures composition in cylinders under pressure is presented. The reference materials of gas mixtures composition of approved type in cylinders under pressure, which are the most often means of mole fraction and mass concentration units transfer in gas analytical measurements, are considered. The certified value in these reference materials is the content of the target component (or components) in the gas medium (analytical matrix). All the produced reference materials of gas mixtures composition, which are used for ensuring the uniformity of measurements are traceable to the State primary standard of units of mole fraction, mass fraction and mass concentration of components in gas and gas condensate media GET 154-2019, which characteristics are confirmed on the international level by the results of about 90 international comparisons. The paper presents a methodology for ensuring metrological traceability of reference materials of gas mixtures composition using GET 154-2019, taking into account the constantly increasing park of gas analytical instruments and the emergence of new measuring tasks in various fields of industry and environmental control. Currently, a park of secondary and working standards has been created at enterprises producing reference materials of gas mixtures composition, and their traceability to GET 154-2019 has been implemented according to the state verification scheme. The paper presents the results of international comparisons with participation of GET 154-2019, confirming the comparability of the obtained and reference value of the target component content in reference gas mixtures at the international level. The variety and large number of relevant gas analytical measurement tasks in various industries and the social sphere determines the need to choose priority areas for improving the existing reference base, including the structure of the GET 154 Standard and the nomenclature of reference gas mixtures. The strategic program of the Gas Analysis working group of the Consultative Committee of the Amount of Substance of the International Bureau of Weights and Measures developed for the period up to 2030 has been analysed and a review of the long-term tasks of gas analytical measurements is given. The currently existing GET 154-2019 Standard of the latest generation provides reproduction, storage and transfer of the components’ mole fraction units in gas and gas condensate media in the range from 1.5·10 –8 to 99.99999 %, and mass concentration units in the range from 1.0·10–6 to 2.0·105 mg/m3, what is confirmed by the results of participation in international comparisons and published CMC positions in the International database of calibration and measurement capabilities (about 400 CMCs positions).

Improved Least Squares Support Vector Machine Model Based on Grey Wolf Optimizer Algorithm for Predicting CO2–Crude Oil Minimum Miscibility Pressure

The minimum miscibility pressure (MMP) is an important reference parameter in the study of CO2 oil drive systems. In response to the problems of time‐consuming and costly prediction of MMP by conventional experimental methods, an improved least squares support vector machine (LSSVM) model based on grey wolf optimizer (GWO) algorithm is proposed to predict the CO2–crude oil MMP. Based on Pearson correlation analysis, reservoir temperature, C5+ molecular weight, intermediate component mole fraction, and volatile component mole fraction are selected as independent variables of the model, and MMP is the dependent variable. A total of 51 MMP experimental data are collected, of which 35 are used to fine‐tune the model's parameters and 16 are used to verify the model's reliability. The high leverage point method is used to detect anomalies in all experimental data to check the reliability of the model, and the abnormality of only one piece of experimental data is identified. Finally, a comparison of the model with other intelligent models is found. The absolute relative deviation of the GWO‐LSSVM model is 2.24% for the training data and 3.48% for the test data, which provides high adaptability and accuracy.

RNN-based CO2 minimum miscibility pressure (MMP) estimation for EOR and CCUS applications

Accurate estimation of minimum miscibility pressure (MMP) is crucial for assessing the efficiency of most miscible and immiscible processes, specifically CO2-based enhanced oil recovery (EOR) methods and Carbon capture utilization and sequestration (CCUS). The experimental procedure for MMP prediction is often time-consuming and costly. On the other hand, the empirical models that have been historically used could work based on limited input parameters, ignore the importance of others and are not necessarily accurate. The novelty of the current study is using an explainable deep-learning approach, Recurrent neural network (RNN), to train a model using a multi-dimensional (22 features) dataset with 544 rows of data. The Dataset comprises mole fractions of injected gas (pure and impure CO2). Out of those features, eight subsets of parameters (labelled X_1 to X_8) were used to develop models. The multi-dimensionality of the dataset makes it suitable to study the effects of various parameters on MMP, specifically in conditions of interest to CCUS-EOR applications. Among the multiple inputs tested, the model trained with X_1 and X_8 input parameters (including mole fraction of different hydrocarbon and nonhydrocarbon components and reservoir temperature) resulted in the most accurate estimations of MMP (R2 = 0.99). To further enhance the explainability of the model, feature importance and shapely values analysis were conducted on the developed models, and the impact of each input feature on MMP was elaborated. Temperature, volatile/intermediate, and nonhydrocarbon components are the most influential parameters depending on the subset of parameters chosen. Moreover, the developed model using X_8 inputs performed significantly better (37 % more accurately) than three well-known empirical models from the literature.

Densities and Viscosities for the Ternary Mixtures of n-Undecane (1) + Butylcyclohexane (2) + 1-Pentanol (3) and Corresponding Binaries at T = (293.15 to 333.15) K

The actual composition is known to be highly responsible for the physical and chemical properties of a fuel. To understand the foundational physical properties of an aviation kerosene substitute mixture for hypersonic aircraft, n-undecane, butylcyclohexane, and 1-pentanol were used to construct a ternary system. The values of density (ρ) and viscosity (η) for the ternary system and three corresponding binaries were measured at temperatures T = (293.15 to 333.15) K and pressure p = 0.1 MPa. The Redlich–Kister equation was used to fit the excess molar volumes (VmE) and viscosity deviations (Δη) of the binary systems, while those of the ternary system were correlated with four semi-empirical formulas (Cibulka, Singh, Redlich–Kister, and Nagata–Tamura equations). The experimental results show that the VmE values of the three binary mixtures have a positive relationship with the mole fraction of nonpolar components, while Δη values have a negative relationship. The non-ideal behavior of mixtures is discussed from the perspective of molecular interactions and structural effects. This work provides data support and guidance for fuel compatibility research.

Error quantification of the Arrhenius blending rule for viscosity of hydrocarbon mixtures

Six hundred and seventy-five measurements of dynamic viscosity and density have been used to assess the prediction error of the Arrhenius blending rule for kinematic viscosity of hydrocarbon mixtures. Major trends within the data show that mixture complexity–binary to hundreds of components—and temperature are more important determinants of prediction error than differences in molecular size or hydrogen saturation between the components of the mixtures. Over the range evaluated, no correlation between prediction error and mole fractions was observed, suggesting the log of viscosity truly is linear in mole fraction, as indicated by the Arrhenius blending rule. Mixture complexity and temperature also impact molar volume and its prediction. However, a linear regression between the two model errors explains less than 20% of the observed variation, indicating that mixture viscosity and/or molar volume are not linear with respect to temperature and/or mixture complexity. Extensive discussion of the intermolecular forces and the geometric arrangement of molecules and vacancies in liquids, which ultimately determines its viscosity, is brought into context with the implicit approximations behind the Arrhenius blending rule. The complexity of this physics is not compatible with a simple algebraic correction to the model. However, sufficient data is now available to determine confidence intervals around the prediction of fuel viscosity based on its component mole fractions and viscosities. At −40°C, when all identified components are pure molecules the modeling error is 13.2% of the predicted (nominal) viscosity times the root mean square of the component mole fractions.

Finite-Time Thermodynamic Modeling and Optimization of Short-Chain Hydrocarbon Polymerization-Catalyzed Synthetic Fuel Process.

The short-chain hydrocarbon polymerization-catalyzed synthetic fuel technology has great development potential in the fields of energy storage and renewable energy. Modeling and optimization of a short-chain hydrocarbon polymerization-catalyzed synthetic fuel process involving mixers, compressors, heat exchangers, reactors, and separators are performed through finite-time thermodynamics. Under the given conditions of the heat source temperature of the heat exchanger and the reactor, the optimal performance of the process is solved by taking the mole fraction of components, pressure, and molar flow as the optimization variables, and taking the minimum entropy generation rate (MEGR) of the process as the optimization objective. The results show that the entropy generation rate of the optimized reaction process is reduced by 48.81% compared to the reference process; among them, the component mole fraction is the most obvious optimization variable. The research results have certain theoretical guiding significance for the selection of the operation parameters of the short-chain hydrocarbon polymerization-catalyzed synthetic fuel process.

A molecular dynamics study on the mechanism of heterogeneous bubble nucleation of mixed liquid

The nucleate boiling of mixed boiling is widely utilized in natural gas, hydrogen liquefaction process, and other fields. In this paper, the molecular dynamics study of heterogeneous bubble nucleation of pure argon liquid and the argon‑krypton mixed liquid on the platinum surface was conducted. The nucleate boiling characteristics were presented and the variations of the density, temperature, nucleation embryo volume, and heat flux were analyzed. The difference in the nucleation mechanism of pure liquid and mixed liquid was explained based on the competition of atomic potential energy and atomic kinetic energy. The effect of the component mole fraction on the bubble nucleation of mixed fluid was also discussed. The results showed that the onset superheat of boiling of argon‑krypton mixed liquid is higher than that of pure argon. The higher the mole fraction of the component with a lower saturation temperature, the lower the onset superheat of the liquid nucleate boiling. When x < 0.5, the growth rate of the nucleation embryo is dominated by the x value, when x > 0.5, the growth rate is dominated by wall temperature. Moreover, the difference in diffusion coefficients of each component is one of the direct causes of determining the growth rate of nucleation embryos. The findings provide insights into the mechanisms of differences in boiling nucleation between mixed liquid and pure liquid, as well as guide the reasonable utilization of mixed liquid.

Molecular Dynamics Simulation of Spreading of Mixture Droplets on Chemically Heterogeneous Surfaces.

The dynamic spreading process of mixed droplets on chemically heterogeneous surfaces has attracted significant attention owing to its extensive industrial applications. The spreading of mixture droplets on a chemically heterogeneous surface is more complex than that for pure fluid droplets and needs to be understood further. In this study, molecular dynamic simulations were performed to investigate the dynamic spreading process of R32/R1234yf mixture droplets and water/ethanol mixture droplets of radius 4.7-6.5 nm with different compositions, on chemically heterogeneous surfaces. The variation in the relative spreading radius with time was analyzed and compared with the molecular kinetic theory. It was observed that for the R32/R1234yf mixture, the actual component mole fraction did not deviate from the nominal one in the triple contact region, and the dynamic spreading behavior was identical to that for the pure fluids. Meanwhile, the converse was true for the ethanol/water mixture. The molecular kinetic theory could accurately predict the spreading of droplets for R32/R1234yf mixtures when the mixture properties were used. However, this was not feasible for ethanol/water mixtures. It was observed that the local physical properties in the triple contact line (including the mole fraction and the lyophilic and lyophobic area ratio) play key roles in the spreading of the ethanol/water mixture droplets. The prediction of the dynamic spreading of water/ethanol mixture droplets on chemically heterogeneous surfaces can be improved significantly by using local properties to modify the molecular kinetic theory.

The sulfate capacities of silicate melts

The solubility of sulfur as sulfate (SO42− or S6+) in silicate melts has been measured experimentally under oxidizing conditions at 1200 to 1500 °C, using SO2-O2 and SO2-CO2 as the input gas mixtures, with S and major elements determined on the quenched glasses by electron microprobe. The silicate melts investigated range from simple systems to natural magmatic compositions. Eighteen compositions in CMAS (CaO-MgO-Al2O3-SiO2) were studied at 1400 °C and varying sulfur trioxide fugacity, fSO3, to demonstrate that [S6+]/fSO3 remains constant within the limits of fSO3 accessed, where [S6+] is the concentration of S6+. This observation validates the concept of the “Sulfate Capacity” defined as CS6+ = [S6+]/(fSO3). Fitting CS6+ to a model derived from reciprocal solution theory as a function of temperature and melt composition from 232 experiments gives:lnCS6+=-8.02+(21100+44000XNa+18700XMg+4300XAl+44200XK+35600XCa+12600XMn+16500XFe2+)/THere XM are the mole fractions of the cation oxide components on the single-cation basis, [S6+] is in parts per million by weight, and fSO3 is in bars referenced to the conventional standard state. As this equation shows, CS6+ is so sensitive to melt composition that the analytical uncertainties in the major-element compositions of the glasses dominate fitting the data to the model.Combining CS6+ with the analogous Sulfide Capacity, CS2-, from previously published work allows the ratio of S oxidation states, S6+/S2−, to be calculated in silicate melts as a function of oxygen fugacity (fO2), temperature and melt composition. These calculations are in reasonable agreement with spectroscopic measurements on experimental glasses at known fO2, and on natural volcanic glasses where measured Fe3+/∑Fe can be used to calculate fO2, despite the presence of H2O in both kinds of glasses. This implies that other S possible melt species like S4+, HS−, etcetera are insignificant. The fugacity of SO2, the main S species degassing from magma on eruption, in equilibrium with a melt of a given total S content varies markedly with fO2, with a maximum at S6+/S2− = 3 (S6+/∑S = 0.75), which corresponds approximately to Fe3+/∑Fe ≈ 0.2 for typical basaltic compositions. Sulfur degassing from magma as SO2 causes oxidation or reduction depending on whether S6+/∑S is greater or less than 0.75, with strong negative feedback on the magnitude of fSO2 in both cases.

An Effective Numerical Simulation Method for Steam Injection Assisted In Situ Recovery of Oil Shale

This paper presents an effective numerical simulation method for production prediction of in situ recovery of oil shale reservoirs with steam injection. In this method, finite volume-based discretization schemes of heat and mass transfer equations of the thermal compositional model are derived and used. The embedded discrete fracture model is used to accurately handle the fractured vertical well. A smooth non-linear solver is proposed to solve the global equations, then cell pressure, temperature, saturation, component mole fractions, and well production rates can be obtained. Compared with the existing commercial software, this new method can have a smoother non-linear solution and handle the complex fracture geometry theoretically. A numerical example is used to test this presented method and can realize accurate calculation results compared with CMG. Another numerical case with a hydraulic fracture and an open thermal boundary condition is implemented to validate the presented method and can effectively handle the actual situation of steam injection-assisted in situ recovery of oil shale, which was difficult to handle using previous methods.

Impact of numerous media on association, interfacial, and thermodynamic properties of promethazine hydrochloride (PMT) + benzethonium chloride (BTC) mixture of various composition

Herein, the impact of numerous media of fixed concentration (H2O, NaCl (50 mmol·kg−1), urea (U, 300 mmol·kg−1) and thiourea (TU, 300 mmol·kg−1)) on the association, interfacial, and thermodynamic properties of promethazine hydrochloride (PMT) and benzethonium chloride (BTC, cationic antimicrobial surfactant)) mixture in several compositions were examined via tensiometry method at room temperature (298.15 K). Along with tensiometry, the interaction between PMT and BTC was also assessed by applying the UV–visible as well as FTIR spectroscopy in an aqueous solution. PMT is used for the symptomatic relief of various allergic conditions. The employed systems critical micelle concentrations (cmc) value was acquired much lower than their calculated corresponding ideal cmc value (cmcid) owing to the interaction between components (PMT and BTC) and the interaction amongst PMT and BTC further increases through increase in mole fraction (α1) of first component (BTC). Diverse solution and surface parameters, thermodynamic parameters, etc. have been processed by use of several purported theoretical models. In NaCl media, the cmc value of singular along with mixed species (PMT + BTC) of each composition were found fewer in magnitude than aqueous media while magnitude increased in U/TU media and TU is more valuable in boosting the cmc than U. Activity coefficient value in each case was continuously found below one due to attractive interaction amongst PMT and BTC. The attained Γmax and Amin value of PMT + BTC implies that the formed mixed interface is the closer packing of PMT and BTC. Excess free energy (ΔGex) was attained negative, exhibiting that the mixed micellar/mixed monolayer stability was higher with the singular component’s micelles/monolayer. The shift in frequency of pure component were attained by FT-IR study by addition of other component that also signifies the straightforward interaction among ingredients. Existing research outcomes revealed a straightforward methodology to design the employed surfactant as an efficient ingredient as a drug delivery vehicle for phenothiazine drug.

Non‐linearchanges in phase inversion temperature for oil and water emulsions of nonionic surfactant mixtures

AbstractHydrophilic–lipophilic deviation (HLD) is a semiempirical framework for surfactant‐oil–water (SOW) formulation that has effectively assimilated SOW properties such as phase inversion temperature (PIT) and Winsor Type I ↔ II ↔ III ↔ IV microemulsion behavior. The HLD system's reliance on surfactant and oil parameters necessitates their experimental determination when relevant and accurate values are not available. In this study, experiments have been of the type commonly used to generate test surfactant HLD parameters based on perturbation of a well‐defined SOW reference system and assumption of linear mixing behavior for PIT versus component mole fractions. The reference SOW compositions comprisedn‐octane, 0.01 M aqueous NaCl, and puren‐decyl tetraethylene glycol ether (C10E4) reference surfactant. Test surfactants were primary alcohol ethoxylates and nonylphenol ethoxylates comprising disperse PEG (polyethylene glycol) chain lengths that are inherent to commercial production of nonionic ethoxylate surfactants. We observe non‐linear behavior of PIT versus test surfactant mole fraction, even when accounting for surfactant concentration effects, so the desired linear correlation that could otherwise be used to assign an HLD parameter has not been obtained. Since an objective of this study has been to improve the predictive utility of the HLD framework for commercial nonionic surfactants, relevant terms in the HLD equation have been assessed in terms of their potential contributions to non‐linear behavior. One current working‐explanation relates substantial non‐linear PIT contribution to oil‐like surfactant components in disperse commercial ethoxylates.

Reduction of Emission Gas Concentration from Coal Based Thermal Power Plant using Full Combustion and Partial Oxidation System

Rapid growth in industrialization has led to high dependency of reliable electric power source for its operation. On the contrary, thermal power plants expel pollutants consisting of hazardous gases that result in degradation of environment and ecosystem. Thus, utmost importance is to generate clean and efficient energy from power plant. This current article resolves the problem of sustainable power production using coal-based thermal power plants, by integrating gasification technologies to the system. The performance of thermal power plant in terms of emission is numerically analyzed with varying gasifier pressure, air-fuel ratio, steam-fuel ratio and flue gas-fuel ratio. Numerical simulation of the gasification cycle with varying parameters is carried out using MATLAB. Optimum performance at gasifier pressure of 2 bar and the steam-fuel ratio of 0.25 was observed with relative air-fuel of 0.075. With increasing flue gas-fuel ratio from 0.25 to 1.00, although the mole fractions of components of syngas don’t differ much, the heating value and cold-gas efficiency of syngas produced decreases for each fuel. Considering the emissions, simulated results present co-gasification as better option over conventional systems. A reduction of two-third in kg of CO2 released per kg of fuel was observed with almost three-fourth decrement in kg of CO2 per kWh of power produced. Also, zero SOx and NOx emissions were observed compared to coal based thermal power plants. It is noted that optimum performance of gasification system at gasifier pressure of 2 bar, air-fuel ratio of 0.1, steam-fuel ratio of 0.25 and flue gas-fuel ratio of 1.00. The proposed cycle presents itself suitable for further research and its application to coal based thermal power plants, providing potential towards supplementary power generation and cleaner exhaust. This research would also significantly contribute to achieve sustainable development goals.

Implications of phase solubility/miscibility and drug-rich phase formation on the performance of co-amorphous materials: The case of Darunavir co-amorphous materials with Ritonavir and Indomethacin as co-formers

The present study was designed to investigate the contribution of solid-state and the impact of composite drug-rich phase generated as a consequence of pH shift on the maximum achievable supersaturation of co-amorphous formulations. The co-amorphous phases of weak base-weak base-pair i.e. Ritonavir and Darunavir were prepared in anticipation of studying the effect of drug-rich phase consequent to pH shift. While the co-amorphous phases of weak base-Weak acid pair i.e. Darunavir and Indomethacin were studied to understand the manifestation of the solid-state drug: co-former miscibility in the absence of drug rich phase. Thermodynamically, the lowering of the supersaturation was found commensurate with the mole fraction of the respective component (Drug/Co-former) within the co-amorphous materials for both Darunavir: Ritonavir and Darunavir: Indomethacin pair. Kinetically, for Darunavir: Ritonavir co-amorphous materials, the shift in the pH from acidic to the neutral side led to the generation of drug-rich phase and subsequent LLPS. The free drug concentration achieved in the bulk of the solution was found dependent upon the mole fraction of the respective component within the drug-rich phase. The relative mole fraction of each component within the composite drug-rich phase is dictated by pH-dependent solubility and molecular weight of the individual components.

Modeling and performance improvement of an industrial ammonia synthesis reactor

Ammonia production from synthesis gas is one of the most important processes in the petrochemical industry. A heterogeneous model is used to improve the efficiency of an industrial ammonia synthesis reactor including three adiabatic catalyst beds. In this model, the effectiveness factor was determined by considering the diffusion reaction equation. Reasonable agreement was achieved between simulated results and industrial data in terms of reactor component mole fraction and temperature. This mathematical model was modified to use for improving the ammonia converter performance and predict the effectiveness factors, nitrogen fractional conversion, temperature, and hydrogen and ammonia mole fraction profiles. The competency of the modified model has been investigated for industrial application by manipulating the reactor operation conditions and observing their effects on reactor output and results revealed the reliability of the developed model.The model is employed to obtain the optimum temperature profiles of each catalyst bed in the reactor based on equilibrium curve of ammonia synthesis reaction. Operating condition of the reactor was changed to achieve the optimum temperature profile according to model results by manipulating the reactor quench valves. After implementing changes in the reactor, the reactor performance and efficiency has improved with increasing ammonia conversion from 15.26% to 15.45% that increases ammonia production by 3t/d and energy saving by 1.66 Gj/h. The differential temperature of the first catalyst bed significantly increased by 6 °C and overall differential temperature through ammonia converter is increased by around 4 °C. This increases steam production by 2 t/h through loop boiler.

Investigation of aggregation behavior of ionic surfactant mixture in crystal violet dye solution at different temperatures and solvent compositions: Conductivity and theoretical approach

The conductometric measurement technique was utilized to have an in-depth knowledge on the aggregation behavior of a mixture of two ionic surfactants – sodium dodecyl sulfate (SDS; a common anionic surfactant) and cetyltrimethylammonium bromide (CTAB; a cationic surfactant), in crystal violet (CV) and CV + ethanol (5 and 10% (w/w)) solution media. The related micellar and thermodynamic parameters of the mixed system have been assessed and presented in this paper. The cmc values of pure SDS/CTAB, & their mixture in presence of CV dye, were observed to decrease and thus the insertion of CV favors the micellization of pure and mixed micelle. Also, the cmc values of the mixture of SDS & CTAB undergo a drop with increasing the concentration of CTAB at a specific temperature and these cmc fall in the middle of the detected cmc of SDS & CTAB micelles in all the media studied. The observed values of cmc are lower in magnitude in comparison to the ideal cmc and the numerical values of the interaction parameter (β) are negative, which manifests the existence of attractive interaction between SDS and CTAB surfactants in presence of CV dye. The cmc values are also dependent on the fluctuation of experimental temperature. The micellar mole fraction of component 1 (CTAB) in SDS + CTAB mixture (X1Rub) and the ideal micellar mole fraction (X1id) was obtained to be relatively greater than the related stoichiometric mole fraction (α1) of component 1 (CTAB). The activity coefficients (f1Rub and f2Rub) remained below unity in all test cases, suggesting an attractive interaction in the mixed micellar system. The obtained thermodynamic parameters demonstrate that the single and mixed micellization phenomena are spontaneous and the main driving forces are hydrophobic and exothermic in nature.

CO2-binding organic liquids for high pressure CO2 absorption: Statistical mixture design approach and thermodynamic modeling of CO2 solubility using LJ-Global TPT2 EoS

CO2-binding organic liquids (CO2-BOLs) or switchable ionic liquids (SILs) are switchable polarity solvents (SPS) that can be used as non-aqueous, energy efficient solvents for CO2 absorption. In this study, the three-component CO2-BOLs comprised of a single-component CO2-BOL (tertiary alkanolamine) and a two-component CO2-BOL (superbase/alcohol) are introduced. The most efficient equimolar combination of superbase (1,8-diazabicyclo-[5.4.0]-undec-7-ene (DBU)), alcohol (methanol, n-butanol, sec-butanol, tert-butanol and hexanol) and amine (Dimethylethanolamine (DMEA), Diethylethanolamine (DEEA) and N-methyldiethanolamine (MDEA)) are obtained using screening experiments considering CO2 loading (αeq) and absorption rate (αR). The mixture design technique is employed for modeling of αeq and αR as a function of mole fraction of components at 35.0 °C and initial pressure of 25.0 bar. The DBU/DMEA/n-butanol CO2-BOL represented the best performance for CO2 uptake. The experimental CO2 solubility data in DBU/n-butanol, DBU/DMEA and DBU/DMEA/n-butanol BOLs were obtained in the temperature range of 25.0–45.0 °C and the pressure range of 1.0–45.0 bar. The DBU mole fraction was selected to be 0.1 and 0.2 while the molar ratio of DMEA to n-butanol was kept constant at 2 in the three-component BOL. The simultaneous vapor–liquid and chemical equilibrium calculation algorithm using LJ-Global TPT2 equation of state was used for the thermodynamic modeling of CO2 solubility in BOLs. The average absolute relative deviation error (AAD%) for the calculation of total pressure of DBU/n-butanol, DBU/DMEA and DBU/DMEA/n-butanol BOLs were obtained to be 8.5%, 5.8% and 8.6%, respectively.

Unraveling the octane response of gasoline/ethanol blends: Paving the way to formulating gasoline surrogates

Ethanol is widely used as a gasoline octane booster, and yet, its blending response is not fully understood. Blending ethanol with gasoline most often leads to a synergistic effect (higher than expected relative to linear blending), but can also lead to a linear or antagonistic blending (lower than expected relative to linear blending). To address the knowledges gap in ethanol blending, this study provides new research octane number (RON) and motor octane number (MON) measurements of ethanol blended with various gasoline surrogates. The first set of blends are ternary mixtures, designed to study the interactions between primary reference fuels (PRFs) and certain gasoline components when blended with ethanol. These gasoline components are 1-hexene, 1,2,4-trimethylbenzene and cyclopentane, which, represents the olefin, aromatic and naphthenes classes in commercial gasoline fuels, respectively. The second set represents multicomponent surrogates for Fuels for Advanced Combustion Engines (FACE) gasolines, developed in our previous work (Badra et al., Applied Energy 2017 p. 778-793). This study developes an octane blending model of ethanol/gasoline surrogates that utilize the new measurements along with datasets available in literature. The model consists of the conventional linear by ethanol molar fraction correlation, with the addition of non-linearity terms that depend on base fuel properties, namely, the octane sensitivity and the mole fraction of gasoline components. The model can predict the octane numbers (RON and MON) of blends containing gasoline surrogates composed of n-heptane, n-pentane, iso-octane, iso-pentane, toluene, 124-trimethylbenzene, cyclopentane, cyclohexane (for RON only) and 1-hexene. To ensure the generality of the developed model and avoid over-fitting, the model is trained using 85% of the available dataset while the remaining measurements have been used to test the model. The proposed model outperforms many ethanol blending models available in literature with 87% of the RON and 83% of the MON measurements being within the reproducibility limits. This model can be integrated to the process of designing gasoline surrogates that contain ethanol.