Design Of Separation Processes Research Articles

CRYSTALLIZATION TEMPERATURE AND SOLVENT COMPOSITION EFFECT FOR ENHANCEMENT OF UNSATURATED FATTY ACIDS FROM PALM OIL USING UREA COMPLEXATION

Mono and Poly Unsaturated Fatty Acids (MUFAs/PUFAs) are vital nutritional sources for infants, adults, and the elderly. The content of monounsaturated fatty acids (MUFAs) and polyunsaturated fatty acids (PUFAs) can be enhanced in vegetable oils or animal fats using a range of different techniques. The process of urea complexation is highly effective and efficient for concentrating monounsaturated fatty acids (MUFAs) and polyunsaturated fatty acids (PUFAs) from vegetable oils. This study employed refined palm oil as the raw material that went through saponification and purification processes in order to generate fatty acids mixture. Subsequently, urea was introduced to create a complex chemical in the form of urea complexed fraction (UCF) and leaving the non-urea complexed fraction (NUCF). Gas chromatography was employed to analyze the fatty acid composition obtained from urea complexation. This study investigated the impact of different crystallization temperatures (-4°C, 8°C, 12°C, 22°C, and 30°C) and ethanol concentrations (ranging from 0% to 100%) on enhancing the unsaturated content and yield of fatty acids derived from palm oil. It also conducted predictive equations to determine the yield and fatty acids composition in the non-urea complexed fraction (NUCF) which are important for separation process design in chemical industries. The study revealed that increasing the crystallization temperature resulted in a larger yield in the liquid fraction (NUCF), but a lower concentration of monounsaturated fatty acids (MUFAs) and polyunsaturated fatty acids (PUFAs).

Cost minimization of membrane-based separation systems for H2 recovery: A comparison of two optimization approaches

This paper addresses the optimization of membrane-based processes, with a specific focus on H2 recovery in hydrocarbon processing plants. A comparative analysis of two optimization approaches is conducted for designing H2 recovery systems for a multicomponent gas mixture containing H2/N2/CO2/CO. The main objective is to achieve the desired H2 recovery and product purity levels while minimizing costs. The paper compares two approaches for optimization: the first uses a simulation-based optimization technique with Aspen Custom Modeler/ASPEN Plus, while the second employs a simultaneous optimization method using GAMS (General Algebraic Modeling System). The methods are thoroughly compared, evaluating their strengths and weaknesses through qualitative and numerical assessments. To this end, a reference case was selected from the existing literature. The results obtained indicate that both proposed approaches are suitable for optimizing the design of a two-stage membrane configuration, as evidenced by the similarity of the optimal solutions obtained from both approaches. Subsequently, based on the analysis of numerical values for the optimal design problem for the investigated two-stage membrane configuration, a hybrid strategy for the optimal synthesis and design of multi-stage separation processes is proposed.The study fills a gap in the literature by providing a comprehensive analysis of the advantages and disadvantages of optimization approaches in the context of technology of separation of gases. This research provides valuable insights into the field and offers guidance for selecting appropriate approaches to improve the efficiency and cost-effectiveness of gas separation processes in real-world applications.

Widening the Stimuli-Responsiveness of Aqueous Biphasic Systems by Changing the Ionic Liquid Cation Basicity.

Herein we demonstrate the formation of new stimuli-responsive aqueous biphasic systems (ABS), able to respond simultaneously to temperature and pH, or just to one stimulus, therefore allowing the design of more sustainable separation processes. This dual behavior is achieved with ABS formed by mono- or dicationic protic ionic liquids as phase-forming components, being defined by the ionic liquid cation chemical structure or its basicity. While ABS comprising monocationic ionic liquids only respond to the effect of temperature, systems comprising dicationic ionic liquids are simultaneously affected by both temperature and pH variations. Dicationic ionic liquids are here identified as the key to unlock a double response to stimuli, which is due to the presence of two pKa values afforded by the cation. The reported findings contribute to increase the customizability of double stimuli-responsive ABS based on ionic liquids, whose development was up to date limited to ionic liquids bearing pH-responsive anions, opening the door towards the development of more sustainable separation processes.

Multiphase Behavior of the Water + 1-Butanol + Deep Eutectic Solvent Systems at 101.3 kPa

The growing demand for more sustainable routes and processes in the mixture separation and purification industry has generated a need to search for innovations, with new solvent alternatives being a possible solution. In this context, a new class of green solvents, known as deep eutectic solvents (DESs), has been gaining prominence in recent years in both academic and industrial spheres. These solvents, when compared to ionic liquids (ILs), are more environmentally friendly, less toxic, low-cost, and easier to synthesize. In addition, they have significantly lower melting points than their precursors, offering a promising option for various applications in this industrial sector. Understanding and studying the thermodynamic behavior of systems composed of these substances in purification and separation processes, such as liquid–liquid extraction and azeotropic distillation, is extremely important. This work aimed to study the phase behavior of liquid–liquid equilibrium (LLE) and vapor–liquid equilibrium (VLE) of water + 1-butanol + DES (choline chloride + glycerol) systems with a molar ratio of 1:2. Experimental LLE data, obtained at 298.15 K and 101.3 kPa, and VLE data, obtained at 101.3 kPa and in the temperature range of 364.05 K–373.85 K, were submitted to the thermodynamic quality/consistency test, proposed by Marcilla et al. and Wisniak, and subsequently modeled using the gamma–gamma approach for the LLE and gamma–phi for the VLE. The non-random two-liquid (NRTL) model was used to calculate the activity coefficient. The results are presented for the VLE in a temperature–composition phase diagram (triangular prism) and triangular phase diagrams showing the binodal curve and tie lines (LLE). The separation and distribution coefficients of LLE were determined to evaluate the extractive potential of the DES. For the VLE, the values of the relative volatility of the system were calculated, considering the entrainer free-basis, to evaluate the presence or absence of azeotropes in the range of collected points. From these data, it was possible to compare DES with ILs as extracting agents, using data from previous studies carried out by the research group. Therefore, the results indicate that the NRTL model is efficient at correlating the fluid behavior of both equilibria. Thus, this study serves as a basis for future studies related to the understanding and design of separation processes.

Thermodynamic Intrinsic Insights and Process Design for High-Efficiency Separation of Quaternary System with Three Azeotropes and Three Homologues

Thermodynamic Intrinsic Insights and Process Design for High-Efficiency Separation of Quaternary System with Three Azeotropes and Three Homologues

Total separation of multi-plastic wastes using magnetic levitation with adjustable sensitivity

Novel separation method with high efficiency is of great significance for mechanical recycling mixed waste plastics plays. However, the efficiency of most extant methods is restricted by their shortage that the methods can only deal with binary mixtures. In this paper, a novel magnetic levitation (MagLev) separation method based on scaled-up MagLev device is proposed to handle multi-plastics. A theoretical model on distribution of magnetic flux intensity and levitation conditions is established to guide the design of separation process. Based on the theoretical analysis, different processes for separation of multi-plastics with different purpose can be realized. The high sensitivity allows the separation of plastics with similar appearances (e.g. transparent plastics like polycarbonate and polymethyl methacrylate) and densities (difference with 0.01 g/cm3). The adjustable distribution of magnetic field changes the levitation condition of the waste plastics. Thus, the sequential separation of multi-plastics and extraction of target material from multi-plastics mixture are successfully addressed. The experiments demonstrate that the purities of separated multiple plastics reach to approx. 100 %. Furthermore, additional advantages of low cost and no energy consumed in separation process make the method a promising solution for economically-viable and environmentally-friendly mass production procedure.

Design and multiperformance evaluation of the ternary azeotrope separation process via extractive distillation based on different extractants

Resource utilization and sustainable wastewater treatment have received widespread attention because of their efficient use of energy. In this study, an ethanol (EtOH)/ethyl tert-butyl ether/water ternary azeotropic system was used to explore the separation efficiency of various extractants. The relative volatility, toxicity, and process modeling of extractants were analyzed to provide a theoretical basis and practical guidance for screening the optimal extractant among nine commonly used extractants. Extractive distillation (ED) was optimized for six processes with a focus on total energy consumption (TEC) and total annual cost (TAC). The ED-EtOH process was the most economical, whereas the extractive ED-DMSO process had the lowest TEC. After heat integration (HI) treatment, the TAC and TEC of each process were reduced, among which HI-ED-EtOH and HI-ED-glycerol (GLY) had the best and lowest economy, respectively. Although high-boiling point and high latent heat extractants (such as GLY and EtOH) increase the heat demand and operating costs, their high latent heat characteristics can effectively recycle heat energy during the HI process. The optimal balance between economy and energy consumption was determined through multi objective optimization considering the physical and chemical properties, environmental impact, and adaptability of extractants.

Adsorption characteristics and separation behavior of binder and binderless zeolite LiX Pellets: O2, N2, and CO2

In adsorptive gas separation process design, optimal adsorbent selection acts as a critical factor in process efficiency. This study investigated the adsorption equilibria and kinetics of O2, N2, and CO2 (weak, medium and strong affinity, respectively) and the breakthrough performance of four commercial zeolite LiX pellets (one binderless and three binder zeolite LiX pellets) because the performance of pelletized zeolites becomes different by adding binders and pelletizing methods. The adsorption isotherms at 293–323 K and up to 100 kPa were correlated with the dual-site Langmuir and Sips models. For all adsorbents, the order of adsorption amount and isosteric heat of adsorption was CO2 ≫ N2 > O2. However, differences among the four zeolite pellets were also observed, showing the highest values of the binderless zeolite LiX pellet. Furthermore, the adsorption capacity was 20–25 % smaller for CO2 and 40–50 % smaller of N2 and O2 at 100 kPa compared to pure zeolite LiX powder. According to kinetic analysis using a non-isothermal diffusion model, the adsorption rate of N2 was faster than that of CO2 for all adsorbents, showing the order difference in the low-pressure range. The kinetic difference among the zeolite pellets resulted from the effects of heat of adsorption, heat dissipation, and thermal resistance. The breakthrough performance using N2 and O2 was mainly controlled by the adsorption capacity, showing almost constant breakthrough pattern regardless of the samples. This study suggests that detailed evaluation of pelletized adsorbent is essential before designing adsorptive processes because performance of adsorbent powder would lead to under-design of the process. (255 words)

Modeling of multi-mechanisms permeability for hydrogen separation using a membrane process

In gas separation using nanoporous membranes, both operating conditions and membrane properties are key to the process performance. Mathematical modeling is crucial for defining the optimal conditions and properties for the optimization and design of these processes. This research introduces a comprehensive model that integrates surface and pore permeabilities for studying the (PIM-1) membrane performance for H2/N2 separation. The model combines empirical and solution-diffusion models to examine temperature and pressure effects alongside a theoretical approach for assessing how pore size and porosity influence permeability and selectivity. Simulation results indicated that temperature increases from 298 K to 373 K significantly enhanced hydrogen and nitrogen permeability by 13% and 135%, respectively, while the selectivity dropped from 24.6 to 15.3. On the other hand, the pressure effect was less significant compared to the effect. The study also highlighted the critical roles of pore size and porosity in transport mechanisms and membrane performance, showing that increasing the pore size and porosity enhanced permeability and reduced selectivity. Remarkably, PIM-1 membranes with pore sizes of near 1 nm and porosity below 0.1 exceeded the Robeson 2008 upper limit, showcasing improved permeability with good selectivity. This model offers a predictive tool for PIM-1 membrane performance under various conditions, facilitating the design of efficient separation process.

Pressure-driven membrane processes for the recovery and recycling of deep eutectic solvents: A seaweed biorefinery case study.

Deep eutectic solvents (DES) are green alternatives for conventional solvents. They have gained attention for their potential to extract valuable compounds from biomass, such as seaweed. In this framework, a case study was developed to assess the feasibility of pressure-driven membrane processes as an efficient tool for the recovery of deep eutectic solvents and targeted biomolecules. For this purpose, a mixture composed of the DES choline chloride – ethylene glycol (ChCl-EG) 1:2, water and alginate was made to mimic a DES extraction from seaweed. An integrated separation process design was proposed where ultrafiltration-diafiltration-nanofiltration (UF-DF-NF) was coupled. UF and DF were found to be effective for the separation of alginate with an 85 % yield. DES was likewise recovered by 93 %, proving the membrane filtrations’ technical feasibility. The NF performance to separate the DES from the water, for its recycling, laid by a 45 %-50 % retention and a final concentrated DES solution of 18 %(v/v).

Estimating the parameters of competitive Langmuir adsorption isotherms from measured responses to rectangular pulse injections exploiting equilibrium theory

Knowledge of adsorption isotherms is essential for the design and optimization of chromatographic separation processes. Since the experimental determination of these thermodynamic functions is a complicated and time consuming task, there is a need to develop methods which are fast and easy to apply. An attractive group of methods is based on neglecting in the analysis of measured dynamic elution profiles all kinetic effects. These methods assume the validity of an isotherm model equation and exploit the possibility to solve analytically the column mass balance equations of the equilibrium model. If just the dispersive part of an elution profile is, the method is known as “elution by characteristic point” (ECP). The ECP method has been applied successfully to analyse column effluent profiles of single component dissolved in a mobile phase. This work extends the ECP method to analyse just the shapes of elution profiles recorded after injecting samples that contain two key components to be separated. The extended ECP method requires recording only one overloaded elution profile for the two-component mixture and offers a fast and efficient way to estimate isotherm model parameters. The method is in particular attractive if there is limited access to the pure components, as for example in cases of enantiomers. The underlying theory is presented and applied for the case that the adsorption equilibria can be described satisfactorily by the classical competitive Langmuir model. Core of the theory are the available analytical equations describing the outlet concentration profiles of the two solutes for the equilibrium controlled case the. Considering a case study, it is shown that the extended ECP method can be applied successfully for columns characterized by 2500 or more theoretical plates. However, the method can be useful also for columns with lower efficiency. It provides then a rough estimation regarding the isotherm courses.

Synthesis of a Series of Quinoline-Based New Chiral Reagent and its Application in Separation of Racemic Mexiletine followed by Liquid Chromatography and Confirmation of Results Using Molecular Modelling; A Complete Study

In present work, L-valine-based new chiral derivatives were prepared by introducing hydrophobic groups. The prepared derivatives were then used to prepare quinoline-based chiral reagents under mild amidation reaction and esterification reaction. Spectroscopic techniques, such as HRMS, FT-IR, 1H NMR and CHNS analysis, were used to characterize the synthesized chiral reagents. The synthesized series of reagents was then used to derivatize diastereomers of racemic mexiletine and these diastereomers were separated using the RP-HPLC (a derivatization approach of enantioseparation). The mobile phase for the analysis consisted of acetonitrile and buffer solution. The impact of modifying mobile phase pH and concentrations was optimized to separate diastereomers. The lowest energy-minimize optimized diastereomer structures, as well as the design of separation processes and elution orders, were also developed through the use of density functional theory (DFT) calculations. Following ICH guidelines, the limits of detection (0.161 ng/mL) and quantification (0.483 ng/mL) were determined, together with the retention-factor (k), selectivity-factor (α), resolution-factor (RS) and technique validation.

Theoretical insights into the extraction behaviors of neptunium(VI) and plutonium(IV) based on the structure of organophosphorus ligands

Organophosphorus ligands such as TBP, TiAP, and DMHMP have exhibited excellent performance in recovering actinides from spent fuel. In this work, the molecular geometries and properties of TBP, TiAP and DMHMP were investigated using density functional theory calculations. Furthermore, the extraction mechanism of ligands for actinides (Np(Ⅵ), Pu(Ⅳ)) was further elucidated by simulating the microstructures and extraction reactions of metal–ligand complexes. The results demonstrate that the complexation ability of the three ligands on actinide cations (NpO22+ and Pu4+) follows the order of DMHMP > TiAP > TBP. The electrostatic potential (ESP) analysis indicates that the nucleophilic ability of DMHMP is stronger than that of the other two ligands. The frontier molecular orbital analysis of the three ligands represents that DMHMP has the highest HOMO energy, suggesting that it has the strongest electron-donating capability and is more likely to bond with metal ions. The values of Wiberg bond indices (WBI) suggest that the MO bonds in DMHMP complexes have more covalency. According to the QTAIM analysis, the interactions between actinide cations and the ligands are predominantly ionic in nature. The molecular orbital analysis of the complexes shows that the M(NO3)n·2DMHMP (MNpO22+ and Pu4+) complexes are more stable, which is supported by thermodynamic energy analysis. This work has clarified the complexing properties of actinide cations with three ligands, shedding light on the extraction mechanisms of organophosphorus ligands for actinide cations. It is anticipated to lay the theoretical foundation for the efficient recovery of critical actinide elements in spent fuel reprocessing, which will also provide innovative approaches for the design and development of related separation processes.

In situ adsorption of itaconic acid from fermentations of Ustilago cynodontis improves bioprocess efficiency

BackgroundReducing the costs of biorefinery processes is a crucial step in replacing petrochemical products by sustainable, biotechnological alternatives. Substrate costs and downstream processing present large potential for improvement of cost efficiency. The implementation of in situ adsorption as an energy-efficient product recovery method can reduce costs in both areas. While selective product separation is possible at ambient conditions, yield-limiting effects, as for example product inhibition, can be reduced in an integrated process.ResultsAn in situ adsorption process was integrated into the production of itaconic acid with Ustilago cynodontis IAmax, as an example of a promising biorefinery process. A suitable feed strategy was developed to enable efficient production and selective recovery of itaconic acid by maintaining optimal glucose concentrations. Online monitoring via Raman spectroscopy was implemented to enable a first process control and understand the interactions of metabolites with the adsorbent. In the final, integrated bioprocess, yield, titre, and space–time yield of the fermentation process were increased to values of 0.41 gIA/gGlucose, 126.5 gIA/L and 0.52 gIA/L/h. This corresponds to an increase of up to 30% in comparison to the first extended batch experiment without in situ product removal. Itaconic acid was recovered with a purity of at least 95% and high concentrations above 300 g/L in the eluate.ConclusionIntegration of product separation via adsorption into the bioprocess was successfully conducted and improved the efficiency of itaconic acid production. Raman spectroscopy was proven to be a reliable tool for online monitoring of various metabolites and facilitated design and validation of the complex separation and feed process. The general process concept can be transferred to the production of various similar bioproducts, expanding the tool kit for design of innovative biorefinery processes.

A perspective on data-driven screening and discovery of polymer membranes for gas separation, from the molecular structure to the industrial performance

Abstract In the portfolio of technologies available for net zero-enabling solutions, such as carbon capture and low-carbon production of hydrogen, membrane-based gas separation is a sustainable alternative to energy-intensive processes, such as solvent-based absorption or cryogenic distillation. Detailed knowledge of membrane materials performance in wide operative ranges is a necessary prerequisite for the design of efficient membrane processes. With the increasing popularization of data-driven methods in natural sciences and engineering, the investigation of their potential to support materials and process design for gas separation with membranes has received increasing attention, as it can help compact the lab-to-market cycle. In this work we review several machine learning (ML) strategies for the estimation of the gas separation performance of polymer membranes. New hybrid modelling strategies, in which ML complements physics-based models and simulation methods, are also discussed. Such strategies can enable the fast screening of large databases of existing materials for a specific separation, as well as assist in de-novo materials design. We conclude by highlighting the challenges and future directions envisioned for the ML-assisted design and optimization of membrane materials and processes for traditional, as well as new, membrane separations.

Molecular-based artificial neural networks for selecting deep eutectic solvents for the removal of contaminants from aqueous media

Computational methods for predicting a solvent’s performance in a given application, and for selecting an adequate solvent for that application, are becoming increasingly essential for separation processes. In this context, this article presents a first-of-a-kind machine learning tool based on guided molecular design of solvents to predict the performance of various solvent systems in the solvent extraction process. The tool was demonstrated herein for the extraction of aqueous boron, through the selection of neoteric solvents from a dataset that spans different types of solvents (molecular solvents, deep eutectic solvents (DESs) and ionic liquids). The model was developed by first obtaining the COSMO-RS-based molecular descriptors (σ-profiles) for each solvent system and using them as input parameters to an Artificial Neural Network (ANN), in addition to other operational parameters (e.g., pH, temperature, ion concentration, and A/O ratio), while extraction efficiency as the output. The results showed that the optimal ANN configuration (59–20-15–1) exhibited remarkable predictability for boron extraction with an R2 of 0.988 and 0.977 for the training and testing sets, respectively. The model was used to investigate different solvent systems of which six new DESs were successfully synthesized, experimentally tested, and characterized across different properties such as density, viscosity, and leachability. The combination of Decanol and 2,2,4- trimethyl-1,3-pentanediol exhibited appreciable properties and high experimental extraction efficiency of 97.22%. The experimentally validated model demonstrates the effectiveness of molecular-based descriptors and machine learning for predicting the extraction capabilities of solvents in aqueous media and allows further exploration of new solvent systems based on their extraction performance at different operational conditions. This proof-of-concept approach can be effectively adopted to predict the extraction behavior of different solvent systems towards target contaminants in aqueous environments, thereby supporting both the design of separation processes and solvent screening for future applications.

Process design and multi-objective optimization for separation of different feed composition of acetonitrile / ethanol / water with extractive distillation by varying pressure / pervaporation

In order to separate and purify the reaction raw material ethanol (EtOH) and product acetonitrile (ACN) from the azeotrope of ACN / EtOH / water, an efficient extractive distillation by varying pressure process (EDP) was designed to separate them. Because the feed composition in industrial production was constantly changing, processes of different feed compositions was simulated. Taking into account both economic and environmental factors, the non-dominated sorting genetic algorithm comprehensively optimizes the parameters. The azeotrope was pressure sensitive and the pressure parameter was also optimized in order to improve the efficiency of process energy utilization. Heat exchange network optimization technology was used to fully utilize excess heat in the process. The distillation coupled pervaporation technology has also been designed to explore emerging technologies. Among the three different coupling processes, the performance of EDP-pervaporation (EDPV) was better. Compared with EDP, EDPV under different schemes reduce the total annual cost (TAC) and gas emissions by more than 15% and 21 %, respectively. It was found that the energy consumption was related to the normal distance from the feed composition to the distillation boundary and isovolatility curve.

Activity coefficients, phase diagram and separation process design for NaNO3 and Pb(NO3)2 of waste liquor in the production of lead–chromium pigments

Lead contamination is one of the common soil heavy metal pollution elements, and the waste solution discharged from chromium–lead pigment plants is one of the potential sources of lead contamination. In order to separate and recover sodium nitrate and lead nitrate from waste liquid of the production of lead–chromium pigments, it is necessary to make systematical studies on thermodynamic properties, and thermodynamic phase diagram of the salt–water system containing NaNO3 and Pb(NO3)2. Accordingly, in this work, the cell potential method were chosen to measure the thermodynamic activity coefficients of mixed solutions NaNO3– Pb(NO3)2–H2O. The thermodynamic properties (mean activity coefficient, osmotic coefficient, water activity, excess Gibbs free energy) of NaNO3–Pb(NO3)2–H2O mixed solutions at 308.15 K were also determined by Pitzer model. Furthermore, the phase equilibria of the NaNO3–Pb(NO3)2–H2O system was investigated by the isothermal dissolution equilibrium method, and its isothermal equilibrium phase diagram was drawn in detail. The solubility data were used to obtain the Pitzer mixing ion parameters, and the solubilities of salts in the ternary system were predicted by Pitzer model. Based on the plotted phase diagrams, as a result, the process to separate NaNO3 and enrich the recycling of Pb(NO3)2 was designed based on the calculated phase diagram. Among them, the recovery of NaNO3 reached 70.82% and the enrichment of Pb(NO3)2 reached about 15 times. The designed separation process in this work has the advantages of green, low energy consumption and sustainability, which is of positive practical significance for the full utilization of resources and the prevention of environmental pollution.

Improved process design for monoclonal antibody charge variants separation with multicolumn counter-current solvent gradient purification

The multicolumn counter-current solvent gradient purification (MCSGP) method has proven effective in addressing the issue of elution profile overlap for difficult-to-separate proteins, leading to improved purity and recovery. However, during the MCSGP process, the flow rate and proportion of loaded proteins undergo changes, causing a significant discrepancy between the elution profiles of batch process design and the actual MCSGP process. This mismatch negatively impacts the purity and recovery of the target protein. To address this challenge, an improved process design (reDesign) was proposed with the first-run MCSGP to mimic the actual continuous process and obtain elution profiles that closely resemble the real ones. The reDesign was demonstrated with both a model protein mixture and a sample of monoclonal antibody (mAb) with charge variants. For model protein mixture, the reDesign-based MCSGP process (reMCSGP) showed a remarkable improvement in recovery, increasing from 83.6% to 97.8% while maintaining a purity of more than 95%. For mAb sample, the recovery of reMCSGP improved significantly to 93.9%, surpassing the performance of normal MCSGP processes at a given purity level of more than 84%. In general, the new process design strategy developed in this work could generate a more representative elution profile that closely mirrors actual conditions in continuous processes, which enhances the separation performance of MCSGP.

Impact of concentration polarization on membrane gas separation processes: From 1D modelling to detailed CFD simulations

Membranes are one key technology for gas separation. Current design methodologies make use of a 1D set of mass balance equations with membrane taken as the only mass transfer resistance (no concentration polarization hypothesis). This strategy has however to be reconsidered with emerging high-performance membrane materials. Accordingly, a rigorous CFD simulation approach is developed in order to correctly compute their separation efficiency. The results reveal that, compared to CFD, in the presence of concentration polarization, 1D models largely overestimate the separation performance of high-performing membranes. Based on a generic modelling of mass transfer in the gas phase under concentration polarization, a novel 1D modified approach is reported, showing similar predictions compared to CFD simulations, but offering very fast computations. This strategy is of interest for the simple and systematic design of membrane gas separation processes, including process synthesis approaches.