Polyurethane-SAPO-34 mixed matrix membrane for CO2/CH4 and CO2/N2 separation

Cationic Imidazolium-Urethane-Based Poly(Ionic Liquids) Membranes for Enhanced CO2/CH4 Separation: Synthesis, Characterization, and Performance Evaluation

The escalating emissions of CO2 into the atmosphere require the urgent development of technologies aimed at mitigating environmental impacts. Among these, aqueous amine solutions and polymeric membranes, such as cellulose acetate and polyimide are commercial technologies requiring improvement or substitution to enhance the economic and energetic efficiency of CO2 separation processes. Ionic liquids and poly(ionic liquids) (PILs) are candidates to replace conventional CO2 separation technologies. PILs are a class of materials capable of combining the favorable gas affinity exhibited by ionic liquids (ILs) with the processability inherent in polymeric materials. In this context, the synthesis of the IL GLYMIM[Cl] was performed, followed by ion exchange processes to achieve GLYMIM variants with diverse counter anions (NTf2-, PF6-, and BF4). Subsequently, PIL membranes were fabricated from these tailored ILs and subjected to characterization, employing techniques such as SEC, FTIR, DSC, TGA, DMA, FEG-SEM, and CO2 sorption analysis using the pressure decay method. Furthermore, permeability and ideal selectivity assessments of CO2/CH4 mixture were performed to derive the diffusion and solubility coefficients for both CO2 and CH4. PIL membranes exhibited adequate thermal and mechanical properties. The PIL-BF4 demonstrated CO2 sorption capacities of 33.5 mg CO2/g at 1 bar and 104.8 mg CO2/g at 10 bar. Furthermore, the PIL-BF4 membrane exhibited permeability and ideal (CO2/CH4) selectivity values of 41 barrer and 44, respectively, surpassing those of a commercial cellulose acetate membrane as reported in the existing literature. This study underscores the potential of PIL-based membranes as promising candidates for enhanced CO2 capture technologies.

Recent advancements in polyurethane-based membranes for gas separation

Gas separation membranes are critical in a variety of environmental research and industrial applications. These membranes are designed to selectively allow some gases to flow while blocking others, allowing for the separation and purification of gases for a variety of applications. Therefore, the demand for fast and energy-efficient gas separation techniques is of central interest for many chemical and energy production diligences due to the intensified levels of greenhouse and industrial gases. This encourages the researchers to innovate techniques for capturing and separating these gases, including membrane separation techniques. Polymeric membranes play a significant role in gas separations by capturing gases from the fuel combustion process, purifying chemical raw material used for plastic production, and isolating pure and noncombustible gases. Polyurethane-based membrane technology offers an excellent knack for gas separation applications and has also been considered more energy-efficient than conventional phase change separation methodologies. This review article reveals a thorough delineation of the current developments and efforts made for PU membranes. It further explains its uses for the separation of valuable gases such as carbon dioxide (CO2), hydrogen (H2), nitrogen (N2), methane (CH4), or a mixture of gases from a variety of gas spillages. Polyurethane (PU) is an excellent choice of material and a leading candidate for producing gas-separating membranes because of its outstanding chemical chemistry, good mechanical abilities, higher permeability, and variable microstructure. The presence of PU improves several characteristics of gas-separating membranes. Selectivity and separation efficiency of PU-centered membranes are enhanced through modifications such as blending with other polymers, use of nanoparticles (silica, metal oxides, alumina, zeolite), and interpenetrating polymer networks (IPNs) formation. This manuscript critically analyzes the various gas transport methods and selection criteria for the fabrication of PU membranes. It also covers the challenges facing the development of PU-membrane-based separation procedures.

Simulating and Comparing CO2/CH4 Separation Performance of Membrane-Zeolite Contactors by Cascade Neural Networks

Separating carbon dioxide (CO₂) from gaseous streams released into the atmosphere is becoming critical due to its greenhouse effect. Membrane technology is one of the promising technologies for CO₂ capture. SAPO-34 filler was incorporated in polymeric media to synthesize mixed matrix membrane (MMM) and enhance the CO₂ separation performance of this process. Despite relatively extensive experimental studies, there are limited studies that cover the modeling aspects of CO₂ capture by MMMs. This research applies a special type of machine learning modeling scenario, namely, cascade neural networks (CNN), to simulate as well as compare the CO₂/CH₄ selectivity of a wide range of MMMs containing SAPO-34 zeolite. A combination of trial-and-error analysis and statistical accuracy monitoring has been applied to fine-tune the CNN topology. It was found that the CNN with a 4-11-1 topology has the highest accuracy for the modeling of the considered task. The designed CNN model is able to precisely predict the CO₂/CH₄ selectivity of seven different MMMs in a broad range of filler concentrations, pressures, and temperatures. The model predicts 118 actual measurements of CO₂/CH₄ selectivity with an outstanding accuracy (i.e., AARD = 2.92%, MSE = 1.55, R = 0.9964).

Truly combining the advantages of polymeric and zeolite membranes for gas separations

Mixed-matrix membranes (MMMs) have been investigated to render energy-intensive separations more efficiently by combining the selectivity and permeability performance, robustness, and nonaging properties of the filler with the easy processing, handling, and scaling up of the polymer. However, truly combining all in one single material has proven very challenging. In this work, we filled a commercial polyimide with ultrahigh loadings of a high-aspect ratio, CO₂-philic Na-SSZ-39 zeolite with a three-dimensional channel system that precisely separates gas molecules. By carefully designing both zeolite and MMM synthesis, we created a gas-percolation highway across a flexible and aging-resistant (more than 1 year) membrane. The combination of a CO₂-CH₄ mixed-gas selectivity of ~423 and a CO₂ permeability of ~8300 Barrer outperformed all existing polymer-based membranes and even most zeolite-only membranes.

Developing a Hybrid Neuro-Fuzzy Method to Predict Carbon Dioxide (CO2) Permeability in Mixed Matrix Membranes Containing SAPO-34 Zeolite

This study compares the predictive performance of different classes of adaptive neuro-fuzzy inference systems (ANFIS) in predicting the permeability of carbon dioxide (CO₂) in mixed matrix membrane (MMM) containing the SAPO-34 zeolite. The hybrid neuro-fuzzy technique uses the MMM chemistry, pressure, and temperature to estimate CO₂ permeability. Indeed, grid partitioning (GP), fuzzy C-means (FCM), and subtractive clustering (SC) strategies are used to divide the input space of ANFIS. Statistical analyses compare the performance of these strategies, and the spider graph technique selects the best one. As a result of the prediction of more than 100 experimental samples, the ANFIS with the subtractive clustering method shows better accuracy than the other classes. The hybrid optimization algorithm and cluster radius = 0.55 are the best hyperparameters of this ANFIS model. This neuro-fuzzy model predicts the experimental database with an absolute average relative deviation (AARD) of less than 3% and a correlation of determination higher than 0.995. Such an intelligent model is not only straightforward but also helps to find the best MMM chemistry and operating conditions to maximize CO₂ separation.

Biopolymer-Based Mixed Matrix Membranes (MMMs) for CO2/CH4 Separation: Experimental and Modeling Evaluation

Alternative materials are needed to tackle the sustainability of membrane fabrication in light of the circular economy, so that membrane technology keeps playing a role as sustainable technology in CO2 separation processes. In this work, chitosan (CS)-based mixed matrix thin layers have been coated onto commercial polyethersulfone (PES) supports. The CS matrix was loaded by non-toxic 1-Ethyl-3-methylimidazolium acetate ionic liquid (IL) and/or laminar nanoporous AM-4 and UZAR-S3 silicates prepared without costly organic surfactants to improve CO2 permselectivity and mechanical robustness. The CO2/CH4 separation behavior of these membranes was evaluated experimentally at different feed gas composition (CO2/CH4 feed mixture from 20:80 to 70:30%), covering different separation applications associated with this separation. A cross-flow membrane cell model built using Aspen Custom Modeler was used to validate the process performance and relate the membrane properties with the target objectives of CO2 and CH4 recovery and purity in the permeate and retentate streams, respectively. The purely organic IL-CS and mixed matrix AM-4:IL-CS composite membranes showed the most promising results in terms of CO2 and CH4 purity and recovery. This is correlated with their higher hydrophilicity and CO2 adsorption and lower swelling degree, i.e., mechanical robustness, than UZAR-S3 loaded composite membranes. The purity and recovery of the 10 wt.% AM-4:IL-CS/PES composite membrane were close or even surpassed those of the hydrophobic commercial membrane used as reference. This work provides scope for membranes fabricated from renewable or biodegradable polymers and non-toxic fillers that show at least comparable CO2/CH4 separation as existing membranes, as well as the simultaneous feedback on membrane development by the simultaneous correlation of the process requirements with the membrane properties to achieve those process targets.

Recent Progress of SAPO-34 Zeolite Membranes for CO2 Separation: A Review

In the zeolite family, the silicoaluminophosphate (SAPO)-34 zeolite has a unique chemical structure, distinctive pore size, adsorption characteristics, as well as chemical and thermal stability, and recently, has attracted much research attention. Increasing global carbon dioxide (CO₂) emissions pose a serious environmental threat to humans, animals, plants, and the entire environment. This mini-review summarizes the role of SAPO-34 zeolite membranes, including mixed matrix membranes (MMMs) and pure SAPO-34 membranes in CO₂ separation. Specifically, this paper summarizes significant developments in SAPO-34 membranes for CO₂ removal from air and natural gas. Consideration is given to a variety of successes in SAPO-34 membranes, and future ideas are described in detail to foresee how SAPO-34 could be employed to mitigate greenhouse gas emissions. We hope that this study will serve as a detailed guide to the use of SAPO-34 membranes in industrial CO₂ separation.

n-Octyltrichlorosilane Modified SAPO-34/PDMS Mixed Matrix Membranes for Propane/Nitrogen Mixture Separation

In this study, zeolite molecular sieve SAPO-34/polydimethylsiloxane (PDMS) mixed matrix membranes (MMMs) were prepared to recover propane. n-Octyltrichlorosilane (OTCS) was introduced to improve compatibility between SAPO-34 and PDMS, and enhance the separation performance of the MMMs. Physicochemical properties of the MMMs were characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD) and water contact angle (WCA). Results showed that, after modification, alkyl chains were successfully grafted onto SAPO-34 without changing its crystal structure, particles in the MMMs were evenly distributed in the base film, and the hydrophobicity of the MMMs was enhanced. Moreover, the effects of SAPO-34 filling content, operating pressure, and feed gas concentration on the separation performance was explored. This indicated that the modification with OTCS effectively enhanced the separation performance of SAPO-34/PDMS MMMs. When the filling content of modified SAPO-34 was 15%, the maximal separation factor of 22.1 was achieved, and the corresponding propane permeation rate was 101 GPU.

Environmental management of industrial decarbonization with focus on chemical sectors: A review

A considerable portion of fossil CO₂ emissions comes from the energy sector for production of heat and electricity. The industrial sector has the second order in emission in which the main parts are released from energy-intensive industries, namely metallurgy, building materials, chemicals, and manufacturing. The decarbonization of industrial wastes contemplates the classic decarbonization through optimization of conventional processes as well as utilization of renewable energy and resources. The upgrading of existing processes and integration of the methodologies with a focus on efficiency improvement and reduction of energy consumption and the environment is the main focus of this review. The implementation of renewable energy and feedstocks, green electrification, energy conversion methodologies, carbon capture, and utilization, and storage are also covered. The main objectives of this review are towards chemical industries by introducing the potential technology enhancement at different subsectors. For this purpose, state-of-the-art roadmaps and pathways from the literature findings are presented. Both common and innovative renewable attempts are needed to reach out both short- and long-term deep decarbonization targets. Even though all of the innovative solutions are not economically viable at the industrial scale, they play a crucial role during and after the energy transition interval.

A high-throughput screening of metal-organic framework based membranes for biogas upgrading

Applications of biomethane as a source of renewable energy and transport fuel rely heavily on successful implementation of purification methods capable of removing undesirable impurities from biogas and increasing its calorific content. Metal-organic frameworks (MOFs) are competitive candidates for biogas upgrading due to a versatile range of attractive physical and chemical properties which can be utilised in membrane materials. In this work, we present a high-throughput computational screening methodology for efficient identification of MOF structures with promising gas separation performance. The proposed screening strategy is based on initial structural analysis and predictions of the single-component permeation of CO₂, CH₄ and H₂S from adsorption and diffusion calculations at infinite dilution. The identified top performing candidates are subject to further analysis of their gas separation performance at the operating conditions of 10 bar and 298 K, using grand canonical Monte Carlo and equilibrium molecular dynamics simulations on equimolar CO₂/CH₄ and H₂S/CH₄ mixtures. The Henry constant for the adsorption of H₂O was also calculated to determine the hydrophobicity of MOF structures, as the presence of H₂O often leads to membrane instability and performance limitations. For the considered gas mixtures, the top MOF candidates exhibit superior separation capabilities over polymer-, zeolite-, and mixed matrix-based membranes as indicated by the predicted values of selectivity and permeability. The proposed screening protocol offers a powerful tool for the rational design of novel MOFs for biogas upgrading.

Ultrahigh Carbon Dioxide-Selective Composite Membrane Containing a γ-CD-MOF Layer

Mixed matrix membranes (MMMs) for CO₂ separation have overcome the trade-off between gas permeability and gas selectivity to some extent. However, most MMMs still are prepared in lab- and pilot-scales since the permeability and selectivity of CO₂ are not good enough to reach the economically available requirements. Moreover, the fabrication of few MMMs with good separation performance is time-consuming or need harsh conditions. In this study, a novel MOF-based composite membrane (PAN-γ-CD-MOF-PU membrane) was successfully fabricated by a facile and fast spin-coating method. In the two-step coating process, we applied a uniform selective layer of γ-cyclodextrin-MOF (γ-CD-MOF) on porous polyacrylonitrile and then coated a layer of polyurethane on the γ-CD-MOF layer. The entire membrane formation process was about 30 s. The formation of a unique γ-CD-MOF layer greatly improved the separation ability of CO₂ (the CO₂ permeability is 70.97 barrers; the selectivity to CO₂/N₂ and CO₂/O₂ are 253.46 and 154.28, respectively). The gas separation performance can exceed the Robeson upper limit obviously and the selectivity is better than other MOF-based composite membranes. In addition, the PAN-γ-CD-MOF-PU membrane is strong and flexible. Therefore, the PAN-γ-CD-MOF-PU membrane developed in this study has great potential in large-scale industrial separation of CO₂.

Greenhouse Gas Emissions from Solid Waste Management in Saudi Arabia—Analysis of Growth Dynamics and Mitigation Opportunities

The continuous growth in population, urbanization, and industrial development has been increasing the generation of solid waste (SW) in the Kingdom of Saudi Arabia. Consequently, the associated greenhouse gas (GHG) emission is also following an increasing trend. The collection and use of greenhouse gases emitted from solid waste management practices are still limited. A causality analysis examined the driving factors of the emissions from solid waste management. The methane (CH4) emissions from municipal solid waste (MSW) increased with an increase in gross domestic product (GDP) per capita and urban population, and an increase in foreign direct investment (FDI) inflows and literacy rate was likely to reduce CH4 emissions from municipal solid waste and vice versa. The CH4 emission generated from industrial solid wastes was found to be positively related to GDP per capita, urban population, and FDI inflows. However, a decrease in the unemployment rate was likely to increase CH4 emissions from industrial solid wastes. The future greenhouse gas emissions were projected under different possible socio-economic conditions. The scenario analysis based on different variations of population and GDP growth revealed that methane emission from total waste would increase at an average annual rate of 5.13% between 2020 and 2050, and is projected to reach about 4000 Gg by the end of the year 2050. Although the Kingdom has been taking some initiatives towards climate change mitigation, it has significant opportunities to adopt some of the best practices in solid waste management including reduction, recycling, composting and waste-to-energy, and carbon capture and utilization. This study also put emphasis on developing appropriate policy approaches for climate change mitigation based on the circular economy which is gaining momentum in the Kingdom.

Improving the Gas-Separation Properties of PVAc-Zeolite 4A Mixed-Matrix Membranes through Nano-Sizing and Silanation of the Zeolite

Mixed-matrix membranes containing synthesised nano-sized zeolite 4A and PVAc were fabricated to investigate the effect of zeolite loading on membrane morphology, polymer-filler interaction, thermal stability and gas separation properties. SEM studies revealed that, although the membranes with 40 wt % nano-sized zeolite particles were distributed uniformly through the polymer matrix without voids, the membranes with 15 wt % zeolite loading showed agglomeration. With increasing zeolite content, the thermal stability improved, the permeability decreased and the selectivity increased. The effect of silanation on dispersion of 15 wt % zeolite 4A nanoparticles through PVAc was investigated by post-synthesis modification of the zeolite with 3-Aminopropyl(diethoxy)methylsilane. Modification of the nanoparticles improved their dispersion in PVAc, resulting in higher thermal stability than the corresponding unmodified zeolite membrane. Modification also decreased the rigidity of the membrane. Partial pore blockage of the modified zeolite nanoparticles after silanation caused a further decrease in permeability, compared to the 15 wt % unmodified zeolite membrane.

Ethylene glycol elimination in amine loop for more efficient gas conditioning

The gas sweetening unit of phase 2 and 3 in South Pars Gas Field (Asalouyeh, Iran) was first simulated to investigate the effect of mono ethylene glycol (MEG) in the amine loop. MEG is commonly injected into the system to avoid hydrate formation while a few amounts of MEG is usually transferred to amine gas sweetening plant. This paper aims to address the points where MEG has negative effects on gas sweetening process and what the practical ways to reduce its effect are. The results showed that in the presence of 25% of MEG in amine loop, H₂S absorption from the sour gas was increased from 1.09 to 3.78 ppm. Also, the reboiler temperature of the regenerator (from 129 to 135 °C), amine degradation and required steam and consequently corrosion (1.10 to 17.20 mpy) were increased. The energy consumption and the amount of amine make-up increase with increasing MEG loading in amine loop. In addition, due to increasing benzene, toluene, ethylbenzene and xylene (BTEX) and heavy hydrocarbon solubility in amine solution, foaming problems were observed. Furthermore, side effects of MEG presence in sulfur recovery unit (SRU) such as more transferring BTEX to SRU and catalyst deactivation were also investigated. The use of total and/or partial fresh MDEA, install insulation and coating on the area with the high potential of corrosion, optimization of operational parameters and reduction of MEG from the source were carried out to solve the problem. The simulated results were in good agreement with industrial findings. From the simulation, it was found that the problem issued by MEG has less effect when MEG concentration in lean amine loop was kept less than 15% (as such observed in the industrial plant). Furthermore, the allowable limit, source and effects of each contaminant in amine gas sweetening were illustrated.

Application of neural networks in membrane separation

Artificial neural networks (ANNs) as a powerful technique for solving complicated problems in membrane separation processes have been employed in a wide range of chemical engineering applications. ANNs can be used in the modeling of different processes more easily than other modeling methods. Besides that, the computing time in the design of a membrane separation plant is shorter compared to many mass transfer models. The membrane separation field requires an alternative model that can work alone or in parallel with theoretical or numerical types, which can be quicker and, many a time, much more reliable. They are helpful in cases when scientists do not thoroughly know the physical and chemical rules that govern systems. In ANN modeling, there is no requirement for a deep knowledge of the processes and mathematical equations that govern them. Neural networks are commonly used for the estimation of membrane performance characteristics such as the permeate flux and rejection over the entire range of the process variables, such as pressure, solute concentration, temperature, superficial flow velocity, etc. This review investigates the important aspects of ANNs such as methods of development and training, and modeling strategies in correlation with different types of applications [microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), reverse osmosis (RO), electrodialysis (ED), etc.]. It also deals with particular types of ANNs that have been confirmed to be effective in practical applications and points out the advantages and disadvantages of using them. The combination of ANN with accurate model predictions and a mechanistic model with less accurate predictions that render physical and chemical laws can provide a thorough understanding of a process.

Wastewaters treatment containing phenol and ammonium using aerobic submerged membrane bioreactor

Phenolic wastewater was treated using anaerobic submerged membrane bioreactor (ASMBR). Effect of different solids retention times on MBR performance was studied. Various ratios of carbon to nitrogen were used in the synthetic wastewaters. During the operation, phenol concentration of feed was changed from 100 to 1000 mg L^-1. Phenol concentration was increased stepwise over the first 30 days and kept constant at 1000 mg L^-1, thereafter. For the first 100 days, a chemical oxygen demand (COD) to N ratio of 100:5.0 was used and this resulted in phenol and COD removal more than 99 and 95%, respectively. However, the ammonium removal decreased from 95 to 40% by increasing the phenol concentration of feed, from 100 to 1000 mg L^-1. For the last 25 days, a COD to N ratio of 100:2.1 was used due to the ammonium accumulation in the ASMBR. This led to the complete ammonium removal and no ammonium was detected in the ASMBR permeate. These results suggest that in the ASMBR at high phenol loading of 1000 mg L^-1, COD to N ratio of the phenolic wastewater must be 100:2.1 for ammonium removal, while at low phenol loading, COD to N ratio of 100:5.0 can be used.