Search Results (10)

CO₂ separation is an important environmental method mainly used in reducing CO₂ emissions to mitigate anthropogenic climate change. The use of mixed-matrix membranes (MMMs) arrives as a possible answer, combining the high selectivity of inorganic membranes with high permeability of organic membranes. However, the combination of these materials is challenging due to their opposing nature, leading to poor interactions between polymeric matrix and inorganic fillers. Many additives have been tested to reduce interfacial voids, some of which showed potential in dealing with compatibility problems, but most of them lack further studies and optimization. Deep eutectic solvents (DESs) have emerged as IL substitutes since they are cheaper and environmentally friendly. Choline chloride-based deep eutectic solvents were studied as additives in polyethersulfone (PES)/SAPO-34 membranes to improve CO₂ permeability and CO₂/N₂ and CO₂/CH₄ selectivity. SAPO-34 crystals of 150 nm with a high surface area and microporosity were synthesized using dry-gel methodology. The PES/SAPO-34 membranes were optimized following previous work and used in a defined composition, using 5 or 10 w/w% of DES during membrane preparation. All MMMs were characterized by their ideal gas permeability using N₂ and CO₂ pure gasses. Selected membranes were also tested using CH₄ pure gas. The results presented that 5 w/w%, in polymer mass, of ChCl–glycerol presented the best result over the synthesized membranes. An increase of 200% in CO₂ permeability maintains the CO₂/N₂ selectivity for the non-modified PES/SAPO-34 membrane. A CO₂/CH₄ selectivity of 89.7 was obtained in PES/SAPO-34/ChCl-glycerol membranes containing 5 w/w% of this DES, which is an outstanding ideal separation performance for MMMs when compared to other results in the literature. FTIR analysis reiterates the presence of glycerol in the membranes prepared. Dynamic Mechanical Thermal Analysis (DMTA) shows that the addition of 5 w/w% of DES does not impact the membrane flexibility or polymer structure. However, in concentrations higher than 10 w/w%, the inclusion of DES could lead to high membrane rigidification without impacting the overall thermal resistance. SEM analysis of DES-enhanced membranes presented asymmetric final membranes and reaffirmed the results obtained in DMTA about rigidified structures and lower zeolite–polymer interaction with higher concentrations of DES. Full article

In this study, we investigate the influence of cold-plasma-induced enhanced performance and efficiency of SAPO-34 membranes in the separation of CO₂ and CH₄ mixtures. Placing the herein presented research in a broader context, we aim to address the question of whether cold plasma can significantly impact the membrane performance. We subjected SAPO-34 membranes to plasma mild disturbances and analyzed their performance in separating CO₂ and CH₄. Our findings reveal a notable enhancement in membrane efficiency and sustained performance when exposed to cold plasma. The pulsed plasma separation displayed improved structural integrity, and the experimental results indicated that the linear structure of CO₂ facilitates the distortion of electron clouds in response to the electric field, a property known as polarizability, which aids in effective separation. Plausible mechanistic insight indicated that the intermolecular forces facilitated an integral role in SAPO-34 membranes exhibiting strong electrostatic interactions. In conclusion, our research highlights the potential of cold plasma as a promising technique for improving the performance of SAPO-34 membranes in gas mixtures at atmospheric pressures, providing valuable insights for optimizing membrane technology in carbon capture and gas separation applications. Full article

The use of ionic liquid [emim][Tf₂N] as an additive in polyethersulphone (PES) and nano-sized silico-aluminophosphate-34 (SAPO-34) mixed matrix membrane was studied through the incorporation of different amounts of [emim][Tf₂N] in the membrane composition, as presented in this work, varying from 10 to 40 wt%. Through gas permeation tests using CO₂ and N₂, the membrane composition containing 20 wt% [emim][Tf₂N] led to the highest increase in CO₂ permeability and CO₂/N₂ selectivity. The use of low concentrations of additive (10–20 wt%) promoted a state called antiplasticization; in this state, the permeability was even more regulated by the kinetic diameter of the species which, in this work, permitted achieving a higher CO₂/N₂ selectivity while increasing the CO₂ permeability until an optimal condition. [emim][Tf₂N] also promoted a better dispersion of SAPO-34 particles and an increase in the flexibility of the polymeric matrix when compared to a film with the same composition without [emim][Tf₂N]. Moreover, the characterizations corroborated that the inclusion of [emim][Tf₂N] increased the zeolite dispersion and improved the polymer/zeolite compatibility and membrane flexibility, characterized by a decrease in glass transition temperature, which helped in the fabrication process while presenting a similar thermal resistance and hydrophilicity as neat PES membrane, without affecting the membrane structure, as indicated by FTIR and a contact angle analysis. Full article

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). Full article

Membrane technology, particularly polymeric membranes, is utilized in major industrial ethylene recovery owing to the very convenient and robust process. Thus, in this paper, a composite membrane (CM) comprising SAPO-34 and Pebax-1657 was employed to conduct a separation performance under two operating conditions, including temperatures and pressures, ranging from 25.0–60.0 °C and 3.5–10.0 bar, respectively. CO₂ permeability and CO₂/C₂H₄ ideal selectivity values that ranged from 105.68 to 262.86 Barrer and 1.81 to 3.52, respectively, were obtained via the experimental works. The separation of carbon dioxide (CO₂) from ethylene (C₂H₄) has then been optimized using response surface methodology (RSM) by adopting a central composite design (CCD) method. As a result, the ideal operational conditions were discovered at a temperature of 60.0 °C and pressure of 10.0 bar with the maximum CO₂ permeability of 233.62 Barrer and CO₂/C₂H₄ ideal selectivity of 3.22. The typical discrepancies between experimental and anticipated data for CO₂ permeability and CO₂/C₂H₄ ideal selectivity were 1.67% and 3.10%, respectively, demonstrating the models’ validity. Overall, a new combination of Pebax-1657 and SAPO-34 composite membrane could inspire the latest understanding of the ethylene recovery process. Full article

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. Full article

CO₂/H₂ separation using membrane technology is an important research area in order to obtain high purity hydrogen as one source of clean energy. Finding a suitable inorganic membrane is one of the critical issues, which needs to be explored for CO₂/H₂ separation. In the present study, Ba-SAPO-34 zeolite membrane was synthesized and followed by a modification process. CO₂/H₂ separation of the membrane was investigated by varying the independent process variables (CO₂ % in the feed, pressure difference across the membrane and temperature). Modeling and optimization for the responses (CO₂/H₂ separation selectivity and CO₂ permeance) was performed by applying response surface methodology and central composite design, which is available in Design Expert software. The accuracy of the models in predicting the response was tested by comparing with the experimental value of response and the two values were in good agreement. The optimization of the models gave CO₂ permeance of 19.23 × 10⁻⁷ mol/m² s Pa and CO₂/H₂ separation selectivity of 11.6 at 5% CO₂ in the feed, a pressure difference of 100 kPa, and temperature of 30 °C for Ba-SAPO-34 zeolite membrane. Full article

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. Full article

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. Full article

Three different zeolite nanocrystals (SAPO-34, PS-MFI and ETS-10) were incorporated into the polymer matrix (Matrimid^® 5218) as polymer precursors, with the aim of fabricating mixed-matrix carbon molecular sieve membranes (CMSMs). These membranes are investigated for their potential for air separation process. Based on our gas permeation results, incorporating porous materials is feasible to improve O₂ permeability, owing to the creation of additional porosities in the resulting mixed-matrix CMSMs. Owing to this, the performance of the CMSM with 30 wt% PS-MFI loading is able to surpass the upper bound limit. This study demonstrates the feasibility of zeolite nanocrystals in improving O₂/N₂ separation performance in CMSMs. Full article