Research Articles (Chemical Engineering)

Permanent URI for this collectionhttp://hdl.handle.net/2263/1691

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Surface engineered NiFe2O4/SnO2/CeO2 ternary heterojunction for dual applications in photocatalytic water treatment and supercapacitors
Oluwole, Adewunmi Olufemi; Sarr, Samba; Yusuf, Tunde Lewis; Tichapondwa, Shepherd Masimba; Daramola, Michael Olawale; Iwarere, Samuel Ayodele (Royal Society of Chemistry, 2025-11)
Please read abstract in the article.
Synergistic removal of hazardous dyes using a clay/carbon composite derived from spent bleaching earth : optimization using response surface methodology
Madhau , Freeman; Wu, Zhenjun; Shi, Yahui; Guo, Dongli; Wan, Dongjin; Tichapondwa, Shepherd Masimba; Wang , Yangyang; Chisadza, Bright; Zhu, Beibei (MDPI, 2025-04-17)
Industrial wastewater contains complex pollutants, including toxic dyes, necessitating effective and sustainable remediation strategies. Conventional treatment methods often struggle to remove multiple dyes simultaneously, underscoring the need for innovative adsorbents. This study investigated a clay/carbon composite (SBE/C (500 °C)) derived from spent bleaching earth (SBE) via pyrolysis for the simultaneous removal of methylene blue (MB) and malachite green (MG) dyes. The pyrolysis process significantly enhanced the specific surface area of SBE, improving its adsorption capacity. Using the Box–Behnken design (BBD) and response surface methodology (RSM), we optimized key parameters (pH, contact time, and dosage) at 45 °C and an initial dye concentration of 20 mg/L. The developed quadratic model demonstrated high predictive accuracy, with experimental results closely aligning with predictions (R2 = 0.9983 for MB, 0.9955 for MG), along with strong adjusted (R2 = 0.9962 for MB, 0.9896 for MG) and predicted (R2 = 0.9811 for MB, 0.9275 for MG) values. Under optimal conditions, the maximum adsorption capacities reached 27.77 mg/g for MB and 27.38 mg/g for MG. These findings highlight the potential of SBE/C (500 °C) as a sustainable and cost-effective adsorbent for the simultaneous removal of MB and MG from wastewater, offering a promising solution for environmental remediation.
Dimer fatty acid-based polyamide/organoclays : structural, thermal properties, and statistical analysis of factors affecting polymer chain intercalation in bentonite layers
Macheca , Afonso D.; Microsse, Diocrecio N.; Mujuri , Theophile M.; Tewo, Robert Kimutai; Mapossa, António Benjamim; Tichapondwa, Shepherd Masimba (MDPI, 2025-07-25)
This work investigates the potential industrial applications of two sodium bentonite samples (white and yellow), obtained from raw Ca-rich bentonite from Maputo Province in Southern Mozambique. Bentonite bio-organoclays were successfully developed from two Mozambican montmorillonite clays through the intercalation of protonated dimer fatty acid-based polyamide chains using a solution casting method. X-ray diffraction (XRD) analysis confirmed polymer intercalation, with the basal spacing (d001) increasing from approximately 1.5 nm to 1.7 nm as the polymer concentration varied between 2.5 and 7.5 wt.%. However, the extent of intercalation was limited at this stage, suggesting that polymer concentration alone had a minimal effect, likely due to the formation of agglomerates. In a subsequent optimization phase, the influence of temperature (30–90 °C), stirring speed (1000–2000 rpm), and contact time (30–90 min) was evaluated while maintaining a constant polymer concentration. These parameters significantly enhanced intercalation, achieving d001 values up to 4 nm. Statistical Design of Experiments and Response Surface Methodology revealed that temperature and stirring speed exerted a stronger influence on d001 expansion than contact time. Optimal intercalation occurred at 90 °C, 1500 rpm, and 60 min. The predictive models demonstrated high accuracy, with R2 values of 0.9861 for white bentonite (WB) and 0.9823 for yellow bentonite (YB). From statistical modeling, several key observations emerged. Higher stirring speeds promoted intercalation by enhancing mass transfer and dispersion; increased agitation disrupted stagnant layers surrounding the clay particles, facilitating deeper penetration of the polymer chains into the interlayer galleries and preventing particle settling. Furthermore, the ANOVA results showed that all individual and interaction effects of the factors investigated had a significant influence on the d001 spacing for both WB and YB clays. Each factor exhibited a positive effect on the degree of intercalation.
An activatable photoacoustic probe for precise hydrazine detection in biological and environmental systems
Jiang, Jiahui; Zeng, Sha; Li, Xiang; Chen, Ke; Sun, Yu Yan; Qiao, Lei; Ren, Jianwei; Liu, Xianjun; Zhang, Chonghua; Zhou, Hu (Elsevier, 2026-01)
Hydrazine (N₂H₄) is a widely used raw material in pesticide manufacturing. Its high water solubility raises concerns because it can contaminate water sources and enter living organisms, leading to significant health issues. Current methods for detecting N2H4 face challenges such as complex procedures, poor biocompatibility, shallow penetration depth, inadequate temporal and spatial resolution. Photoacoustic (PA) imaging is an innovative biomedical imaging technique that detects sound waves rather than photons following light stimulation, enabling non-invasive visualization of biological processes within deep tissues at high spatial resolution. Here, we present an activatable PA probe (SH-ONS) for sensitive and selective detection of N₂H₄. This thoughtfully engineered probe incorporates a sulfur-substituted hemicyanine dye (SH-OH) as the PA reporter and features a 4-nitrobenzenesulphonate group as the recognition element. The designed probe SH-ONS achieves a low detection limit of 0.15 μM, a high PA signal-to-background ratio of 10.8-fold, and excellent selectivity in vitro. The probe was successfully applied to visualize exogenous N₂H₄ in living mice and to detect N₂H₄ in real environmental water samples, in both cases showing dose-dependent PA responses. This work demonstrates that SH-ONS is a robust and versatile tool for monitoring N₂H₄ across biological and environmental contexts. HIGHLIGHTS • An activatable photoacoustic probe (SH-ONS) for N2H4 detection was developed. • SH-ONS achieved a 0.15 μM detection limit and a 10.8-fold activation fold. • SH-ONS achieved precise N2H4 detection in biological and environmental systems.
Rare-earth-induced intermediate-spin co centers in MnCo2O4.5 for sustainable acidic water oxidation
Li, Meng; Yang, Juan; Li, Shaoxiong; Deng, Liming; Zhao, Sheng; Li, Linlin; Hung, Sung-Fu; Xing, Gengyu; Wang, Tao; Liang, Yanyu; Ren, Jianwei; Wu, Yuping; Peng, Shengjie (American Chemical Society, 2025-11)
Please read abstract in the article.
Reductive degradation of Congo red dye in aqueous solution using recyclable polyaniline@Co(OH)2 nanocomposites
Bhaumik, Madhumita; Maity, Arjun; Brink, Hendrik Gideon (Elsevier, 2025-11)
Please read abstract in the article.
Groundwater vulnerability under climate change : a machine learning framework
Abu El-Magd, Sherif; Masoud, Ahmed M.; Brink, Hendrik Gideon; Hlawitschka, Mark W.; Maged, Ali (Springer, 2025)
Groundwater quality assessment is essential for sustainable water management but remains challenging owing to hydrogeological complexity, climate variability, and anthropogenic pressures. This study evaluates groundwater quality in the East Nile River region of Sohag, Egypt, by integrating hydrochemical parameters with machine learning (ML) approaches. The aim is to identify spatial contamination risks, assess water suitability, and explore the implications of environmental change. In total, 78 groundwater samples were collected and analyzed for 15 hydrochemical and ion-derived parameters. Two ML algorithms, Artificial Neural Networks (ANN) and Extreme Gradient Boosting (XGBoost), were applied, with datasets divided into training (70%) and testing (30%) subsets. The models generated probability maps of groundwater vulnerability, highlighting central areas, particularly near agricultural zones with shallow water tables, as most at risk. ANN outperformed XGBoost (R² = 0.89 vs. 0.86), demonstrating higher predictive accuracy for groundwater quality assessment. Spatial variability was linked to hydrogeological processes and intensified urban and agricultural activities, while climate-related stressors are expected to exacerbate groundwater deterioration. The proposed ML framework provides a reliable, cost-effective tool for groundwater monitoring and early warning, supporting improved decision-making for water sustainability. These findings contribute to global efforts toward SDG 6 (Clean Water and Sanitation), SDG 12 (Responsible Consumption and Production), and SDG 13 (Climate Action).
Oxidative stability of edible oils: linking rancimat to PDSC results
Diaz-Diaz, Ana-Maria; Lopez-Beceiro, Jorge Jose; Diaz, Ramon Pedro Artiaga; Augustyn, Wilma; Van der Westhuizen, Isbe; Focke, Walter Wilhelm; Focke, Walter Wilhelm (Springer, 2025)
Please read abstract in the article.
The phosphorus negotiation game (P-Game): first evaluation of a serious game to support science-policy decision making played in more than 20 countries worldwide
Haneklaus, Nils; Kaggwa, Mary; Misihairabgwi, Jane; Abu El-Magd, Sherif; Ahmadi, Naima; Ait Brahim, Jamal; Amasi, Aloyce; Kovacs, Andrea Ballane; Bartela, Lukasz; Bellefqih, Hajar; Beniazza, Redouane; Bernas, Jaroslav; Bilal, Essaid; Bituh, Tomislav; Chernysh, Yelizaveta; Chubur, Viktoriia; Ciric, Jelena; Dolezal, Claudia; Figulova, Andrea; Filipi, Janja; Glavan, Gordana; Guzsvinecz, Tibor; Horvath, Laszlo; Josimovski, Sasho; Kiselicki, Martin; Lazarus, Maja; Kazazic, Maja; Komlosi, Istvan; Maged, Ali; Mashifana, Tebogo; Medunic, Gordana; Mehic, Emina; Mongi, Felhi; Mtei, Kelvin; Mwalongo, Dennis; Mwimanzi, Jerome M.; Nowak, Jakub; Basal, Oqba; Qamouche, Khaoula; Rajfur, Malgorzata; Roubik, Hynek; Santa, Mijalche; Sik-Lanyi, Cecilia; Sippel, Maike; Steiner, Gerald; Skorek-Osikowska, Anna; Slavov, Anton; Swislowski, Pawel; Tlili, Ali; Trenevska-Blagoeva, Kalina; Tschalakov, Ivan; Vlcek, Tomas; Waclawek, Stanislaw; Zlatanovic, Ivan; Misik, Matus; Brink, Hendrik Gideon; Lee, Tzong-Ru (Springer, 2025-01)
Environmental negotiations are complex, and conveying the interaction between science and policy in traditional teaching methods is challenging. To address this issue, innovative educational approaches like serious gaming and role-playing games have emerged. These methods allow students to actively explore the roles of different stakeholders in environmental decision-making and weigh for instance between sometimes conflicting UN Sustainable Development Goals or other dilemmas. In this work the phosphorus negotiation game (P-Game) is for the first time introduced. We present the initial quantitative and qualitative findings derived from engaging 788 students at various academic levels (Bachelor, Master, PhD, and Postdoc) across three continents and spanning 22 different countries. Quantitative results indicate that female participants and MSc students benefitted the most significantly from the P-Game, with their self-reported knowledge about phosphorus science and negotiation science/practice increasing by 71–93% (overall), 86–100% (females), and 73–106% (MSc students in general). Qualitative findings reveal that the P-Game can be smoothly conducted with students from diverse educational and cultural backgrounds. Moreover, students highly value their participation in the P-Game, which can be completed in just 2–3 h. This game not only encourages active engagement among participants but also provides valuable insights into the complex environmental issues associated with global phosphorus production. We strongly believe that the underlying methodology described here could also be used for other topics. HIGHLIGHTS • The Phosphorus Negotiation Game (P-Game) is for the first time introduced. • First results from playing in 22 countries with 788 participants are presented. • The P-Game can be played well with participants from various backgrounds.
Marine bioassay acceptability for determining the effects of different emerging contaminants on the marine organism Haliotis midae of South Africa
Venter, Somien; Witte, Andrew; Haneklaus, Nils; Brink, Hendrik Gideon; Chirwa, Evans M.N. (Springer, 2025-10)
The presence of emerging contaminants (ECs) in South Africa’s marine coastal waters has received increasing attention, yet their ecotoxicological effects on indigenous species remain poorly understood. A major gap in monitoring is the absence of a standardised marine bioassay protocol. Although South Africa’s National Toxicity Monitoring Programme (NTMP) outlines water quality assessment for inland waters, it excludes marine ecosystems. In contrast, the United States Environmental Protection Agency (USEPA) recommends Haliotis rufescens for Whole Effluent Toxicity (WET) assessments. This study adapts the USEPA WET protocol for South African conditions by employing Haliotis midae, an economically important abalone species native to South Africa. A reference toxicant test with zinc sulphate was conducted, followed by exposures to five ECs commonly detected in South African coastal waters: Acetaminophen, Atrazine, Benzotriazole, Carbamazepine, and Emtricitabine. Toxicity tests at 100 µg/L, 50 µg/L, and 25 µg/L for each EC revealed significant developmental impairments at all concentrations, including the lowest tested. These effects occurred at levels comparable to reported environmental concentrations, underscoring H. midae’s high sensitivity to ECs. The bioassay met all USEPA acceptability criteria, confirming robustness, reproducibility, and environmental relevance. Zinc testing further validated H. midae as a suitable bioassay organism. This standardised, locally relevant assay offers a valuable tool for marine ecotoxicology in South Africa, with potential integration into national monitoring programmes. The work supports United Nations Sustainable Development Goals SDG 6 (Clean Water and Sanitation), SDG 14 (Life below Water), and SDG 15 (Life on Land) by advancing capabilities for monitoring and protecting aquatic ecosystems from emerging pollutants.
Hydrothermal synthesis of Aragonite from acid mine drainage (AMD) of the Witwatersrand basin in Gauteng, South Africa
Khumalo, Recardo D.S.; Brink, Hendrik Gideon; Chirwa, Evans M.N. (Elsevier, 2025-12)
Hydrothermal urea hydrolysis has been extensively used for homogenous precipitation processes mainly because the resulting products are generally of high crystallinity, uniform particle size and shape, as well as not generating waste brine. In this study, acid mine drainage water samples from the three Witwatersrand goldfields basins (Eastern, Central and Western, Gauteng, South Africa) were subjected to hydrothermal urea hydrolysis to investigate if any mineral(s) could be recovered. In these experiments, three urea concentrations (3.3, 4.0 and 10.0 [urea]/[total metal] ratio) were used while the reaction time (3 h) and temperature (80 °C) were kept constant. The resulting materials were characterised to reveal their chemical compositions, crystalline phases and morphologies. The bulk properties as determined using the Fourier Transform Infrared Spectroscopy, Thermogravimetric Analysis and X-ray Diffraction Spectroscopy showed that the obtained products were predominantly calcium carbonate, the aragonite polymorph, for all three basins. The particles obtained from the polluted mine water samples displayed different morphologies, while mostly were characterised by needle and/or rod-like morphologies with varying lengths and diameters in nanometre range (average aspect ratios ranged from 3.1 to 13.2) as shown by the Scanning Electron Microscope images. Other morphologies, cauliflower-, bouquet- and urchin-like particles were obtained without the use of organic additives. The method was demonstrated to be effective in the removal of calcium (more than 98 % on average) and some evidence of heavy metals, manganese in particular, also being removed from the polluted water. The findings highlighted a possibility of a single method that can be adopted for the remediation of acid mine drainage of the three basins to recover aragonite calcium carbonate, an industrially valuable mineral. HIGHLIGHTS • Hydrothermal urea hydrolysis was used to treat acid mine drainage. • Aragonite CaCO3 was recovered from all three Witwatersrand gold field basins. • Diverse aragonite super-structures were obtained without utilising organic additives.
CO conversion to liquid fuel over a bi-functional Co/H-ZSM-5 catalyst: effect of support desilication and catalyst promotion
Mudau, Tsireledzo L.; Sadare, Olawumi Oluwafolakemi; Iwarere, Samuel Ayodele; Daramola, Michael Olawale (Taylor and Francis, 2025)
Please read abstract in the article.
Improving the thermal stability of fly ash-based geopolymer materials through cellulose nanocrystal reinforcement
Roopchund, Rishen; Fajimi, Lanrewaju; Seedat, Naadhira; Andrew, Jerome (Springer, 2025-12)
Prior to this study, the thermal stability of fly ash-based geopolymer (FAG) construction materials as a function of cellulose nanocrystal (CNC) concentration and the optimal CNC dosage leading to thermal stability have not been investigated. This study investigates the influence of CNC reinforcement and curing duration on the thermal stability of FAG geopolymer. A series of samples incorporating CNC dosages ranging from 0 to 1.86 wt.% were prepared and subjected to 24- and 48-h curing regimes to evaluate their thermal degradation behaviors. Thermogravimetric analysis (TGA) revealed that 24-h-cured samples exhibited steeper weight losses compared to 48-h-cured ones, particularly in the 100–600 ℃ range. This trend was attributed to incomplete stabilization of organics in shorter curing times. Among all dosages, the 48-h-cured 1.7 wt.% CNC sample demonstrated the lowest total weight loss (~ 9.6% lower than the control), indicating enhanced thermal resistance. Derivative weight analysis further confirmed this, showing the lowest peak weight change rate (0.105%/℃) for the 1.7 wt.% CNC sample cured for 48 h, compared to 0.304%/℃ for the unreinforced control. Additionally, differential scanning calorimetry (DSC) indicated reduced exothermic heat flow in 48-h-cured samples, especially in the 1.7 wt.% CNC formulation, suggesting minimal phase transitions and improved thermal reliability. The novelty of this work lies in demonstrating the synergistic enhancement of thermal resistance through CNC addition and extended curing. Unlike prior studies that primarily focused on mechanical reinforcement, this research establishes an optimal CNC dosage (1.7 wt%) that minimizes thermal degradation, offering critical insights for thermally stable, bio-reinforced geopolymer development. These findings support the application of CNC–geopolymer composites in fire-resistant, sustainable construction materials.
MXenes as sustainable functional nanomaterials for photocatalytic degradation of dye pollutants : performance, effect of process parameters, stability and re-useability evaluation – a critical review
Emmanuel, Stephen Sunday; Adesibikan, Ademidun Adeola; Tichapondwa, Shepherd Masimba; Rayaroth, Manoj P.; Boscá, Francisco; Marín, M. Luisa; Samejo, Bakhtiar Ali; Boczkaj, Grzegorz (Elsevier, 2025-12)
Please read abstract in the article. HIGHLIGHTS • Good MXENE stability and possibility of its regeneration for long-term applications. • Importance of scavenging tests and proper identification of radical species in the process. • Degradation studies must be evaluated, including the final mineralization rate of the pollutant. • Optimization of pollutant concentration must include the aspect of photocatalyst capacity. • Controversial, not confirmed, conclusions about CO2 formation during treatment.
Influence of carbon sources and biosurfactants on selenite and lead bioremediation by Enterococcus sp
Tendenedzai, Job Tatendan; Chirwa, Evans M.N.; Brink, Hendrik Gideon (Elsevier, 2026-01)
Please read abstract in the article.
Ultrahigh-efficiency zinc-air batteries enabled by defect-engineered biomass carbon and dynamic nickel redox mediation
Huang, Yongfa; Li, Tingzhen; Wu, Zhenzhen; Yang, Wu; Liu, Zhendong; Gan, Jianyun; Zou, Ren; Iwuoha, Emmanuel; Feleni, Usisipho; Ren, Jianwei; Ocakoglu, Kasim; Zhong, Linxin; Peng, Xinwen (Wiley, 2025)
Coupled zinc-air batteries (CZABs) are promising in future energy storage and conversion solutions because of their potential for enhanced energy efficiency and boosted power density. However, sluggish reaction kinetics at the cathode remain a key challenge, leading to cycling instability and insufficient battery performance. In this study, a rational interfacial etching method is developed to fabricate nitrogen-doped and defect-rich carbon catalysts from the low-cost eucalyptus waste. The precise formation of carbon vacancies, driven by synergistic spatial confinement domains and oxygen-containing functional groups exposed on eucalyptus precursors, promotes the reconstruction of pyridinic nitrogen (Py-N) coordination. This induces local electron redistribution, enhancing charge transfer efficiency at adjacent Py-N sites, and optimizing *O/*OH adsorption–desorption kinetics, thereby significantly boosting the electrocatalytic activity for the oxygen reduction reaction. Additionally, the integration of self-adaptive Ni2+/Ni3+ redox pair into the cathode effectively mitigates the oxygen evolution reaction and thus reduces voltage delay by 0.12 V. The resulting CZABs achieve 82% energy efficiency at 5 mA cm−2 and 77% after 400 h, which is rarely reported. This work elucidates the intricate mechanism of defect formation during biomass pyrolysis and presents a scalable, cost-effective strategy for producing high-efficiency catalysts, offering a promising strategy toward advanced energy storage systems.
Antibiotic removal in South African water using artificial neural networks and adaptive neuro-fuzzy inference system models : a review
Keitemoge, Molly Katlo; Onu, Matthew Adah; Sadare, Olawumi Oluwafolakemi; Seedat, Naadhira; Moothi, Kapil (Elsevier, 2025-10)
The growing occurrence of antibiotic residues in South African water systems poses serious environmental and public health risks, owing mostly to pharmaceutical discharge, agricultural runoff, and poor waste management. Conventional water treatment procedures frequently fail to properly remove these micropollutants, needing new predictive and analytical approaches. This review critically investigates the implementation of Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) models to forecast and optimize antibiotic removal from South African water bodies. To the best of our knowledge, little or no research compares the models’ respective performances in the context of the urban water cycle in South Africa. Therefore, this review elaborates on some of the pharmaceuticals (such as diclofenac sodium and tetracycline) that have been studied, as well as the challenges associated with their removal. It also emphasizes studies on modeling and predicting pharmaceutical removal from wastewater using ANN and ANFIS models. Additionally, this review considered the comparisons between ANN and ANFIS models in predicting the removal of emerging contaminants, as well as the challenges and limitations associated with these modeling techniques. The studies established that AI models achieved higher R² and lower error metrics compared to classical statistical or isotherm models.
Mixture models inspired by the Kolmogorov-Arnold representation theorem
Focke, Walter Wilhelm (Elsevier, 2025-10)
Physical property models were developed to predict temperature-dependent multicomponent data using only temperature-independent binary parameters and pure component property temperature dependence. The Kolmogorov-Arnold representation theory was used to extend the linear blending rules and the Padé-like expressions describing the variation of physical properties of ideal solutions with composition. The effectiveness of correlating density, viscosity, refractive index and surface tension using this concept was tested. Ten ternary systems at either three or four different temperatures were regressed and compared to an ideal solution case. It was found that the four-parameter Kolmogorov-Arnold (KA) model performed excellently when the data regression included the full datasets. Unfortunately, the KA model may be too flexible, leading to overfitting binary data when applied to predicting ternary data.
Degradation of rhodamine B Dye on BiOIO3/Bi12O17Cl2 heterostructure photocatalyst under visible light activation
Ogbeifun, Osemeikhian; Tichapondwa, Shepherd Masimba; Chirwa, Evans M.N. (Elsevier, 2025-10)
Dye pollution resulting from industrial waste poses a substantial threat to both human health and the environment. Heterostructure composites of BiOIO3 and Bi12O17Cl2 with varying mass ratios (BiOIO3/Bi12O17Cl2-y:x) were fabricated to enhance the degradation abilities of the individual material towards dye contaminants. The rapid recombination of photogenerated electron-hole pairs in Bi12O17Cl2 and the limited photon utilisation of the visible light wavelengths by BiOIO3 were addressed in the heterojunction. The heterojunction formed between the material provides for spatial charge separation and boost of redox power of photogenerated electrons and holes. The degradation rate constant of Rhodamine B dye on BiOIO3/Bi12O17Cl2–1:1, the best performing material, under visible light in 6 h was 0.4 h−1, which is 2.7 and 4.3 times the rate constants for Bi12O17Cl2 (0.149 h−1) and BiOIO3 (0.093 h−1), respectively. The results demonstrate the contribution of heterostructure formation in improving the photocatalytic degradation process. The main species in the degradation step are hydroxyl (•OH) and superioxide (•O2–) radicals. BiOIO3/Bi12O17Cl2–1:1 has good photocatalytic stability, as 96 % efficiency retention is reported after four cycles. Thus, BiOIO3/Bi12O17Cl2–1:1 is a promising material for the degradation of dyes.
Superstructure-based optimization of membrane gas separation processes : a review
Chiwaye, Natsayi; Majozi, Thokozani; Daramola, Michael Olawale (American Chemical Society, 2025-07)
Membrane technology for gas separation has apparent advantages such as compactness, ease of operation, and the possibility of incorporation into hybrid systems. This review analyzes the superstructure-based optimization models for membrane gas separation systems reported in the literature. The review describes and analyzes the membrane permeation models embedded in the optimization models and solution approaches, the superstructures presented, the objective functions adopted, and outcomes for different application cases. The progress is reported, and challenges and opportunities for future research are suggested. The presented review would be useful to researchers and engineers in membrane technology research and development and could lead to the deployment and adoption of membranes in various applicable industries, such as carbon capture.

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