Design and Machine Learning Prediction of In Situ Grown PDA-Stabilized MOF (UiO-66-NH2) Membrane for Low-Pressure Separation of Emulsified Oily Wastewater

Next-generation stimuli-responsive smart membranes: Developments in oil/water separation

Effective treatment of oil-contaminated wastewater is essential due to its severe environmental and health impacts. The membrane-based separation is cost-effective, energy-efficient, and eco-friendly; however, fouling has remained a pressing issue. Stimuli-responsive membranes, which adjust their pore structure and surface properties in response to external triggers such as light, pH, and temperature, offer enhanced fouling resistance and improved separation performance. This review provides a comprehensive analysis of stimuli-responsive membranes for oil/water separation, emphasizing the role of smart polymeric materials engineered for controllable separation processes. We critically assess the strengths of these advanced membranes, including their tuneable wettability and energy-efficient operation, while identifying key limitations such as long-term stability, response time, scalability, and cost-effectiveness. Furthermore, the review explores various polymer types, synthesis methods, and fabrication techniques, evaluating their effectiveness in separation applications. Finally, the review concludes by outlining the challenges and proposing future directions to enhance the performance of stimuli-responsive membranes. By offering valuable insights into the dynamic control of membrane structures and properties, this study aims to inspire the development of next-generation stimuli-responsive membranes, drive their commercialization, and promote sustainable water treatment solutions.

Pressure Sensitivity of UiO-66 Framework with Encapsulated Spin Probe: A Molecular Dynamics Study

Probes sensitive to mechanical stress are in high demand for analyzing pressure distributions in materials. Metal-organic frameworks (MOFs) are especially promising for designing pressure sensors due to their structural tunability. In this work, using classical molecular dynamics (MD) simulations, we clarified the mechanism of exceptional pressure sensitivity of the material based on the UiO-66 framework with a trace amount of spin probes encapsulated in cavities. The role of defects in the MOF structure has been revealed using a combination of electron paramagnetic resonance (EPR) spectroscopy and MD calculations, and potential degradation pathways under mechanical stress have been proposed. The combined MD and EPR study provides valuable insights for further development of new MOF-based sensors applicable for non-destructive pressure mapping in various materials.

Bioinspired Nanoporous MOF-Modified Basalt Fiber Fabrics for Efficient and Multifunctional Oil-Water Separation

Oily wastewater pollution is increasing globally. Conventional treatment methods often fail due to inefficiency and secondary contamination. Therefore, developing advanced membrane separation technologies is crucial. While membrane separation technology holds promise as a solution, its widespread applicability necessitates overcoming significant obstacles related to corrosion resistance, alkali resistance, and the prevention of membrane fouling. This study presents a novel and highly efficient approach for oil-water separation, employing bioinspired, nanoporous metal-organic framework-modified basalt fiber fabrics (BFF). The integration of UiO-66-NH2, renowned for its high porosity and tunable functionalities, with a chitosan-dopamine (CS-DA) layer on BFFs creates a multifunctional membrane with enhanced hydrophilicity and underwater superoleophobicity. This bioinspired design (refers to engineering solutions that mimic natural structures or mechanisms to improve performance and efficiency), drawing inspiration from the structure and function of natural materials, results in superior oil-water separation performance, demonstrating excellent flux and oil rejection rates. The UiO-66-NH2 effectively captures oil droplets due to its high porosity, while the CS-DA layer facilitates water permeability and promotes surface stability. Furthermore, the composite membrane exhibits exceptional stability and reusability, positioning it as a promising candidate for efficient and sustainable oil-water separation applications. This research showcases the potential of bioinspired design principles for developing innovative solutions to pressing environmental challenges.

Tunning the Wettability of the PVDF Membrane using the PVA-Stabilized TA-UiO-66-NH2 MOF Membranes to Separate Layered Oil-Water Mixture and Surfactant-Stabilized Emulsion

This study introduces a UiO-66-NH2/Tannic acid/Polyvinylidene fluoride (UTP) composite membrane for efficient oil-water separation. Pristine polyvinylidene fluoride (PVDF) membranes, due to their hydrophobic nature, tend to foul during oil-in-water emulsion separation. By incorporating the metal-organic framework (MOF) UiO-66-NH2 and stabilizing it with tannic acid (TA) and polyvinyl alcohol (PVA), the membrane's hydrophilicity and antifouling properties were significantly enhanced. The water contact angle of the UTP membrane decreased from 121° to 3°, indicating a dramatic increase in hydrophilicity, while the underwater oil contact angle (UWOCA) of 119° demonstrated excellent oleophobicity. The modified membrane achieved over 99 % separation efficiency and improved flux by 15 times compared to the pristine PVDF. TA acted as a binder, ensuring uniform MOF dispersion and improving the composite's stability. The PVA further reinforced the structure, enhancing durability under operational conditions. Durability tests showed no significant MOF detachment after repeated use, confirming the stability of the UTP composite. The results highlight the potential of the UTP membrane for oil-water separation with superior permeability and fouling resistance.

MOF UiO-66 and its composites: design strategies and applications in drug and antibiotic removal

Antibiotics and pharmaceuticals exert significant environmental risks to aquatic ecosystems and human health. Many effective remedies to this problem have been developed through research. Metal-organic frameworks (MOFs) are potential constituents, for drug and antibiotic removal. This article explores the potential of MOFs like UiO-66 (University of Oslo-66) to remove pharmaceutical and antibiotic contaminants from water. Zr-based MOF UiO-66 is used in water treatment due to its well-known chemical, thermal, and mechanical stability. The review covers several modifications, including metal doping, organic-group functionalization, and composite construction, to increase the UiO-66 selectivity and adsorption capacity for various pollutants. Recent studies have shown that UiO-66 is an effective material for pharmaceutical pollutants such as ciprofloxacin, tetracycline, and sulfamethoxazole removal. Practical application, photostability, and large-scale synthesis remain challenges in water treatment methods. Moreover, recent studies indicate the recycling potential of UiO-66 that validates its capability to retain its efficiency over multiple cycles, indicating its cost-effectiveness and sustainability. Besides, the toxicity of UiO-66 and its derivatives, which occur during water treatment, has also been highlighted, addressing the health and environmental risks. Prospective research directions include designing flaws, producing stable analogs of UiO-66, and transforming powdered UiO-66 into other forms that might be utilized, including films and membranes. This review is crucial as no comprehensive literature is currently available that thoroughly discusses the design techniques and applications of UiO-66 and its composites for drug and antibiotic removal. Our study specifically concentrates on the latest developments, emphasizing particular alterations that improve performance in water treatment.

A Wide-Spectrum Oil/Water Separation Scenario Enhanced by a Chitosan-Based Superwetting Membrane with a Tunable Microstructure and Powerful Photocatalytic Self-Cleaning Capability

Oil spills and industrial oily wastewater pose serious threats to the environment. A series of modified membranes with special wettability have been widely used for separating oil/water mixtures and emulsions. However, these membranes still face challenges such as the detachment of the modified coatings and membrane fouling. Here, a freestanding biobased superwetting nanofibrous membrane for oil/water mixture separation was electrospun with chitosan (CS) and poly(vinyl alcohol) (PVA) as precursors, followed by chemical cross-linking and in situ growth of β-FeOOH nanoparticles on the surface. Moreover, by precisely controlling both the cross-linking time between CS and PVA and the growth time of β-FeOOH nanoparticles, the nanosize apertures and rough structures on the membrane surface can be regulated toward a wide range of oil/water separation scenarios. As a result, FeOOH@CS/PVA-4-12 demonstrated superwettability, with a water contact angle of 9.5 ± 3.5° in air and an underwater-oil contact angle above 140°, achieving a separation efficiency of 98.5% and a water permeation flux of 2350 L·m-2·h-1 for n-heptane/water mixtures. The membrane FeOOH@CS/PVA-24-24 exhibited exceptional oil-in-water emulsion separation performance with a separation efficiency of up to 99.9% for water/n-heptane emulsions. Additionally, the membrane exhibited remarkable antifouling properties, attributed to its superwetting surface and the photocatalytic ability of β-FeOOH nanoparticles. After five photocatalytic self-cleaning cycles, the water permeation flux and separation efficiency remained almost unchanged, demonstrating its great potential for practical application.

Enhanced desalination with polyamide thin-film membranes using ensemble ML chemometric methods and SHAP analysis

Addressing global freshwater scarcity requires innovative technological solutions, among which desalination through thin-film composite polyamide membranes stands out. The performance of these membranes plays a vital role in desalination, necessitating advanced predictive modeling for optimization. This study harnesses machine learning (ML) algorithms, including support vector machine (SVM), neural networks (NN), linear regression (LR), and multivariate linear regression (MLR), alongside their ensemble techniques to predict and enhance average water flux (AWF) and average salt rejection (ASR) essential metrics of desalination efficiency. To ensure model interpretability and feature importance analysis, SHapley Additive exPlanations (SHAP) were employed, providing both global and local insights into feature contributions. Initially, the individual models were validated, with NN demonstrating superior performance for both AWF and ASR, achieving the lowest mean absolute error (MAE = 0.001) and root mean squared error (RMSE = 0.0111) for AWF and an MAE = 0.0107 and RMSE = 0.0982 for ASR. The accuracy of predictions improved significantly with ensemble models, as evidenced by the near-perfect Nash-Sutcliffe efficiency (NSE) values. Specifically, the NN ensemble (NN-E) and Linear Regression ensemble (LR-E) reached an MAE and RMSE of 0.001 and 0.0111, respectively, for AWF. For ASR, NN-E reduced the MAE to 0.0013 and the RMSE to 0.0089, while LR-E maintained competitive performance with an MAE of 0.0133 and an RMSE of 0.0936. SHAP analysis revealed that features such as MDP and TMC were critical drivers of performance, with MDP showing the most significant positive impact on ASR. These findings demonstrate the dominance of ensemble methods over individual algorithms in predicting key desalination parameters. The enhanced precision in estimating AWF and ASR offered by these neuro-intelligent ensembles, combined with the interpretability provided by SHAP analysis, can lead to significant environmental and operational improvements in membrane performance, optimizing resource usage and minimizing ecological impacts. This study paves the way for integrating intelligent ML ensembles and SHAP-based interpretability into the practical field of membrane technology, marking a step forward toward sustainable and efficient desalination processes.

MOF-Enhanced Aluminosilicate Ceramic Membranes Using Non-Firing Processes for Pesticide Filtration and Phytochrome Removal

Aluminosilicates, abundant and crucial in both natural environments and industry, often involve uncontrollable chemical components when derived from minerals, making further chemical purification and reaction more complicated. This study utilizes pure alumina and fumed silica powders as more controllable sources, enhancing aluminosilicate reactivity through room temperature (non-firing) processing and providing a robust framework that resists mechanical stress and high temperature. By embedding iron-based metal-organic frameworks (Fe-MOF/non-firing aluminosilicate membranes) within the above matrix, these ceramic membranes not only preserve their mechanical robustness but also gain significant chemical functionality, enhancing their capacity to removing phytochromes from the vegetables. Sodium hydroxide and sodium silicate were selected as activators to successfully prepare high-strength, non-firing aluminosilicate membranes. These membranes demonstrated a flexural strength of 8.7 MPa under wet-culture conditions with a molar ratio of Al2O3:SiO2:NaOH:Na2SiO3 at 1:1:0.49:0.16. The chlorophyll adsorption of spinach conducted on these membranes showed a removal rate exceeding 90% at room temperature and pH = 9, highlighting its potential for the selective adsorption of chlorophyll. This study underscores the potential of MOF-enhanced aluminosilicate ceramic membranes in environmental applications, particularly for agricultural pollution control.