Thiol-Ene Click Reaction in Constructing Liquid Separation Membranes for Water Treatment.

In the evolving landscape of water treatment, membrane technology has ascended to an instrumental role, underscored by its unmatched efficacy and ubiquity. Diverse synthesis and modification techniques are employed to fabricate state-of-the-art liquid separation membranes. Click reactions, distinguished by their rapid kinetics, minimal byproduct generation, and simple reaction condition, emerge as a potent paradigm for devising eco-functional materials. While the metal-free thiol-ene click reaction is acknowledged as a viable approach for membrane material innovation, a systematic elucidation of its applicability in liquid separation membrane development remains conspicuously absent. This review elucidates the pre-functionalization strategies of substrate materials tailored for thiol-ene reactions, notably highlighting thiolation and introducing unsaturated moieties. The consequential implications of thiol-ene reactions on membrane properties-including trade-off effect, surface wettability, and antifouling property-are discussed. The application of thiol-ene reaction in fabricating various liquid separation membranes for different water treatment processes, including wastewater treatment, oil/water separation, and ion separation, are reviewed. Finally, the prospects of thiol-ene reaction in designing novel liquid separation membrane, including pre-functionalization, products prediction, and solute-solute separation membrane, are proposed. This review endeavors to furnish invaluable insights, paving the way for expanding the horizons of thiol-ene reaction application in liquid separation membrane fabrication.

Superior performance of a membrane bioreactor through innovative in-situ aeration and structural optimization using computational fluid dynamics.

The optimization of membrane bioreactors (MBRs) involves a critical challenge in structural design for mitigation of membrane fouling. To address this issue, a three-dimensional computational fluid dynamics (CFD) model was utilized in this study to simulate the hydrodynamic characteristics of a flat sheet (FS) MBR. The optimization of the membrane module configuration and operating conditions was performed by investigating key parameters that altered the shear stress and liquid velocity. The mixed liquor suspended solids (MLSS) concentration was found to increase the shear stress, leading to a more uniform distribution of shear stress. By optimizing the appropriate bubble diameter to 5 mm, the shear stress on the membrane surface was optimized with relatively uniform distribution. Additionally, extending the side baffle length dramatically improved the uniformity of the shear stress distribution on each membrane. A novel in-situ aeration method was also discovered to promote turbulent kinetic energy by 200 times compared with traditional aeration modes, leading to a more uniform bubble streamline. As a result, the novel in-situ aeration method demonstrated superior membrane antifouling potential in the MBR. This work provides a new approach for the structural design and optimization of MBRs. The innovative combination of the CFD model, optimization techniques, and novel in-situ aeration method has provided a substantial contribution to the advancement of membrane separation technology in wastewater treatment.

New methods based on back propagation (BP) and radial basis function (RBF) artificial neural networks (ANNs) for predicting the occurrence of haloketones in tap water.

Haloketones (HKs) is one class of disinfection by-products (DBPs) which is genetically toxic and mutagenic. Monitoring HKs in drinking water is important for drinking water safety, yet it is a time-consuming and laborious job. Developing predictive models of HKs to estimate their occurrence in drinking water is a good alternative, but to date no study was available for HKs modeling. This study was to explore the feasibility of linear, log linear regression models, back propagation (BP) as well as radial basis function (RBF) artificial neural networks (ANNs) for predicting HKs occurrence (including dichloropropanone, trichloropropanone and total HKs) in real water supply systems. Results showed that the overall prediction ability of RBF and BP ANNs was better than linear/log linear models. Though the BP ANN showed excellent prediction performance in internal validation (N25 = 98-100%, R2 = 0.99-1.00), it could not well predict HKs occurrence in external validation (N25 = 62-69%, R2 = 0.202-0.848). Prediction ability of RBF ANN in external validation (N25 = 85%, R2 = 0.692-0.909) was quite good, which was comparable to that in internal validation (N25 = 74-88%, R2 = 0.799-0.870). These results demonstrated RBF ANN could well recognized the complex nonlinear relationship between HKs occurrence and the related water quality, and paved a new way for HKs prediction and monitoring in practice.

Filtration behaviors and fouling mechanisms of ultrafiltration process with polyacrylamide flocculation for water treatment.

This study aims to investigate thermodynamic mechanisms of filtration behaviors of ultrafiltration (UF) process with polyacrylamide (PAM) flocculation for surface water treatment, which has not been investigated previously. It was interestingly found that, filtration of durably mixed sodium alginate (SA) solution corresponded to an extraordinarily high specific filtration resistance (SFR) (3.28 × 1014 m·kg-1 without polyacrylamide addition) and a V-shaped profile of SFR characterized by a sharp fall followed by a correspondingly sharp rise along with the increase in PAM addition concentration. Experimental characterizations suggested that, membrane fouling was mainly caused by the gel layer formation rather than the pore clogging and cake/floc formation. Rather than the chemical composition change, the changes of the solution physicochemical properties (pH and zeta potential) and foulant morphology are associated with above-mentioned interesting filtration behaviors. Accordingly, the thermodynamic mechanisms of the filtration behaviors were proposed. It was proposed that, the thermodynamics of polymeric network described by the Flory-Huggins lattice theory were responsible for the extraordinarily high SFR of SA gel layer. Low dosage of PAM addition decreased the negative zeta potential and homogeneity of the gel system, causing the reduced SFR. In contrast, further PAM addition increased the negative zeta potential and homogeneity of the gel system, and then increased the SFR of the gel layer. These results reasonably explained the V-shaped profile of SFR. This study provided significant insights into the effects of PAM addition on ultrafiltration behaviors of alginate solution.

Molecular insights into the impacts of iron(III) ions on membrane fouling by alginate.

Molecular mechanisms responsible for the filtration behaviors of sodium alginate (SA) in presence of different iron(III) ion concentration were explored in this study. It was found that specific filtration resistance (SFR) of alginate mixtures (1.0 gSA/L) firstly increased and then decreased to a trough with iron(III) concentration increase from 0 to 2.5 mM. Alginate mixture interacting with 0.1 mM iron(III) possessed an SFR as high as 1.65 × 1014 m kg-1, which could be explained by Flory-Huggins lattice theory related with gel filtration. Optical observation showed significant morphology transition (from gel to granular solids) of foulant layers with iron(III) concentration increase. A series of characterizations indicated the change of microstructure, pH and surface charge of alginate mixture with iron(III) concentration. Density functional theory (DFT) simulation suggested that iron(III) ion preferentially forms coordination bonds with three terminal carboxyl groups of alginate chains, facilitating elongation and cross-linking of alginate chains. Such a coordination mode induces formation of a slime and homogeneous gel, corresponding to high SFR. Continuous increase in iron(III) concentration leads to non-terminal coordination, which makes alginate chains more clustered and coiled. This effect, together with effects of the reduced surface charge and electric double layer compression, significantly decrease SFR of alginate mixtures. This study provided deep molecular insights into effects of iron(III) ions on alginate fouling.

Application of radial basis function artificial neural network to quantify interfacial energies related to membrane fouling in a membrane bioreactor.

Efficient quantification of interfacial energy related with membrane fouling represents the primary interest in membrane bioreactors (MBRs) as interfacial energy determines foulant layer formation. In this study, radial basis function (RBF) artificial neural networks (ANNs) with five related factors as input variables were applied to quantify interfacial energy with randomly rough membrane surface. It was found that, RBF ANNs could well capture the complex non-linear relationships between the related factors and interfacial energy. RBF ANN quantification showed high regression coefficient and accuracy, suggesting its high capacity to quantify interfacial energy. Compared to at least one-week time consumption of the advanced extensive Derjaguin-Landau-Verwey-Overbeek (XDLVO) approach, quantification by RBF ANNs only took several seconds for a same case, indicating the high efficiency of RBF ANNs. Moreover, the abilities of RBF ANNs can be further improved. The robust RBF ANNs proposed paved a new way to study membrane fouling in MBRs.

Effects of surface morphology on alginate adhesion: Molecular insights into membrane fouling based on XDLVO and DFT analysis.

While surface morphology is the key parameter affecting membrane performance, its exact roles on membrane fouling have not well unveiled. In this study, effects of membrane surface roughness on fouling caused by alginate adhesion were investigated by thermodynamic techniques of the extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) approach and density functional theory (DFT). The energy of a single typical alginate chain adhering to rough membrane surface was figured out to be 0.5-3.0 kJ/mol for the first time. Whereas, the related bending energy at typical bending angle was calculated to be over 13.0 kJ/mol based on DFT calculations. The big energy gap suggested that the alginate chain in solution would not change its configuration to fit membrane surface morphology, and tended to directly adhere to membrane surface. The thermodynamic analyses predicted that the direct adhesion pathway was favorable in energy when an alginate chain approaching to rough membrane surface. As a result, as compared to the smooth membrane, rough membrane corresponds to less alginate adhesion and adhesive fouling. Combination of XDLVO and DFT techniques provided not only molecular insights into membrane fouling, but also a new way for fouling research.

Novel insights into membrane fouling caused by gel layer in a membrane bioreactor: Effects of hydrogen bonding.

Gel layer formation in some cases directly determines membrane fouling extent in membrane bioreactors (MBRs). While hydrogen bonding interactions extensively exist in gelling foulants and sludge suspension, their exact roles in fouling remain unveiled. Filtration results in this study showed that, specific filtration resistance (SFR) of a gel layer formed in the MBR was as high as 2.06 × 1019 m-1·kg-1 at 20 °C, and moreover, SFR of both the real gel and model gel (Poly(N-isopropylacrylamide) (PNIPAM)) decreased with temperature. Fourier-transform infrared spectroscopy (FTIR) analysis indicated that gel samples were abundant of good hydrogen bonding donors/acceptors to form hydrogen bonding, and hydrogen bonding strength decreased with temperature. From viewpoint of free energy, mathematical models depicting roles of hydrogen bonding were proposed. For the first time, contribution level of hydrogen bonding effects to total gel SFR was quantified to be around 20%. These results offered in-depth insights into membrane fouling in MBRs.

A unified thermodynamic mechanism underlying fouling behaviors of soluble microbial products (SMPs) in a membrane bioreactor.

Soluble microbial products (SMPs) are the predominate foulants determining fouling extent in membrane bioreactors (MBRs). However, exact mechanism underlying their typical fouling behaviors remains unrevealed. In this study, the typical fouling behaviors of SMPs during initial operational period of a MBR were characterized. It was found that, although being low content, SMPs rather than sludge particulates preferentially adhered to membrane surface to accumulate a gel layer, and moreover, specific filtration resistance (SFR) of SMPs was approximately 700 times larger than that of the sludge particulates at operational day 3. According to energy balance principle, a unified thermodynamic mechanism underlying these fouling behaviors of SMPs was proposed. Thermodynamic analyses demonstrated that, the attractive interaction energy strength in contact between SMPs and membrane was larger by around 3700 times than that between sludge particulates and membrane, well explaining the extremely high adhesive ability of SMPs over sludge particlulates. Meanwhile, filtration through a SMPs layer was modelled and simulated as a thermodynamic process. Simulation on an agar gel showed that, about 92.6% of SFR was originated from mixing free energy change during filtration. Such a result satisfactorily interpreted the extremely high SFR of SMPs layer over sludge cake layer. The revealed thermodynamic mechanism underlying SMPs fouling behaviors significantly deepened understanding of fouling, and facilitated to development of effective fouling control strategies.

Novel insights into membrane fouling in a membrane bioreactor: Elucidating interfacial interactions with real membrane surface.

While governing adhesion/deposition of various foulants on membrane surface and membrane fouling in membrane bioreactors (MBRs), interfacial interactions with real membrane surface have not yet been fully quantified. In this study, theoretical deduction and experiments were carried out to numerically elucidate interfacial interactions in a MBR. A continuous real membrane morphology was reconstructed based on atomic force microscopy (AFM) characterization and triangulation technique. Thereafter, a method to calculate those interactions was established by incorporating the spatial relationship between a foulant and the reconstructed morphology into surface element integration (SEI) method. A case study of the proposed method was conducted. With surface characterization of the foulants and membrane, the interfacial interactions with real membrane morphology were approximated for the first time by computer programming according to composite Simpson's rule. The results showed that rough morphology prolonged the interfacial interactions, indicating the profound role of morphology in the interfacial interactions related with membrane fouling. The new method would provide significant insights into membrane fouling in MBRs.

Thermodynamic insights into membrane fouling in a membrane bioreactor: Evaluating thermodynamic interactions with Gaussian membrane surface.

While membrane bioreactor (MBR) technology is generally considered as one of the most promising technologies for wastewater treatment and recovery, membrane fouling remains the major obstacle limiting its applications. Interfacial interactions, which critically determine adhesion process and membrane fouling, were investigated in this study. It was found that, natural membrane surface was of a Gaussian surface obeying Gaussian distribution. A Gaussian approach integrating Fourier transform technique, Gaussian distribution and spectrum method was deduced to simulate rough surface topography of membrane. Thereafter, surface element integral (SEI) method, together with composite Simpson rule and triangulation of Gaussian surface was proposed to calculate interfacial interactions. By using the unified method, quantification of interfacial interactions with a Gaussian membrane surface was realized for the first time to date. It was further found that, membrane surface topography had profound impacts on interfacial interactions and adhesive fouling in the MBR. The deduced method can be used to address impacts of various factors on interfacial interactions and adhesive fouling, posing in-depth thermodynamic insights into membrane fouling and pointing towards its widespread potential in fouling research in MBRs.

Mechanistic insights into alginate fouling caused by calcium ions based on terahertz time-domain spectra analyses and DFT calculations.

Fouling mechanisms underlying the filtration behaviors of alginate solution caused by calcium addition were investigated by Terahertz time-domain spectroscopy (THz-TDS) and density functional theory (DFT) techniques. Filtration tests showed that specific filtration resistance (SFR) of alginate solution (0.75 g L-1) monotonously increased with calcium addition at a relatively low range of calcium concentration (0-1.0 mM), and SFR (2.61 × 1015 m kg-1) of alginate solution with 1.0 mM calcium addition was extremely high as compared with sludge suspension. Characterizations by X-ray photoelectric spectroscopy (XPS), Fourier transform infrared spectroscopy (FTIR) and Thermogravimetric analysis (TGA) showed that the composition of functional groups, elements and thermal stability of alginate was not apparently affected by calcium concentration. Howbeit, THz-TDS spectra showed that calcium addition caused structural variation of alginate polymer in solution. DTF calculation results showed that initial binding of alginate chains induced by calcium ions preferentially occurred in intermolecular other than intramolecular, and moreover, the two alginate chains bridged by a calcium atom tend to stretch in a tetrahedron structure (cross to each other) other than parallel to each other. According to these results, "chemical potential gap" depicted by Flory-Huggins theory was suggested to be responsible for the filtration behaviors of alginate solution caused by calcium addition. This study provided the mechanistic insights into membrane fouling.

Effects of fractal roughness of membrane surfaces on interfacial interactions associated with membrane fouling in a membrane bioreactor.

Fractal roughness is one of the most important properties of a fractal surface. In this study, it was found that, randomly rough membrane surface was a fractal surface, which could be digitally modeled by a modified two-variable Weierstrass-Mandelbrot (WM) function. Fractal roughness of membrane surfaces has a typical power function relation with the statistical roughness of the modeled surface. Assessment of interfacial interactions showed that an increase in fractal roughness of membrane surfaces will strengthen and prolong the interfacial interactions between membranes and foulants, and under conditions in this study, will significantly increase the adhesion propensity of a foulant particle on membrane surface. This interesting result can be attributed to that increase in fractal roughness simultaneously improves separation distance and interaction surface area for adhesion of a foulant particle. This study gives deep insights into interfacial interactions and membrane fouling in MBRs.

Physicochemical correlations between membrane surface hydrophilicity and adhesive fouling in membrane bioreactors.

36 membrane material cases used in membrane bioreactors (MBRs) covering wide range of hydrophilicity/hydrophobicity were used to calculate thermodynamic interactions between membranes and foulants. It was found that adhesive fouling can be represented by the total interaction energy at minimum separation distance (h0). No functional relationship between membrane hydrophilicity and adhesive fouling can be deduced. However, membrane hydrophilicity, in terms of water contact angle or interaction energy between two identical surfaces at h0 in water (ΔGsws), had high statistical correlations with adhesive fouling. This statistical correlations should be attributed to the major role of acid-base interaction in total interaction associated with adhesion in most of membrane cases. Moreover, the statistical correlations were independent of the changes in membrane surface roughness or hydrophilicity/hydrophobicity of foulants. These findings satisfactorily explained the inconsistent conclusions in the literature regarding effects of membrane hydrophilicity on adhesive fouling, giving implications for membrane fouling mitigation.

Quantitative evaluation of the interfacial interactions between a randomly rough sludge floc and membrane surface in a membrane bioreactor based on fractal geometry.

In this paper, a new method for quantification of interfacial interactions between a randomly rough particle and membrane surface was proposed. It was found that sludge flocs in a membrane bioreactor were of apparent fractal characteristics, and could be modeled by the modified two-variable Weierstrass-Mandelbrot (WM) function. By combining the surface element integration (SEI) method, differential geometry and composite Simpson's rule, the quantitation method for calculating such interfacial interactions was further developed. The correctness and feasibility of the new method were verified. This method was then applied to evaluate the interfacial interactions between a randomly rough particle and membrane surface. It was found that, randomly rough particle possesses stronger interaction strength than regularly rough particle but weaker strength than smooth particle with membrane surface, indicating significant effects of surface morphology and roughness. The proposed method in this study has broad application prospect in membrane fouling study.

Novel indicators for thermodynamic prediction of interfacial interactions related with adhesive fouling in a membrane bioreactor.

This study focused on developing indicators to predict adhesive membrane fouling in a membrane bioreactor (MBR). Thermodynamic interactions between membrane surface and foulants in various interaction scenes were comprehensively evaluated. It was revealed that, the total interaction energy in contact could be considered as a critical value affecting adhesion of foulants. Surface hydrophilicity cannot be simply represented by water contact angle. Statistical analysis showed that membrane acid-based (AB) surface tension, Lifshitz-Van der waals (LW) surface tension, total tension, zeta potential and water contact angle had no apparent correlation with adhesive fouling, suggesting the infeasibility of these parameters as fouling predictors. It was found that, interaction between two identical membrane surface in water (ΔGsws) and membrane surface electron donor tension (γ-) strongly correlated with adhesive fouling, and could be reliable indicators to predict adhesive fouling. This study identified the relationships of series membrane surface properties with adhesive fouling in MBRs.

Realization of quantifying interfacial interactions between a randomly rough membrane surface and a foulant particle.

Quantification of interfacial interaction with randomly rough surface is the prerequisite to quantitatively understand and control the interface behaviors such as adhesion, flocculation and membrane fouling. In this study, it was found that membrane surface was randomly rough with obvious fractal characteristics. The randomly rough surface of membrane could be well reconstructed by the fractal geometry represented by a modified Weierstrass-Mandelbrot function. A novel method, which combined composite Simpson's approach, surface element integration method and approximation by computer programming, was developed. By using this method, this study provided the first realization of quantifying interfacial energy between randomly rough surface of membrane and a foulant particle. The calculated interactions with randomly rough surface of membrane were significantly different from those with smooth surface of membrane, indicating the significant effect of surface topography on interactions. This proposed method could be also potentially used to investigate various natural interface environmental phenomena.

Modeling three-dimensional surface morphology of biocake layer in a membrane bioreactor based on fractal geometry.

While the adsorptive fouling in membrane bioreactors (MBRs) is highly dependent of the surface morphology, little progress has been made on modeling biocake layer surface morphology. In this study, a novel method, which combined static light scattering method for fractal dimension (Df) measurement with fractal method represented by the modified two-variable Weierstrass-Mandelbrot function, was proposed to model biocake layer surface in a MBR. Characterization by atomic force microscopy showed that the biocake surface was stochastic, disorder, self-similarity, and with non-integer dimension, illustrating obvious fractal features. Fractal dimension (Df) of sludge suspension experienced a significant change with operation of the MBR. The constructed biocake layer surface by the proposed method was quite close to the real surface, showing the feasibility of the proposed method. It was found that Df was the critical factor affecting surface morphology, while other factors exerted moderate or minor effects on the roughness of biocake layer.

A novel insight into membrane fouling mechanism regarding gel layer filtration: Flory-Huggins based filtration mechanism.

This study linked the chemical potential change to high specific filtration resistance (SFR) of gel layer, and then proposed a novel membrane fouling mechanism regarding gel layer filtration, namely, Flory-Huggins based filtration mechanism. A mathematical model for this mechanism was theoretically deduced. Agar was used as a model polymer for gel formation. Simulation of the mathematical model for agar gel showed that volume fraction of polymer and Flory-Huggins interaction parameter were the two key factors governing the gel SFR, whereas, pH and ionic strength were not related with the gel SFR. Filtration tests of gel layer showed that the total SFR value, effects of pH and ionic strength on the gel SFR well agreed with the perditions of model's simulation, indicating the real occurrence of this mechanism and the feasibility of the proposed model. This mechanism can satisfactorily explain the extremely high SFR of gel layer, and improve fundamental insights into membrane fouling regarding gel layer filtration.

Membrane fouling in a membrane bioreactor: High filtration resistance of gel layer and its underlying mechanism.

A membrane bioreactor (MBR) was continuously operated to investigate mechanisms of fouling caused by the gel layer in this study. Agar was used as a model foulant for gel layer formation, and filtration resistance of gel layers was systematically assessed. The results showed that gel layer possessed unusually high specific filtration resistance (SFR) and high measured porosity as compared with cake layer. Current knowledge cannot explain the contradiction between high filtration resistance and high porosity of gel layer. A new fouling mechanism based on Flory-Huggins theory was then proposed. Filtration resistance of agar gel layer was found to be independent of pH and ionic strength, but linearly increase with gel thickness. The results are accordant with the mechanism deductions. Simulation of the mechanism model showed that the filtration resistance induced by mixing chemical potential variation was comparable to the experimental data of filtration resistance of agar gel layer, indicating that the proposed mechanism is the predominant mechanism responsible for the high filtration resistance of gel layer. The proposed mechanism was further verified from the bound water viewpoint.