Membrane fouling in a membrane bioreactor: A novel method for membrane surface morphology construction and its application in interaction energy assessment

Quantifying interfacial interactions for improved membrane antifouling: A novel approach using triangulation and surface element integration method

To gain a thorough understanding of interfacial behaviors such as adhesion and flocculation controlling membrane fouling, it is necessary to simulate the actual membrane surface morphology and quantify interfacial interactions. In this work, a new method integrating the rough membrane morphology reconstruction technology (atomic force microscopy (AFM) combining with triangulation technique), the surface element integration (SEI) method, the extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory, the compound Simpson's approach, and the computer programming was proposed. This new method can exactly mimic the real membrane surface in terms of roughness and shape, breaking the limitation of previous fractal theory and Gaussian method where the simulated membrane surface is only statistically similar to the real rough surface, thus achieving a precise description of the interfacial interactions between sludge foulants and the real membrane surface. This method was then applied to assess the antifouling propensity of a polyvinylidene fluoride (PVDF) membrane modified with Ni-ZnO particles (NZPs). The simulated results showed that the interfacial interactions between sludge foulants in a membrane bioreactor (MBR) and the modified PVDF-NZPs membrane transformed from an attractive force to a repulsive force. The phenomenon confirmed the significant antifouling propensity of the PVDF-NZPs membrane, which is highly consistent with the experimental findings and the interfacial interactions described in previous literature, suggesting the high feasibility and reliability of the proposed method. Meanwhile, the original programming code of the quantification was also developed, which further facilitates the widespread use of this method and enhances the value of this work.

Effect of organic loading rates on the performance of membrane bioreactor for wastewater treatment behaviours, fouling, and economic cost

Although submerged membrane bioreactor (MBR) are widely used in treating municipal wastewater and recovery of potential resources, membrane operational parameters and membrane fouling control remain debated issues. In this study, the treatment of municipal wastewater by MBR at high-biomass sludge (MLSS (g/L) ranging from 5.4 g/L to 16.1 g/L) was assessed at an organic loading rates (OLRs) ranging from 0.86 to 3.7 kg COD/m3d. The correlation between trans-membrane pressure and total fouling resistance was thoroughly investigated in this study. According to the findings, greater OLRs of 0.86 to 3.7 kg COD/m3d caused a decrease in COD, BOD, and NH4-N removal efficiency, and higher OLRs of 3.7 kg COD/m3d resulted in a higher increase in total fouling resistance (Rt). The economic study of using the MBR system proved that for a designed flow rate of 20 m3/d, the payback period from using the treated wastewater will be 7.98 years, which confirms the economic benefits of using this MBR for treating municipal wastewater. In general, understanding the challenges facing the efficiency of MBR would improve its performance and, consequently, the sustainability of wastewater reclamation.

A Review on Membrane Fouling Prediction Using Artificial Neural Networks (ANNs)

Membrane fouling is a major hurdle to effective pressure-driven membrane processes, such as microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), and reverse osmosis (RO). Fouling refers to the accumulation of particles, organic and inorganic matter, and microbial cells on the membrane's external and internal surface, which reduces the permeate flux and increases the needed transmembrane pressure. Various factors affect membrane fouling, including feed water quality, membrane characteristics, operating conditions, and cleaning protocols. Several models have been developed to predict membrane fouling in pressure-driven processes. These models can be divided into traditional empirical, mechanistic, and artificial intelligence (AI)-based models. Artificial neural networks (ANNs) are powerful tools for nonlinear mapping and prediction, and they can capture complex relationships between input and output variables. In membrane fouling prediction, ANNs can be trained using historical data to predict the fouling rate or other fouling-related parameters based on the process parameters. This review addresses the pertinent literature about using ANNs for membrane fouling prediction. Specifically, complementing other existing reviews that focus on mathematical models or broad AI-based simulations, the present review focuses on the use of AI-based fouling prediction models, namely, artificial neural networks (ANNs) and their derivatives, to provide deeper insights into the strengths, weaknesses, potential, and areas of improvement associated with such models for membrane fouling prediction.

A unified thermodynamic fouling mechanism based on forward osmosis membrane unique properties: An asymmetric structure and reverse solute diffusion

Fouling mechanism of the forward osmosis membrane, which was peculiarly featured by the asymmetric membrane structure and reverse solute diffusion, was investigated at the molecular level and from the energy perspective. Two noteworthy fouling behaviors were observed in batch fouling tests conducted in AL-FS mode (active layer facing feed solution) and AL-DS mode (active layer facing draw solution) after filtering foulants with identical volume: 1) after filtering 100 mL of foulants, the flux decline rate in AL-DS mode was 1.78 times faster than that in AL-FS mode, but the flux decline behaviors of the two modes were similar in the subsequent filtration stages; 2) although the foulant layer weight of the same mode increased linearly in middle and late stages, the flux loss rate was distinctly different. Thermodynamic analysis indicated that the attractive interaction energy between the foulants and the support layer was about 5 times higher than that between the foulants and the active layer, well interpreting the higher flux decline rate of AL-DS mode in initial stage. Meanwhile, a non-invasive microscope observed that the structure of the fouling layer remarkably changed from loose to dense in the middle stage, and stabilized in the late stage. Furthermore, quantum chemistry calculation proved that the reverse diffusion of NaCl brought alginate molecular chains closer, whereas the distance between them tended to be constant as the continuous increase of NaCl. Based on these findings, the thermodynamic fouling mechanism proposed by combining the structure change process of the fouling layer with Flory-Huggins lattice theory satisfactorily interpreted the noteworthy fouling behaviors caused by reverse NaCl diffusion in middle and late stages. The revealed fouling mechanism unifies the adhesion and filtration behaviors related to the unique properties of FO membrane, deepening understanding of membrane fouling in the dynamic and complex ternary system of the FO process.

DLVO Interactions between Particles and Rough Surfaces: An Extended Surface Element Integration Method

The surface element integration (SEI) method is a computationally facile technique for calculating DLVO interactions between particles and surfaces. This method yields the exact total DLVO interaction between a particle and a flat surface; however, all surfaces have some degree roughness that profoundly affects the interaction. Previously, an ad hoc approximate method has been used to extend the SEI method to interactions between particles and surfaces with arbitrary morphology. Here we derive a more rigorous approximate method based on the fundamental scaling of DLVO interactions, which approaches the exact solution as the separation distance decreases regardless of the particle or surface morphology. We verify this method by comparison to the exact van der Waals energy when roughness is present on the particle and surface. The accuracy of this method at small separations makes it well-suited for the contexts of particle adhesion and deposition in which the length scale of interaction is on the order of angstroms and nanometers, respectively.

Data-Driven Intelligent Warning Method for Membrane Fouling

Membrane fouling has become a serious issue in membrane bioreactor (MBR) and may destroy the operation of the wastewater treatment process (WWTP). The goal of this article is to design a data-driven intelligent warning method for warning the future events of membrane fouling in MBR. The main novelties of the proposed method are threefold. First, a soft-computing model, based on the recurrent fuzzy neural network (RFNN), was proposed to identify the real-time values of membrane permeability. Second, a multistep prediction strategy was designed to predict the multiple outputs of membrane permeability accurately by decreasing the error accumulation over the predictive horizon. Third, a warning detection algorithm, using the state comprehensive evaluation (SCE) method, was developed to evaluate the pollution levels of MBR. Finally, the proposed method was inserted into a warning system to complete the predicting and warning missions and further tested in the real plants to evaluate its efficiency and effectiveness. Experimental results have verified the benefits of the proposed method.

Effect of particle surface corrugation on colloidal interactions

HYPOTHESIS

Production of corrugated particles generally introduces several morphological heterogeneities, such as surface roughness and local variations in the corrugation pattern, which are known from model system studies to significantly alter the colloidal interaction energy. Thus, realistic particle morphologies need to be investigated and compared to simple model shapes to yield insights into how interactions are influenced by such morphological heterogeneities.

EXPERIMENTS

We applied the surface element integration method to study the colloidal interactions of electron tomography-based, realistic, corrugated colloidal particles and their symmetric, concave polyhedral analogs by differentiating local surface features to vertices, ridges and ridge networks. We applied molecular modelling to assess the surface access of these features.

FINDINGS

Significant mixing of the interaction energy was found between the different surface features. Larger and smaller energy barrier heights and secondary minimum depths were observed compared to the concave polyhedral models with similar volume or surface area depending on the contacting surface feature. Analysis of surface area distributions suggests that the deviations originate from the altered effective contact distance as a result of surface roughness and other morphological heterogeneities. We also found that the surface access of nanoparticles is greatly impaired at the crevices between the surface corrugations.

Fabrication of hierarchical layer-by-layer membrane as the photocatalytic degradation of foulants and effective mitigation of membrane fouling for wastewater treatment

A polyvinylidene fluoride plate sheet membrane coated 3D TiO₂/poly (sodium styrenesulfonate) (PSS) photocatalyst layers were fabricated via dip-coating layer-by-layer (LbL) assembly. Cationic TiO₂ and anionic PSS were alternately stacked on the support membrane via electrostatic interactions. The obtained modified membrane with (TiO₂/PSS)₇ exhibited optimal versatility under ultraviolet light irradiation in both dead-end and membrane reactor, which showed superior Lanasol Blue 3R (LB) removal rate to membrane filtration and biodegradation. The modified membranes (MM) exhibited good performance in terms of photocatalytic activity of foulant degradation and mitigation of membrane fouling in a membrane reactor. The obtained MM with (TiO₂/PSS)₇ exhibited optimal versatility under ultraviolet light irradiation in both dead-end and membrane reactors and superior Lanasol Blue 3R removal rate in membrane filtration and biodegradation. The MM (TiO₂/PSS)₇ possessed excellent antifouling properties by using bovine serum albumin (BSA), as evidenced by the extended Derjaguin-Landau-Verwey-Overbeek theory. Additionally, the TiO₂/PSS membrane showed good self-cleaning ability, and the foulants on the membrane surface could be degraded using ultraviolet light irradiation.

Optimizing carbon fibre supports for bioreactors by nitric acid oxidation and calcium ion coverage according to extended DLVO theory

Optimizing supports for microorganisms is required for bioreactors. Carbon fibres (CF) were employed as supports for microorganisms. To optimize CF supports for immobilizing bacterial cells, we used methods of nitric acid oxidation and calcium ion coverage. We evaluated the capacity of these CF supports (untreated CF, nitric acid oxidation CF and Ca²⁺-covered CF) via bacterial cell adhesion tests, based on extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory. The results implied that because of the high hamaker constants, oxidized CF supports had higher capacity in this regard than untreated CF supports. However, the growing oxygen groups increased the negative zeta potential of CF supports, thus likely to reduce their capacity, in accordance with XDLVO theory. Since the Ca²⁺ coverage could decrease the negative zeta potentials of CF without reducing the hamaker constants, it could enhance the capacity of oxidized CF supports. We concluded that a combination of nitric acid oxidation and Ca²⁺ coverage could increase the capacity of CF supports to immobilize bacterial cells.

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.

Dynamic membrane bioreactor performance enhancement by powdered activated carbon addition: Evaluation of sludge morphological, aggregative and microbial properties

The effects of powdered activated carbon (PAC) addition on sludge morphological, aggregative and microbial properties in a dynamic membrane bioreactor (DMBR) were investigated to explore the enhancement mechanism of pollutants removal and filtration performance. Sludge properties were analyzed through various analytical measurements. The results showed that the improved sludge aggregation ability and the evolution of microbial communities affected sludge morphology in PAC-DMBR, as evidenced by the formation of large, regularly shaped and strengthened sludge flocs. The modifications of sludge characteristics promoted the formation process and filtration flux of the dynamic membrane (DM) layer. Additionally, PAC addition did not exert very significant influence on the propagation of eukaryotes (protists and metazoans) and microbial metabolic activity. High-throughput pyrosequencing results indicated that adding PAC improved the bacterial diversity in activated sludge, as PAC addition brought about additional microenvironment in the form of biological PAC (BPAC), which promoted the enrichment of Acinetobacter (13.9%), Comamonas (2.9%), Flavobacterium (0.31%) and Pseudomonas (0.62%), all contributing to sludge flocs formation and several (such as Acinetobacter) capable of biodegrading relatively complex organics. Therefore, PAC addition could favorably modify sludge properties from various aspects and thus enhance the DMBR performance.

New insight into the fouling behavior of hydrophobic and hydrophilic polypropylene membranes in integrated membrane bioreactors

To investigate the effect of hydrophobic and hydrophilic polypropylene hollow fiber membranes (PPHFMs) applied in membrane bioreactors (MBR), the fouling behaviors of membrane surfaces and pores have been tested. The structural and morphological features on the membrane surface were characterized using attenuated total reflection-Fourier transform infrared spectroscopy, field emission scanning electron microscopy, atomic force microscope, energy dispersive X-ray spectroscopy and laser granularity distribution analysis. The results showed that significantly more polysaccharide, protein and inorganic ingredients were accumulated in the original membrane compared to the hydrophilic membrane. Furthermore, it was found that the pore size influenced the particle distribution and accumulation, such that smaller pore size membranes tended to contain fewer pollutants and a narrow size distribution. Under a constant flux of 11.5 L/m² h, the transmembrane pressure (TMP) varied narrowly between 38 and 53 KPa. Alongside this, a relatively hydrophilic membrane (PP-g-AA) showed the characteristics of lower TMP in comparison to hydrophobic membranes (PP). Indeed, the flux recovery was 30% higher than those of the original PPHFM. This investigation broadens our understanding of membrane modifying and fouling behavior in integrated MBRs.

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.

Impacts of morphology on fouling propensity in a membrane bioreactor based on thermodynamic analyses

Impacts of morphologies of both membrane and foulant on interaction energies related with adhesive fouling in a membrane bioreactor (MBR) were explored by thermodynamic analyses. Interaction energies in three possible interaction scenarios regarding different membrane and foulant morphologies under conditions in this study were quantified according to the thermodynamic methods. It was interestingly found that, strength of total interaction between soluble microbial products (SMPs) and rough membrane was over 20,000 times of that between sludge flocs and rough membrane under same conditions, indicating the extremely higher adhesion ability of SMPs than the large particulate foulants. This result plausibly explained the high fouling propensity of SMPs over sludge flocs. As compared with smooth surfaces, rough surfaces of both membrane and sludge flocs significantly reduced total interaction strength, alleviating adhesive fouling caused by the sludge flocs. Reduce in fractal dimension (D_f) of membrane increased adhesive fouling caused by the SMPs, but alleviated adhesive fouling caused by the sludge flocs. These findings gave important implications to better understand and control membrane fouling in MBRs.

Treatment of palm oil mill effluent using combination system of microbial fuel cell and anaerobic membrane bioreactor

It was found that the operational temperature and the incorporation of microbial fuel cell (MFC) into anaerobic membrane bioreactor (AnMBR) have significant effect on AnMBRs' filtration performance. This paper addresses two issues (i) effect of temperature on AnMBR; and (ii) effect of MFC on AnMBRs' performance. The highest COD removal efficiency was observed in mesophilic condition (45°C). It was observed that the bioreactors operated at 45°C had the highest filtration resistance compared to others, albeit the excellent performance in removing the organic pollutant. Next, MFC was combined with AnMBR where the MFC acted as a pre-treatment unit prior to AnMBR and it was fed directly with palm oil mill effluent (POME). The supernatant from MFC was further treated by AnMBR. Noticeable improvement in filtration performance was observed in the combined system. Decrease in polysaccharide amount was observed in combined system which in turn suggested that the better filtration performance.

Membrane fouling in a submerged membrane bioreactor: An unified approach to construct topography and to evaluate interaction energy between two randomly rough surfaces

Quantitatively evaluating interaction energy between two randomly rough surfaces is the prerequisite to quantitatively understand and control membrane fouling in membrane bioreactors (MBRs). In this study, a new unified approach to construct rough topographies and to quantify interaction energy between a randomly rough particle and a randomly rough membrane was proposed. It was found that, natural rough topographies of both foulants and membrane could be well constructed by a modified two-variable Weierstrass-Mandelbrot (WM) function included in fractal theory. Spatial differential relationships between two constructed surfaces were accordingly established. Thereafter, a new approach combining these relationships, surface element integration (SEI) approach and composite Simpson's rule was deduced to calculate the interaction energy between two randomly rough surfaces in a submerged MBR. The obtained results indicate the profound effects of surface morphology on interaction energy and membrane fouling. This study provided a basic approach to investigate membrane fouling and interface behaviors.

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.

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.

Dynamic changes of dissolved organic matter in membrane bioreactors at different organic loading rates: Evidence from spectroscopic and chromatographic methods

Excitation emission matrix-parallel factor analysis (EEM-PARAFAC) and size exclusion chromatography (SEC) were utilized to explore the dynamics in extracellular polymeric substances (EPS), soluble microbial products (SMP), and effluent for the membrane bioreactors at two different organic loading rates (OLRs). Combination of three different fluorescent components explained the compositional changes of dissolved organic matter. The lower OLR resulted in a higher production of tryptophan-like component (C1) in EPS, while the opposite trends were found for the other two components (humic-like C2 and tyrosine-like C3), signifying the role of C1 in the endogenous condition. Larger sized molecules were more greatly produced in EPS at the lower OLR. Meanwhile, all the size fractions of SMP were more abundant at the higher OLR particular for the early phase of the operation. Irrespective of the OLR, the higher degrees of the membrane retention were found for relatively large sized and protein-like molecules.

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 (D_f) 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 (D_f) 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 D_f was the critical factor affecting surface morphology, while other factors exerted moderate or minor effects on the roughness of biocake layer.