Fouling sensors for water filtration membranes and methods of using the same

Abstract

There is provided herein, a fouling sensor for assessing the extent of fouling of nanofiltration (NF) and / or Reverse Osmosis (RO) membranes before / during water filtration and / or membrane cleaning, the sensor including: a substrate having noble metal nanoparticles on a surface thereof; and a polymer layer associated with the noble metal nanoparticles, wherein the polymer layer is characterized by similar physico-chemical properties as an active layer of the NF and / or RO membranes. Additionally, disclosed herein are methods of assessing and predicting fouling in NF / RO membrane(s) of a water filtration system using the provided fouling sensor.

Description

[0001] FOULING SENSORS FOR WATER FILTRATION MEMBRANES AND METHODS

[0002] OF USING THE SAME

[0003] TECHNICAL FIELD

[0004] The present disclosure relates to the field of water filtration. More specifically, the disclosure relates to sensors for monitoring the extent of fouling in water filtration membranes and methods of using the same.

[0005] BACKGROUND

[0006] Municipal wastewater re-use is an important alternative water source worldwide and is currently applied mainly in agriculture and to replenish water bodies. However, this practice distributes soluble salts and organic substances from the effluent back into the environment, limiting the sustainability of effluent use. Wastewater effluent in irrigation may increase soil salinity, affect the physical properties of soil, and change soil hydraulic conductivity, with consequent reduction in crop yields. Furthermore, technologies commonly used in wastewater treatment plants (WWTPs) do not address the increasing concentrations of micropollutants in wastewater, even after tertiary treatment. Thus, the discharge of wastewater effluent into the environment and its use in irrigation have environmental costs that require attention.

[0007] Desalination of wastewater effluent using reverse osmosis (RO) or nanofiltration (NF) membranes is helpful in removing ions, micropollutants, and residual microbial pollution after advanced wastewater treatment, with benefits including the production of potable water and reduced stress on depleted water resources. However, the complex composition of wastewater effluent, including the presence of organic matter (OM) and microorganisms, makes single- step wastewater desalination costly and challenging. In this context, the integration of wastewater treatment processes that remove OM and most microorganisms, and subsequent low-pressure RO desalination, is promising for the production of high-quality water. The main drawback of membrane-based technology in general and wastewater effluent desalination in particular is membrane fouling, which can result in plant downtime, increased energy consumption, and other operational costs. Organic fouling during desalination of tertiary effluents is caused by the adsorption of effluent OM (EfOM) on the membrane surface. EfOM comprises natural OM, synthetic organic compounds from domestic use, soluble microbial products (SMPs) produced by microorganisms during biological treatment, and extracellular polymeric substances (EPSs) from microbial biofilms. SMPs and EPSs comprise humic substances, polysaccharides, proteins, lipids, nucleic and amino acids, organic acids, and cell components. In addition to causing fouling, EfOM acts as a conditioning film that promotes cell attachment and biofilm growth on membranes. The first thin layer of organic or inorganic substances deposited on the membrane surface, the “conditioning film”, alters the physicochemical characteristics of the surface, including the hydrophobicity, charge, and roughness, thereby promoting bacterial deposition and consequent biofilm formation.

[0008] The approaches employed to mitigate fouling include pre-treatment of effluent feedwater, optimization of membrane processing conditions, use of low-fouling membranes, careful selection of biocides and antibacterial agents, development of new membrane modules and spacer design, and in-line physical and chemical cleaning.

[0009] Nevertheless, membrane fouling is usually inevitable in the longer term. The malfunction of the membrane and suitable pretreatment design may be revealed too late to optimize it in a reasonable operational timeframe. In addition, the final step in removing fouling from a membrane is chemical cleaning. For RO / NF membranes, this typically involves the use of alkaline or acidic solutions, metal chelating agents, and surfactants, all of which reduce membrane module lifetime and produce hazardous waste, meaning their use should be minimized.

[0010] Therefore, accurate and timely fouling sensors are essential in such systems in order to prevent performance degradation and high operational costs. Current fouling sensors, which typically rely on pressure, flow, and differential measurement techniques, have significant limitations. The sensing techniques, which track changes in pressure drop and flow rate across the membrane, commonly provide a direct indication of fouling, though resulting in delayed detection. The most common sensing techniques include silt density index (SDI), turbidity, and particle counters, which can detect particulate fouling in the feed water, however, they do not accurately represent fouling on the membrane itself. Real-time monitoring technologies like electrical impedance spectroscopy offer more direct insights but are often costly and complex to implement. Overall, these methods may lack the sensitivity and specificity needed for timely, accurate, and effective fouling management, potentially leading to reduced efficiency and membrane lifespan.

[0011] Accordingly, there is a need in the art for a sensor device that can predict the tendency of water to foul the RO / NF membrane in real time and with high sensitivity, while allowing operational responses that are time and cost effective.

[0012] SUMMARY

[0013] The disclosure is directed, in embodiments thereof, to an optical fouling sensor device for a water filtration membrane. The sensor includes gold nanoparticle plasmon probes associated with a polymer layer configured to undergo fouling, similarly to a corresponding water filtration membrane during a water filtration process.

[0014] According to some embodiments, the sensor facilitates the monitoring of an accumulation of foulant in a water filtration membrane, such as, but not limited to, a reverse osmosis membrane (RO) and / or nanofiltration (NF) membrane. The monitoring, according to some embodiments, is advantageously simple and may be utilized before, during and / or after the water filtration process. In some embodiments, the sensor predicts the fouling of the water filtration membrane prior to introducing a water flow to the membrane itself. In some embodiments, the prediction may be done via a simulated water filtration process, and in some other embodiments, the prediction may be done prior to introducing the water flow to a water filtration system in general.

[0015] According to some embodiments, the sensing is via optical means utilizing the advantageous response of a localized surface plasmon resonance (LSPR) of the gold nanoparticles.

[0016] Advantageously, the polymer layer possesses some physico-chemical properties similar to the active layer of the water filtration membrane.

[0017] Advantageously, the sensor can be applied, in accordance with some embodiments, in a water filtration membrane operating in various types of water originating from, but not limited to, seawater, wastewater, sewage water, drinking water, irrigation water, groundwater, pool water, physiological water, and any post treated version thereof, such as secondary or tertiary water, to name a few.

[0018] The advantageous sensor can be utilized, according to some embodiments, before, during and / or after a procedure of cleaning the water filtration membrane, thus allowing an optimization thereof.

[0019] In addition, there is provided, in accordance with some embodiments, a method of sensing / monitoring the development of the fouling in the water filtration membrane. In some embodiments, the monitoring method may be applied in real-time.

[0020] According to some further embodiments, there is provided herein a method of producing the fouling sensor.

[0021] There is provided herein, in accordance with some embodiments, a fouling sensor for predicting and / or assessing the extent of fouling of nanofiltration (NF) and / or Reverse Osmosis (RO) membranes before and / or during water filtration and / or membrane cleaning, the sensor including: a substrate having noble metal nanoparticles on a surface thereof; and a polymer layer associated with the noble metal nanoparticles, wherein the polymer layer is characterized by similar physico-chemical properties as an active layer of the NF and / or RO membranes, and thereby the polymer layer is configured to mimic the fouling of the membranes active layer before and / or during the water filtration and / or membrane cleaning, wherein when light impinges the sensor, it is reflected and / or transmitted in a characteristic ,max, wherein a change in Xmax enables quantifying the adsorbed foulant to the sensor and therefore, is indicative of the extent of membrane’s fouling before and / or during water filtration and / or membrane cleaning.

[0022] According to some embodiments, the physico-chemical properties include properties of surface hydrophobicity and / or surface charge.

[0023] According to some embodiments, the hydrophobicity of the polymer layer is characterized by a wetting angle of about 50°-80°. According to some embodiments, the surface charge is a negative charge expressed by a zeta potential of about (-30)-(-60) mV in conditions of 10 mM solution of NaCl and pH 7.

[0024] According to some embodiments, the polymer is selected from a group consisting of linear polyamide, aromatic polyamide, crossed-linked aromatic polyamide, cellulose-based polymer, polyamine, polymethacrylate, polyethersulfone (PES), polysulfone (PSU), polyester, poly vinylidene fluoride (PVDF), polyacrylonitrile, and any combination thereof. According to some embodiments, the linear polyamide includes Nylon 6,6.

[0025] According to some embodiments, water treated by the water filtration is selected from the group consisting of seawater, wastewater, sewage water, drinking water, irrigation water, groundwater, pool water, physiological water, and membrane cleaning solution.

[0026] According to some embodiments, the noble metal nanoparticles are in a form selected from the group consisting of nano-discs, nano-rods, nano-spheres, nano-plates, nano-dots, nano-islands, and any combination thereof.

[0027] According to some embodiments, the noble metal nanoparticles include a metal selected from the group consisting of gold, silver, and platinum. According to some embodiments, the noble metal nanoparticles include gold.

[0028] According to some embodiments, the noble metal nanoparticles have a diameter of about 12-150 nm. According to some embodiments, the noble metal nanoparticles have a diameter of about 110-140 nm.

[0029] According to some embodiments, the substrate is selected from a group consisting of silica, alumina, titania, and zirconia. According to some embodiments, the substrate is a silica substrate.

[0030] According to some embodiments, the fouling sensor further includes a coupling agent for associating the substrate with the polymer layer. According to some embodiments, the coupling agent is a silane coupling agent. According to some embodiments, the silane coupling agent includes a functional moiety selected from the group consisting of amine, amide, pyridine, alcohol, carbonyl, alkyl, nitrile, ester, and any combination thereof. According to some embodiments, the silane coupling agent is an amino silane. According to some embodiments, there is provided herein a use of the sensor disclosed herein to assess fouling of the NF and / or RO membranes before and / or during water filtration.

[0031] According to some embodiments, there is provided herein a use of the sensor disclosed herein to assess removal of fouling from the NF and / or RO membranes during cleaning thereof.

[0032] There is provided herein, in accordance with some embodiments, a method of predicting and / or sensing fouling of nanofiltration (NF) and / or Reverse Osmosis (RO) membranes before and / or during a water filtration and / or membrane cleaning, the method including: providing NF and / or RO membranes; providing a fouling sensor for predicting and / or assessing the extent of fouling of the NF and / or RO membranes, wherein the sensor is positioned in NF- and / or RO- based water filtration system, the sensor including noble metal nanoparticles associating with a polymer layer, wherein the polymer layer is characterized by similar physico-chemical properties as an active layer of the NF and / or RO membranes, and thereby the polymer layer is configured to adsorb and / or desorb foulant to a similar extent as the active layer of the NF and / or RO membranes before and / or during water filtration and / or membrane cleaning; introducing a water flow to the NF- and / or RO- based water filtration system such that the water flow contacts the sensor during the water filtration or membrane cleaning; irradiating light on the sensor to induce a reflected and / or transmitted light with a characteristic range of wavelengths; detecting the reflected and / or transmitted light; and determining a change in a characteristic Xmax before and / or during the water filtration and / or membrane cleaning, wherein the change in Xmax facilitates quantifying the adsorbed and / or desorbed foulant to the sensor and therefore, is indicative of the extent of membrane’s fouling before and / or during water filtration and / or membrane cleaning.

[0033] According to some embodiments, the sensor is configured to be positioned beside, upstream, downstream, and / or within the membrane. There is provided herein, in accordance with some embodiments, A method of simulating and predicting and / or assessing fouling of NF and / or RO membranes before and / or during a simulation of water filtration and / or membrane cleaning, the method including: providing a fouling sensor configured to be positioned instead of NF and / or RO membranes to simulate and assess an extent of fouling in the membranes, wherein the sensor including noble metal nanoparticles associating with a polymer layer, wherein the polymer layer is characterized by similar physico-chemical properties as an active layer of the membranes, and thereby the polymer layer is configured to adsorb foulant to a similar extent as the active layer of the membranes before and / or during water filtration and / or membrane cleaning; flowing water such that the water flow contacts the sensor before and / or during the simulation of the water filtration and / or membrane cleaning; irradiating light on the sensor to induce a reflected and / or transmitted light with a characteristic range of wavelengths; detecting the reflected and / or transmitted light; and determining a change in a characteristic Xmax before and / or during the simulation of the water filtration and / or membrane cleaning, wherein the change in Xmax enables quantifying the adsorbed foulant to the sensor and therefore, is indicative of the extent of a simulated membrane’s fouling before and / or during water filtration and / or membrane cleaning.

[0034] According to some embodiments, the extent of the fouling is assessed continuously, during the water filtration.

[0035] According to some embodiments, the extent of the fouling is assessed in one or more selected time points.

[0036] There is provided herein, in accordance with some embodiments, a method of producing a fouling sensor for RO and / or NF membranes, the method including: providing a substrate associated with noble metal nanoparticles; and applying a polymer layer atop the noble metal nanoparticles, thereby producing the fouling sensor. According to some embodiments, the method further includes cleaning the substrate before applying the polymer layer.

[0037] According to some embodiments, the cleaning includes a treatment selected from UV / ozone, plasma, sonication, solvent dip-washing, solvent spray-washing, acidic solution treatment, alkaline solution treatment, drying, and any combination thereof.

[0038] According to some embodiments, further including applying a coupling layer on the substrate, to facilitate the application of the polymer layer.

[0039] According to some embodiments, the application of the polymer layer is via a technique selected from a group consisting of interfacial polymerization, spin coating, drop casting, spraying, vapor deposition, and any combination thereof.

[0040] There is provided herein, in accordance with some embodiments, a system of NF- and / or RO-based water filtration, the system including:

[0041] NF and / or RO membranes; a fouling sensor for assessing the extent of fouling of the NF and / or RO membranes or membrane sets, wherein the sensor including a substrate having noble metal nanoparticles on a surface thereof, wherein the noble metal nanoparticles are associated with a polymer layer, wherein the polymer layer is characterized by similar physico-chemical properties as an active layer of the NF and / or RO membranes, and thereby the polymer layer is configured to adsorb / desorb foulant to a similar extent as the active layer of the NF and / or RO membranes during water filtration and / or membrane cleaning; a water flow conduit system configured to direct water flow to contact the sensor and the NF and / or RO membranes before and / or during the water filtration and / or membrane cleaning; a light source configured to irradiate light on the sensor; an optical detector configured to detect light reflected and / or transmitted from and / or through the sensor; and a processing circuitry configured to: determine a characteristic A,max of the reflected and / or transmitted light; determine a change in kmax detected before and / or during the water filtration and / or membrane cleaning; and calculate an extent of fouling of the sensor based on the change in Z,max, and accordingly assess the extent of fouling of the membrane’s active layer.

[0042] Certain embodiments of the present disclosure may include some, all, or none of the above advantages. One or more technical advantages may be readily apparent to those skilled in the art from the figures, descriptions and claims included herein. Moreover, while specific advantages have been enumerated above, various embodiments may include all, some or none of the enumerated advantages.

[0043] In addition to the exemplary aspects and embodiments described above, further aspects and embodiments will become apparent by reference to the figures and by study of the following detailed descriptions.

[0044] BRIEF DESCRIPTION OF THE FIGURES

[0045] Some embodiments of the disclosure are described herein with reference to the accompanying figures. The description, together with the figures, makes apparent to a person having ordinary skill in the art how some embodiments may be practiced. The figures are for the purpose of illustrative description and no attempt is made to show structural details of an embodiment in more detail than is necessary for a fundamental understanding of the disclosure. For the sake of clarity, some objects depicted in the figures are not to scale.

[0046] In the figures:

[0047] FIGURE la - shows an exemplary flow diagram of using a fouling sensor prior to the introduction of a water flow to reverse osmosis (RO) water filtration system, according to some embodiments;

[0048] FIGURE lb - shows a flowchart of steps of a method for sensing fouling of water filtration membrane, according to some embodiments; FIGURE 2 - shows a flowchart of steps of a method for producing a fouling sensor for water filtration membrane, according to some embodiments;

[0049] FIGURE 3 - shows an exemplary bar graph of total organic compound (TOC) of hydrophobicity-based fractions (five repetitions of five different types of fractions) in effluent organic matter (EfOM) mix samples (30 mg TOC), expressed as a percentage of the EfOM TOC content, according to some embodiments;

[0050] FIGURE 4 - shows an exemplary scheme of a lab-scale RO cross-flow filtration system for comparison of the fouling degree of each EfOM fraction and the EfOM mix, according to some embodiments;

[0051] FIGURE 5 - shows an exemplary graph of normalized permeate flux vs. time for each of the EfOM fractions and the EfOM mix as deduced from the exemplary RO crossflow filtration system (FIG. 5). Boundaries between areas of gray and white shading indicate a change in solution from a background solution (BS) to different fractions or the EfOM mix. The five EfOM fractions and EfOM mix were adjusted to the same final TOC content (5 mg-L-1), according to some embodiments;

[0052] FIGURE 6 - shows an exemplary bar graph of intrinsic hydraulic resistance of the EfOM fractions and EfOM mix, according to some embodiments;

[0053] FIGURE 7 - shows an exemplary bar graph of mass surface concentration, Ts, accumulated on the surface of the disclosed fouling sensor, LSPR membrane-mimetic sensor, measured using the Nano-X2 device after 1.5 h of adsorption from a background solution, according to some embodiments. The five EfOM fractions and EfOM mix were adjusted to the same final TOC content (5 mg-L-1), according to some embodiments;

[0054] FIGURE 8a - shows an exemplary bar graph of a total RO flux decline (%) for model foulants and a secondary effluent during filtration, according to some embodiments. Model foulants’ concentration was 100 mg / L (w / v) and secondary effluents had a DOC concentration of 10.73±0.203 mg / L, according to some embodiments. The model foulants were examined under three different aquatic conditions with similar ionic strength of 10 mM: 10 mM NaCl in pH 5 (black bar); lOmM NaCl in pH 7 (dark grey bar); and 8.5mM NaCl + 0.5mM CaCh (light grey bar); FIGURE 8b - shows an exemplary graph of a normalized flux decline (J / Jo [-]) vs. time of filtration when the foulant model is humic acid, according to some embodiments. The model foulant was examined under three different aquatic conditions with similar ionic strength of 10 mM: 10 mM NaCl in pH 5 (black bar); 10 mM NaCl in pH 7 (dark grey bar); and 8.5 mM NaCl + 0.5 mM CaCL (light grey bar). The dashed lines indicate a change in the feeding solution, switching from the background solution (BS) to the humic acid foulant solution and back to the BS, according to some embodiments. Model foulants’ concentration was 100 mg / L (w / v);

[0055] FIGURE 8c - shows an exemplary graph of a normalized flux decline (J / Jo [-]) vs. time of filtration when the foulant model is alginate, according to some embodiments. The model foulant was examined under three different aquatic conditions with similar ionic strength of 10 mM: 10 mM NaCl in pH 5 (black bar); 10 mM NaCl in pH 7 (dark grey bar); and 8.5 mM NaCl + 0.5 mM CaCh (light grey bar). The dashed lines indicate a change in the feeding solution, switching from the background solution (BS) to the alginate foulant solution and back to the BS, according to some embodiments. Model foulants’ concentration was 100 mg / L (w / v);

[0056] FIGURE 8d - shows an exemplary graph of a normalized flux decline (J / Jo [-]) vs. time of filtration when the foulant model is athletes’ protein, according to some embodiments. The model foulant was examined under three different aquatic conditions with similar ionic strength of 10 mM: 10 mM NaCl in pH 5 (black bar); 10 mM NaCl in pH 7 (dark grey bar); and 8.5 mM NaCl + 0.5 mM CaCh (light grey bar). The dashed lines indicate a change in the feeding solution, switching from the background solution (BS) to the athletes’ protein foulant solution and back to the BS, according to some embodiments. Model foulants’ concentration was 100 mg / L (w / v);

[0057] FIGURE 8e - shows an exemplary graph of a normalized flux decline (J / Jo [-]) vs. time of filtration when the foulant is a secondary effluent, according to some embodiments. The dashed lines indicate a change in the feeding solution, switching from the background solution (BS) to the secondary effluent solution and back to the BS, according to some embodiments. The secondary effluents had a DOC concentration of 10.73+0.203 mg / L;

[0058] FIGURE 9 - shows an exemplary bar graph of a hydraulic resistance of the fouling layers formed by the three foulant models at lOmM NaCl (pH 7) and at 8.5mM NaCl+0.5mM CaCh and from the fouling layer formed by the secondary effluents, according to some embodiments;

[0059] FIGURE 10 - shows an exemplary graph of shifts in the maximum wavelength peak position, kmax, during exposure of the sensor to ethylene glycol at four different concentrations of 5%, 10%, 15% and 20%, vs. their corresponding refractive indexes (insert graph) to analyze the sensor sensitivity (So), according to some embodiments.

[0060] FIGURE 11 - shows an exemplary graph of a refractive index increment, dn / dc [cm3 / g] estimation for Alginate and Humic acid, according to some embodiments;

[0061] FIGURE 12a - shows an exemplary graph of a shift in maximum wavelength peak position, kmax, for a 2-hour adsorption period of the humic acid model foulant, according to some embodiments. In this period, the foulant accumulated on the surface of the disclosed fouling sensor, the LSPR membrane-mimetic sensor hosted in the XNano device (Insplorion AB, Gotenburg, Sweden), according to some embodiments. The model foulant had a concentration of 100 mg / L (w / v);

[0062] FIGURE 12b - shows an exemplary graph of a shift in maximum wavelength peak position, kmax, for a 2-hour adsorption period of the alginate model foulant, according to some embodiments. In this period, the foulant accumulated on the surface of the disclosed fouling sensor, the LSPR membrane-mimetic sensor hosted in the XNano device (Insplorion AB, Gotenburg, Sweden), according to some embodiments. The model foulant had a concentration of 100 mg / L (w / v);

[0063] FIGURE 12c - shows an exemplary graph of a shift in maximum wavelength peak position, kmax, for a 2-hour adsorption period of the athlete’s protein model foulant, according to some embodiments. In this period, the foulant accumulated on the surface of the disclosed fouling sensor, the LSPR membrane-mimetic sensor hosted in the XNano device (Insplorion AB, Gotenburg, Sweden), according to some embodiments. The model foulant had a concentration of 100 mg / L (w / v);

[0064] FIGURE 12d - shows an exemplary graph of a shift in maximum wavelength peak position, kmax, for a 2-hour adsorption period of the secondary effluent model foulant, according to some embodiments. In this period, the foulant accumulated on the surface of the disclosed fouling sensor, the LSPR membrane-mimetic sensor hosted in the XNano device (Insplorion AB, Gotenburg, Sweden), according to some embodiments. The secondary effluents had a TOC concentration of 10.73±0.203 mg / L;

[0065] FIGURE 13a - shows an exemplary graph of a mass surface concentration, Ts [ng / cm2], of humic acid foulant model accumulated on the surface of the LSPR membranemimetic sensor, measured during 2 hours of adsorption period, according to some embodiments. The adsorption was performed under three different aquatic conditions with total ionic strength of 10 mM (lOmMNaCl in pH 5 (black), lOmMNaCl in pH 7 (grey), and 8.5mM NaCl + 0.5mM CaCb (white)). The model foulant had a concentration of 100 mg / L (w / v);

[0066] FIGURE 13b - shows an exemplary graph of a mass surface concentration, Ts [ng / cm2], of alginate foulant model accumulated on the surface of the LSPR membranemimetic sensor, measured during 2 hours of adsorption period, according to some embodiments. The adsorption was performed under three different aquatic conditions with total ionic strength of 10 mM (lOmMNaCl in pH 5 (black), lOmMNaCl in pH 7 (grey), and 8.5mM NaCl + 0.5mM CaCb (white)). The model foulant had a concentration of 100 mg / L (w / v);

[0067] FIGURE 13c - shows an exemplary graph of a mass surface concentration, Ts [ng / cm2], of athletes’ protein foulant model accumulated on the surface of the LSPR membrane-mimetic sensor, measured during 2 hours of adsorption period, according to some embodiments. The adsorption was performed under three different aquatic conditions with total ionic strength of 10 mM (lOmMNaCl in pH 5 (black), lOmMNaCl in pH 7 (grey), and 8.5mM NaCl + 0.5mM CaCb (white)). The model foulant had a concentration of 100 mg / L (w / v);

[0068] FIGURE 13d - shows an exemplary graph of a mass surface concentration, Ts [ng / cm2], of the dissolved organic matter of secondary effluent accumulated on the surface of the LSPR membrane-mimetic sensor, measured during 2 hours of adsorption period, according to some embodiments. The secondary effluents had a TOC concentration of 10.73±0.203 mg / L;

[0069] FIGURE 13e - shows an exemplary graph of a maximum mass surface concentration, Ts [ng / cm2], of the three foulant models and the dissolved organic matter of secondary effluent accumulated on the surface of the LSPR membrane-mimetic sensor, measured during 2 hours of adsorption period, according to some embodiments; and FIGURE 14 - shows an exemplary bar graph of Silt Density Index (SDI) results for all foulant models (10 mM NaCl and 8.5 mM NaCl + 0.5 CaCh, pH 7) and secondary effluents, according to some embodiments.

[0070] DETAILED DESCRIPTION

[0071] In the following description, various aspects of the disclosure will be described. For the purpose of explanation, specific configurations and details are set forth in order to provide a thorough understanding of the different aspects of the disclosure. However, it will also be apparent to one skilled in the art that the disclosure may be practiced without specific details being presented herein. Furthermore, well-known features may be omitted or simplified in order not to obscure the disclosure.

[0072] Prior to setting forth the present subject matter in detail, it may be helpful to provide definitions of certain terms to be used herein. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as is commonly understood by one of skill in the art to which this subject matter pertains. The following definitions are provided for clarity.

[0073] The term "a" or "an" as used herein includes the singular and the plural, unless specifically stated otherwise. Therefore, the terms "a," "an", "at least one", or “at least two” can be used interchangeably in this application.

[0074] As used herein, the verb "comprise" as is used in this description and in the claims and its conjugations are used in its non-limiting sense to mean that items following the word are included, but items not specifically mentioned are not excluded.

[0075] As used herein, the term "about" when used in connection with a numerical value includes ±10% from the indicated value. In addition, all ranges directed to the same component or property herein are inclusive of the endpoints, are independently combinable, and include all intermediate points and ranges. It is understood that where a parameter range is provided, all integers within that range, and tenths thereof, are also provided by the invention.

[0076] As used herein, in accordance with some embodiments, the term “water filtration membrane” refers to nanofiltration (NF), reverse osmosis (RO), or forward osmosis (FO) membrane. According to some embodiments, the water filtration membrane may be a single or a set of membranes. In some embodiments, the set of membranes are arranged in parallel or series.

[0077] As used herein, in accordance with some embodiments, the term “water filtration system” refers to a system intended for cleaning / purification of water, such as desalination of water. The system, in accordance with some embodiments, produces water with a reduced amount of one or more types of undesired entities. Examples of one or more types of undesired entities may include, but are not limited to, small molecules, charged small molecules, metal ions, or macromolecules. According to some embodiments, the system contains one or more water filtration membranes to enable the production of water with a desired content and purity level. According to some embodiments, the system includes reverse osmosis (RO) and / or nanofiltration (NF) membranes. According to some embodiments, the water filtration system includes the RO and / or NF membranes as a single membrane(s) and / or as a membrane set(s).

[0078] As used herein, in accordance with some embodiments, the term “fouling” refers to the deposition and accumulation of organic, inorganic, or biological matter and is termed a “foulant”. The foulant resides on, and / or within, a surface’s membrane, in accordance with some embodiments. In some embodiments, the fouling results in a reduction in permeate flux, which in turn causes a reduction in the performance of the water filtration.

[0079] As used herein, in accordance with some embodiments, the term “reverse osmosis membrane (RO)” refers to a semi-permeable membrane used in water purification. The membrane operates by allowing water molecules to pass through while blocking the passage of dissolved salts, organic compounds, and other impurities, including common ions like sodium (Na+), chloride (O'), calcium (Ca2+), and sulfate (SO42'), according to some embodiments. Multivalent ions (e.g., Ca2+, SO42') are generally rejected more effectively than monovalent ions (e.g., Na+, Cl") due to their larger hydrated sizes and stronger interaction with the membrane surface. This semi-permeable membrane operates under high pressure, effectively removing contaminants to produce clean, potable water, according to some embodiments. RO membranes are essential in applications such as desalination and wastewater treatment and provide high-purity water for industrial processes. According to some embodiments, the typical membrane generally includes, but is not limited to, an active layer that performs the actual selective filtration, a porous support layer, and a backing layer. According to some exemplifying embodiments, the active layer includes, but is not limited to, a dense polyamide layer having a typical thickness of about 100-200 nanometers and a pore size of less than about 0.001 um. In some embodiments, the support layer includes, but is not limited to, a porous polysulfone (PS) or polyether sulfone (PES), and the backing layer includes, but is not limited to, a non-woven fabric layer.

[0080] As used herein, in accordance with some embodiments, the term “nanofiltration membrane (NF)” refers to a semi-permeable membrane used in water treatment processes to remove dissolved solutes, such as small organic molecules, divalent ions (like Ca2+and Mg2+), and certain salts, while allowing monovalent ions (such as Na+and Cl") and water molecules to pass through. According to some embodiments, the NF membrane operates at lower pressures compared to the RO membrane and is particularly effective for applications requiring selective removal of specific contaminants, such as softening hard water, treating wastewater, and producing high-quality water for industrial processes. According to some embodiments, the NF membrane includes a dense active layer such as, but not limited to, polyamide that provides the selectivity needed for the nanofiltration process. In some embodiments, the active layer of the NF membrane is characterized by a larger pore size than the RO, typically between 0.001 to 0.01 um. According to some embodiments, the membrane’s active layer is supported, typically by a porous layer such as polysulfone (PS) or polyether sulfone (PES), and a nonwoven fabric backing layer.

[0081] As used herein, in accordance with some embodiments, the term “similar physicochemical properties” refers to one or more physico-chemical properties of RO and / or NF membranes, or specifically of the membranes’ active layer, that are similar to one or more of the physical properties of the polymer layer of the disclosed fouling sensor. Examples include, according to some embodiments, but are not limited to, surface charge, hydrophobicity, or polarity. Each possibility is a separate embodiment.

[0082] As used herein, in accordance with some embodiments, the term “fouling sensor” refers to a device, module, or subsystem whose purpose it is to detect events or changes in its environment and send / signal the information to other electronics, such as a data acquisition and monitoring system. The sensor, according to some embodiments, typically includes a sensitive surface which is the part of the sensor responsible for perceiving said events or changes. In some embodiments, the surface-sensitive sensor detects fouling, i.e. the deposition of foulant, at the surface thereof. In some embodiments, the sensor is covered or coated with a polymer layer that mimics some of the physico-chemical properties of the RO / NF membrane’s active layer. According to some embodiments, a fouling on said polymer is detected by the sensor. According to some embodiments, the detection of the fouling is facilitated by noble metal nanoparticles’ plasmons that are associated with the polymer layer. According to some embodiments, the plasmons serve as an optical probe to a change in their environment (e.g., the evolvement of a foulant). In some embodiments, the plasmons indicate this change as a change in their optical properties.

[0083] As used herein, in accordance with some embodiments, the term “mimic” refers to imitating a fouling tendency related to RO and / or NF membranes, or specifically an active layer thereof, upon operation or cleaning thereof. In some embodiments, the capability of a polymer layer to mimic the fouling of the RO and / or NF membranes is a result of mimicking part of their physico-chemical properties, and thereby the corresponding tendency towards fouling.

[0084] As used herein, in accordance with some embodiments, the term “characteristic A,max” refers to the characteristic peak wavelength where plasmonic nanoparticles demonstrate maximum absorption or reflection due to their surface plasmon resonance.

[0085] As used herein, in accordance with some embodiments, the term “characteristic range of wavelengths” refers to the characteristic range of wavelengths where plasmonic nanoparticles demonstrate absorption or reflection at different intensities, across the spectrum, due to their surface plasmon resonance.

[0086] As used herein, in accordance with some embodiments, the terms “localized surface plasmon resonance” and “LSPR” refer to the collective oscillation of free electrons on the surface of metal nanoparticles when they are exposed to light of a specific wavelength, a wavelength that matches the frequency of oscillation. This resonance phenomenon causes enhanced absorption and reflection of light, leading to unique optical properties that depend on the size, shape, and material of the nanoparticles, in accordance with some embodiments, and in particular, the properties depend on the environment of the nanoparticles. According to some embodiments, sensitivity towards changes in the environment of the nanoparticles makes them highly sensitive probes at the nanoscale.

[0087] As used herein, in accordance with some embodiments, the term “substrate” refers to a base layer supporting the noble metal nanoparticles and the polymer layer. The term also refers to the base layer that supports an assembly of the noble metal nanoparticles and the polymer layer, according to some embodiments. In some embodiments, the substrate can be made of, but is not limited to, ceramic or metallic material.

[0088] As used herein, in accordance with some embodiments, the term “simulating water filtration” refers to an operation of the water filtration system or part of the system in the presence of the fouling sensor, to allow a prediction of fouling in the NF and / or RO membranes, while excluding from the system at least part of the membrane(s). According to some embodiments, simulating filtration enables the prediction of fouling of the membrane(s) and / or the success of the filtration system, while protecting at least part of the membranes required for the filtration process. According to some embodiments, the simulating system can be of any scale, including the actual scale of the water filtration system or a smaller scale.

[0089] As used herein, in accordance with some embodiments, the term “secondary water” refers to water treated in a second stage of wastewater treatment, following primary treatment. Its primary goal is to significantly reduce the biological content of the sewage, including organic matter, bacteria, and other microorganisms, according to some embodiments. This stage uses biological processes to decompose and remove organic pollutants from the water.

[0090] As used herein, in accordance with some embodiments, the term “tertiary water” or “advanced / tertiary wastewater” refers to water treated in a third stage of wastewater treatment. It involves additional processes to further improve the quality of treated water after primary and secondary treatments, according to some embodiments. The goal of tertiary treatment is to remove remaining contaminants, nutrients, and pollutants that were not adequately addressed in the previous treatment stages. This stage often makes the treated water suitable for various reuse applications, including irrigation, industrial processes, and even potable water supply in some cases.

[0091] Reverse osmosis (RO) and nanofiltration (NF) membranes are essential for water purification, but their performance is often compromised by fouling, which is the accumulation of unwanted materials on the membrane surface. One significant challenge in managing fouling is the lack of sensitivity in current monitoring techniques, making it difficult to detect early stages of fouling before it significantly impacts membrane performance. Additionally, many existing methods do not provide real-time measurements, leading to delays in identifying and addressing fouling issues. This latency can result in prolonged periods of reduced efficiency and higher operational costs due to increased energy consumption and more frequent cleaning or replacement of membranes. Enhancing the sensitivity and real-time monitoring capabilities for fouling detection could vastly improve the maintenance and operational efficiency of RO / NF systems, ensuring more consistent water quality and longer membrane lifespans.

[0092] According to some embodiments, the fouling sensor provided herein enables the realtime monitoring of fouling formation in the highly dense and selective reverse osmosis (RO) and nanofiltration (NF) membranes. The sensor is applicable in a water filtration system during, after, and / or before flowing water into the system. The sensor disclosed herein is sensitive and provides essential information regarding the condition of the membrane and the water at the different steps of the process. The sensor is optical and relies on the sensitive surface plasmon probes and an associated polymer layer that mimics the physico-chemical properties of the active layer of the RO / NF membrane. Fouling formation at the mimicking polymer layer affects the optical properties of the surface plasmon probes. Accordingly, by a direct correlation, the amount of foulant at the RO / NF membrane is indicated.

[0093] According to some embodiments, there are provided herein methods that include monitoring membrane condition, water quality evaluation, and / or water's tendency to foul the membrane, all in real time. According to some embodiments, the sensor is also applicable in a method for monitoring membrane’s fouling removal, during a cleaning process thereof. Advantageously, the methods disclosed herein provide tools to design appropriate RO / NF water filtration systems per aquatic source. In addition, they facilitate the design of appropriate water pretreatment steps and / or membrane cleaning procedures.

[0094] There is provided herein, a fouling sensor for predicting and / or assessing the extent of fouling of nanofiltration (NF) and / or Reverse Osmosis (RO) membranes before and / or during water filtration and / or membrane cleaning, the sensor including: a substrate having noble metal nanoparticles on a surface thereof; and a polymer layer associated with the noble metal nanoparticles, wherein the polymer layer is characterized by similar physico-chemical properties as an active layer of the NF and / or RO membranes, and thereby the polymer layer is configured to mimic the fouling of the membrane’s active layer before and / or during the water filtration and / or membrane cleaning, wherein when light impinges the sensor it is reflected / transmitted in a characteristic A,max, wherein a change in Z,max enables quantifying the adsorbed foulant to the sensor and therefore, is indicative of the extent of membranes’ fouling before and / or during water filtration and / or membrane cleaning. According to some embodiments, the change in Xmax is utilized in the quantification of a mass of a foulant adsorbed on the fouling sensor. According to some embodiments, the adsorbed foulant mass on the sensor is correlated to the adsorbed foul ant mass on the RO and / or NF membranes. According to some embodiments, the adsorbed foulant mass detected by the sensor is accurate within an error of less than about 20% from the adsorbed foulant mass on the RO and / or NF membranes, for example, within an error of about 18-20%, about 15-18%, about 12-15%, about 9-12%, or about 5-9%. Each possibility is a separate embodiment.

[0095] According to exemplifying embodiments, a calculation of the mass adsorbed on the fouling sensor is as detailed in Example 6 (Equations 4 and 5) and denoted as a calculation of a dry mass or a mass surface concentration.

[0096] According to some embodiments, the change in Xmax is utilized in the quantification of the thickness of a foulant adsorbed on the fouling sensor (i.e. thickness of the fouling layer). According to some embodiments, the adsorbed foulant thickness on the sensor is correlated to the foulant thickness adsorbed on the RO and / or NF membranes.

[0097] According to some embodiments, the polymer layer shares part of the physico-chemical properties of the RO / NF membrane, or more specifically of the RO / NF membrane’s active layer. According to some embodiments, the part of the physico-chemical properties that are shared include, but are not limited to, properties of surface hydrophobicity and / or surface charge.

[0098] In some embodiments, the hydrophobicity of the polymer layer is characterized by a wetting angle of about 50°-80°, for example, about 55°-80°, about 60°-75°, about 65°-75°, or about 68°-75°. Each possibility is a separate embodiment.

[0099] In some embodiments, the surface charge is a negative charge expressed by a zeta potential of about (-30)-(-60) mV under the conditions of 10 mM solution of NaCl and pH 7. For example, the zeta potential is about (-32)-(-58) mV, about (-35)-(-55) mV, about (-37)-(- 53) mV, or about (-40)-(-50) mV, under the conditions of 10 mM solution of NaCl and pH 7. Each possibility is a separate embodiment.

[0100] According to some embodiments, the polymer layer and the RO / NF membrane, or more specifically of the RO / NF membrane’s active layer, have a chemical similarity. The chemical similarity, in accordance with some embodiments, may include, but is not limited to, functional chemical moiety (e.g., amide), polarity, heteroatom (e.g., nitrogen) and / or frequency thereof. Each possibility is a separate embodiment. According to some embodiments, a formation of fouling occurs through different kinds of chemical interaction between the polymer and the foulant, such as, but not limited to, van der Waals, electrostatic, polar, covalent, or H-bond interactions. Each possibility is a separate embodiment. In some embodiments, the chemical similarity between the polymer layer and the membrane induces a similar chemical interaction between the polymer layer or the membrane to a foulant in the water.

[0101] According to some embodiments, the polymer layer and the RO / NF membrane, or more specifically the RO / NF membrane’s active layer, possess a structural similarity. In some embodiments, the morphology of the polymer shares similar motifs with the RO / NF membrane, or more specifically with the RO / NF membrane’s active layer. In some embodiments, the motif may include, but is not limited to, cavity, pore, asymmetry, or thickness. Each possibility is a separate embodiment. In some embodiments, one or more structural motifs may be combined and configured by a certain similar: gradient, density, distribution, hierarchy, or scale. Each possibility is a separate embodiment. In some embodiments, the base of the polymer layer or the membrane’s active layer is dense with nanoscale pores, the middle part of the layer is less dense, and the upper part is relatively more porous. In some embodiments, a similar structural motif between the polymer and the membrane induces a corresponding similarity of a foul ant- surface physical interaction. According to some embodiments, the chemical and / or physical interactions induce a similar extent of fouling on the sensor as on the RO / NF membrane, or more specifically of the RO / NF membrane’s active layer.

[0102] In some other additional embodiments, the polymer layer and the RO / NF membrane, or more specifically the RO / NF membrane’s active layer, are made of similar or the same material.

[0103] According to some embodiments, the polymer is selected from, but is not limited to, polyamide, aromatic polyamide, crossed-linked aromatic polyamide, polyimide, polyurethane, cellulose acetate, polypropylene, polyamine, poly methacryl ate, polyethersulfone (PES), polysulfone (PSU), polyester, polyvinylidene fluoride (PVDF), polyacrylonitrile, polydimethylsiloxane (PDMS), polyacrylonitrile, polypiperazine-amide (PPA), any derivative thereof, any substituted version thereof, and any combination thereof. Each possibility is a separate embodiment. According to some embodiments, the polymer is polyamide. In some embodiments, the polyamide polymer includes, or is, nylon 6,6.

[0104] According to some other embodiments, the polymer is a crosslinked aromatic polyamide. In some embodiments, the crosslinked aromatic polyamide includes, but is not limited to, aromatic diamine. In some embodiments, the aromatic diamine includes, but is not limited to, m-phenylenediamine (MPD), p-Phenylenediamine (PPD), di ami nobenzene (DAB), any derivatives thereof, or any combination thereof.

[0105] In yet some other embodiments, the polymer includes a non-aromatic multi-amine such as, but not limited to, tris(2-aminoethyl)amine (TAEA), ethylenediamine (EDA), cyclohexanediamine (CHDA), any derivatives thereof, or any combination thereof.

[0106] According to some embodiments, the polymer may be further modified with sulfonic, or fluorinated moieties.

[0107] According to some embodiments, water treated by the water filtration membrane is selected from, but is not limited to, seawater, wastewater, sewage water, drinking water, irrigation water, groundwater, pool water, physiological water, any partial water fraction thereof, any water combination thereof, and any pre / post-treated water thereof. Each possibility is a separate embodiment. According to some embodiments, the water treated by the water filtration membrane is wastewater. According to some embodiments, the water treated by the water filtration membrane is seawater. According to some embodiments, the water treated by the water filtration membrane includes a foulant that forms the fouling on the water filtration membrane, and accordingly, a similar fouling on the sensor’s polymer layer.

[0108] According to some embodiments, the foulant may include, but is not limited to, protein, organic molecule, lipophilic molecule, polysaccharide, polymer, charged compound, neutral compound, biomacromolecule, mineral, ions, or any combination thereof.

[0109] According to some embodiments, the water introduced to the water filtration membrane is a membrane-cleaning solution. In some embodiments, the membrane-cleaning solution is passing through the membrane in order to clean and maintain the membrane's proper function. In some embodiments, the cleaning solution may be characterized by a pH below or above 7. In some embodiments, the cleaning solution may be supplemented with a detergent. In some embodiments, the cleaning solution may be supplemented with enzymes. In some embodiments, the cleaning solution may be supplemented with chelating agents. In some embodiment, the cleaning solution may be supplemented with oxidizing agents.

[0110] According to some embodiments, the water to be treated in the water filtration system is pre-treated prior to entering the water filtration system (i.e., prior to reaching the RO and / or NF). The pre-treatment is essential in order to protect the RO and / or NF membranes and ensure the system operates efficiently and effectively. The type of pre-treatment required depends on the quality of the water. According to some embodiments, the pre-treatment includes, but is not limited to, sedimentation, coagulation, flocculation, sand filtration, activated carbon filtration, multimedia filtration, microfiltration (MF), ultrafiltration (UF), softening, chemical pre-treatment such as antiscalants, pH adjustment, chlorination / dichlorination, oxidation, cartridge filtration, or biocide treatment. Each possibility is a separate embodiment. In some embodiments, the water to be treated by said water filtration NF and / or RO membranes is tertiary water.

[0111] According to some embodiments, the noble metal nanoparticles are in a form selected from, but are not limited to, nano-discs, nano-rods, nano-spheres, nano-plates, nano-dots, nanoislands, and any combination thereof. Each possibility is a separate embodiment. According to some embodiments, the noble metal nanoparticles are preferably in the form of nano-discs.

[0112] According to some embodiments, the noble metal nanoparticles include a metal selected from the group consisting of gold, silver, and platinum. Each possibility is a separate embodiment. According to some embodiments, the noble metal nanoparticles include gold.

[0113] According to some embodiments, the noble metal nanoparticles have a diameter of about 12-150 nm. In some embodiments, the noble metal nanoparticles have a diameter of about 110-140 nm, for example, about 110-135 nm, about 110-130 nm, or about 115-125 nm. In some embodiments, the noble metal nanoparticles are gold nano-discs having a diameter of about 115-125 nm. Each possibility is a separate embodiment. According to some embodiments, the noble metal nanoparticles are nano-discs with a thickness of about 5-50 nm, for example, about 7-35 nm, about 10-30 nm, about 10-25 nm, or about 15-25nm. Each possibility is a separate embodiment. In some embodiments, the noble metal nanoparticles are gold nano-discs having a thickness of about 20 nm.

[0114] A collective oscillation of conduction electrons in the noble metal nanoparticles refers to the term “localized surface plasmons” (“LSP”). These plasmons are confined to a small volume, typically smaller than the wavelength of light. “Localized surface plasmons resonance” (“LSPR”) refers to when the electrons in the metal nanoparticles resonate with the electric field of an incident light, leading to unique optical properties. Metal nanoparticles (e.g., gold, silver) exhibit LSPR when the frequency of incident light matches the natural frequency of collective oscillations of their conduction electrons (plasmons). A resonance’s characteristic range of wavelength, or Xmax is influenced by the size, shape, material, and in particularly by the environment of the nanoparticles.

[0115] According to some embodiments, changes in a local dielectric environment, such as the association of foulant molecules to the nanoparticle's surface, can shift the plasmon resonance, allowing for highly sensitive detection of chemical and biological matter. This shift is expressed by a change of the wavelength (X) at the maximum optical absorption / reflection, i.e. Amax -

[0116] According to some embodiments, the substrate includes an inorganic material. According to some embodiments, the substrate includes a ceramic or metallic material. According to some embodiments, the substrate includes a ceramic material. According to some embodiments, the substrate includes a ceramic material including, but not limited to, silica, alumina, titania, zirconia, or any combination thereof. Each possibility is a separate embodiment. According to some embodiment, the substrate is a silica substrate.

[0117] According to some embodiments, the substrate has a thickness between about 50 nm to 5 pm, for example, about 50 nm - 1 pm, about 50-500 nm, about 50-200 nm, or about 80-120 nm. Each possibility is a separate embodiment. According to some embodiments, the substrate has a thickness of about 80-120 nm.

[0118] According to some embodiments, the sensor includes a coupling agent for associating the substrate with the polymer layer. According to some embodiment, the coupling layer is bound to the substrate. According to some embodiment, the coupling layer facilitates the association of the polymer layer to the substrate. In some embodiments, the facilitation is enabled via chemical interactions between the polymer and the substrate. In some embodiments, the interactions may include, but are not limited to, hydrophobic, H-bonds, or polar interactions. According to some embodiments, the coupling agent is a silane coupling agent. In some embodiments, the silane coupling agent includes, but is not limited to, a functional moiety selected from, but is not limited to, amine, amide, pyridine, alcohol, carbonyl, alkyl, nitrile, ester, or any combination thereof. Each possibility is a separate embodiment. According to some embodiments, the silane coupling agent includes a silicon element. In some embodiments, the silicon element is covalently bound to moieties selected from, but not limited to, -Cl, -Br, -I, -OCH3, -OCH2CH3, and / or directly to a substrate’s moiety of -O-X- that is included on the surface of the substrate, wherein X is selected from Zr, Si, or Al. Each possibility is a separate embodiment. According to some embodiments, X is Si. According to some embodiments, the silane coupling agent includes the amine functional moiety. In some embodiments, the silane coupling agent is an amino silane. In some embodiments, the silane coupling agent is aminopropyltriethoxysilane (APTES).

[0119] According to some embodiments, there is provided a use of the fouling sensor disclosed herein, for assessing and monitoring fouling of the NF and / or RO membranes before and / or during the water filtration process.

[0120] In some embodiments, the fouling sensor is used to predict fouling in the NF and / or RO membranes prior to the formation of a certain extent of fouling. In some embodiments, the fouling sensor is used as a tool to prevent fouling and / or dysfunction of the NF and / or RO membranes.

[0121] According to some embodiments, the fouling sensor is used to dictate a membrane’s maintenance program. In some embodiments, the maintenance includes cleaning the membrane.

[0122] According to some embodiments, the fouling sensor is used to monitor the fouling and / or fouling tendency in real-time.

[0123] According to some additional embodiments, the fouling sensor is used to assess and / or predict the fouling before, during and / or after the water filtration process. In some embodiments, the sensor is used prior to introducing a water flow to the water filtration system. In some exemplifying embodiments, the sensor is configured to be positioned at the entrance of the water filtration system in order to dictate what is the purity level of the water prior to entering the water filtration system. In some embodiments, the use of the sensor prior to entering the water is for the prevention of fouling of the membrane. In some embodiments, the use of the sensor prior to entering the water is for an evaluation of water pre-treatment steps. A reference is now made to FIG. la which exemplifies a workflow diagram 050 using the fouling sensor, according to some embodiments. In the example, the sensor is used specifically as a tool for deciding regarding the required water pre-treatment prior to introducing a water flow to an RO water filtration system, according to some embodiments. From left to right, a flow of water is introduced to a sensor (item 051) for a first sensing (item 052). If the results from the first sensing predict that there will be no fouling upon contacting an RO membrane (item 053), then the water flows forward into the RO water filtration system (item 054). If the results from the first sensing predict that there will be fouling (item 055), then the water is directed to go through pretreatment steps (item 056). After the pretreatment steps, a subsequent sensing is performed to dictate whether the water will foul the RO membrane (item 057). If yes (item 058), then the water will go through additional pretreatment steps (item 056), including additional subsequent sensing (item 057), iteratively, until results predict no fouling (item 059). If subsequent sensing predicts that there will be no fouling (item 059), then the water will be directed to the RO water filtration system to start the RO process (item 054). Additional sensing (not mentioned in the figure) may be included in the RO water filtration system itself.

[0124] Yet according to some other embodiments, the sensor disclosed herein is used for monitoring fouling of a surface that is continuously exposed to water. According to some embodiments, the sensor is used for assessing and / or predicting the fouling of the surface. In some embodiments, the use of the sensor for surfaces is performed by exposing the sensor to an environment or a simulated environment of said surface. In some embodiments, the disclosed sensor is used for monitoring fouling of underwater surfaces, more particular marine underwater surfaces such as the bottom of marine vessels exposed to seawater. In some embodiments, the disclosed sensor is used for monitoring the fouling of surfaces involved in the production of foodstuffs, including beverages, food, and feed, wherein the deposition of biological compounds such as proteins and polysaccharides is of particular concern. In some embodiments, the disclosed sensor is used for monitoring fouling of fluid container surfaces, such as reactors, tanks, or piping / tubing, in particular those involved in cooling / heating or heat exchange, for instance in the oil and gas industry, e.g. for the production of fuel such as coke. In some embodiments, the disclosed sensor is used for monitoring the fouling of surfaces involved in chemical reactions such as polymerization reactions and catalytically active surfaces. According to some embodiments, there is provided a use of the fouling sensor disclosed herein, for assessing a removal of foulant from the NF and / or RO membranes during cleaning thereof. The sensor is used, according to some embodiments, to assess the extent of cleaning of the NF and / or RO membranes during a cleaning process. In some embodiments, the sensing is performed intermittently or continuously throughout the cleaning process. According to some embodiments, the sensing facilitates decision-making concerning the cleaning process. The cleaning process regenerates the membrane to be ready for an additional RO and / or NF water filtration process, according to some embodiments. According to some embodiments, the sensor enables optimizing the cleaning time and conditions. Thus, the fouling sensor may prevent excessive or insufficient cleaning process, that can harm the membrane or the water filtration process, respectively, according to some embodiments.

[0125] According to some embodiments, the fouling sensor is suitable to detect and signal in a response to adsorbed foulant at a surface concentration between about 1 ng / cm2to 10 pg / cm2, for example, between about 1-10 ng / cm2, between about 10-100 ng / cm2, between about 100- 1000 ng / cm2, or between about 1-10 pg / cm2. Each possibility is a separate embodiment.

[0126] According to some embodiments, the fouling sensor can be operated at a pH condition of about 2-12.

[0127] There is provided herein, in accordance with some embodiments, a method of predicting and / or sensing fouling of nanofiltration (NF) and / or Reverse Osmosis (RO) membranes before and / or during a water filtration and / or membrane cleaning, the method including: providing NF and / or RO membranes; providing a fouling sensor for predicting and / or assessing the extent of fouling of the NF and / or RO membranes, wherein the sensor is positioned in NF- and / or RO- based water filtration system, the sensor including noble metal nanoparticles associating with a polymer layer, wherein the polymer layer is characterized by similar physico-chemical properties as an active layer of the NF and / or RO membranes, and thereby the polymer layer is configured to adsorb and / or desorb foulant to a similar extent as the active layer of the NF and / or RO membranes before and / or during water filtration and / or membrane cleaning; 1 introducing a water flow to the NF- and / or RO- based water filtration system such that the water flow contacts the sensor during the water filtration or membrane cleaning; irradiating light on the sensor to induce a reflected / transmitted light with a characteristic range of wavelengths; detecting the reflected / transmitted light; and determining a change in a characteristic Xmax before and / or during the water filtration and / or membrane cleaning, wherein the change in Xmax facilitates quantifying the adsorbed and / or desorbed foulant to the sensor and therefore, is indicative of the extent of membrane’s fouling before and / or during water filtration and / or membrane cleaning.

[0128] Reference is now made to FIG. lb which schematically illustrates a flowchart of a method for predicting / sensing fouling of nanofiltration (NF) and / or Reverse Osmosis (RO) membranes before and / or during a water filtration. As shown in FIG. lb, the sensing method 100 includes step 110 providing NF and / or RO membranes. The NF and / or RO membranes can be a single membrane of NF or RO, multiple NF membranes, multiple RO membranes, or any combination of a number and type of NF / RO membranes, according to some embodiments. According to some embodiments, the membranes may be of any type of membranes that correspond to the terms of RO or NF. In step 120, a fouling sensor as disclosed herein, according to some embodiments, is provided. In some embodiments, the provided sensor in the system can be more than one sensor. The provided sensor and NF and / or RO membranes are positioned in an array that allows monitoring of the extent of the fouling of the membranes during the water filtration, according to some embodiments. In step 130, water is introduced to the (RO / NF) water filtration system. According to some embodiments, the water may be first introduced to a sensor prior to entering the water filtration system. This first sensing enables to dictate whether the water is suitable to enter the NF / RO-based water filtration system. According to some embodiments, the provided sensor is positioned in different location(s) in the water filtration system therein, with respect to the NF and / or RO membranes. In some further embodiments, a sensor is positioned at an exit from the water filtration system. This last sensing can facilitate dictating on the quality of treated water at the end of the process. In step 140, the sensor is irradiated with light. The light can be of any source, according to some embodiments, with the condition that it must cover the UV-vis spectrum range that matches the resonance frequency of the localized surface plasmon of the noble metal nanoparticles. According to some embodiments, the light is in a spectrum range of, but not limited to, 400- 700 nm. In step 150, a reflected / transmitted light from the sensor is detected. According to some embodiments, the detection may be performed intermittently or continuously during the water filtration process. Both the irradiation and detection may be performed, in accordance with some embodiments, before / during / after the water filtration process. According to some embodiments, the sensor may be fixated or be taken out from the system in order to irradiate it and detect the reflected / transmitted light therefrom. In step 160, a change in a characteristic kmax is determined, i.e. AZ. According to some embodiments, the change facilitates the quantification of the foulant of the membrane. The change in the kmax is determined compared to the characteristic kmax value determined prior to introducing a water flow to the sensor, in accordance with some embodiments. The change in the characteristic kmax value, therefore, according to some embodiments, may be determined at the entrance to the water filtration system, i.e. before the water filtration. The change in the characteristic kmax value, therefore, according to some embodiments, may be determined during the water filtration process. According to some embodiments, the change in the characteristic kmax enables the qualitative and / or quantitative evaluation of the extent of the fouling. According to some embodiments, the qualitative evaluation of the fouling may be presented to a user as, but not limited to, a change in color, a value on a relative scale, or as a binary scale, such as but not limited to, pass / fail, yes / no, or true / false. Each possibility is a separate embodiment. In an optional step 170, the fouling in the NF and / or RO membranes is quantified utilizing the determined change in the characteristic kmax, according to some embodiments. The quantification, according to some embodiments, includes, but is not limited to, the quantitative evaluation of a mass surface concentration, i.e. how much foulant resides or is deposited on the membrane per surface area. According to some additional embodiments, the quantification may evaluate the thickness of the foulant.

[0129] As used herein, in accordance with some embodiments, the term “contacting” refers to the act of contacting, and yet includes the acts of “flowing through”, or “introducing”, the water flow to the NF and / or RO membranes and / or the fouling sensor by any means that results in a formation of fouling in the NF and / or RO membranes and / or the fouling sensor.

[0130] According to some embodiments, the sensor is configured to be positioned beside, upstream, downstream, and / or within the membrane. Each possibility is a separate embodiment. In a scenario where the sensor is being positioned beside the NF and / or RO membranes, according to some embodiments, the water flow is contacting the sensor and the membrane in parallel. Hence, parameters of the water flow that the sensor and the NF and / or RO membranes experience are in common for both, in real-time. According to some embodiments, the water flow contacts the sensor and the NF and / or RO membranes, simultaneously. According to some embodiments, the common parameters in this scenario may include, but are not limited to, the pressure of the flow, foulant type, foulant concentration, temperature of the flow, or water contact duration. This parallel scenario, according to some embodiments, allows a real-time assessment and / or prediction of the fouling of the NF and / or RO membranes. In some embodiments, the real-time assessment allows the real-time monitoring of membranes’ quality / functionality. In some additional embodiments, the real-time monitoring enables a realtime monitoring of the water filtration process and the quality of water resulting from the water filtration process, accordingly.

[0131] In a scenario where the sensor is being positioned downstream with respect to the NF and / or RO membranes, according to some embodiments, the water flow is contacting the sensor after flowing through and / or parallel to the membrane. In some embodiments, this scenario implies that the sensor detects the residual potential fouling at a permeate and / or retentate stream, i.e. a water flow that had been treated and / or concentrated by the NF and / or RO membranes. A potential foulant may be the source of fouling in proceeding membrane-based steps in the water filtration system, thereby the sensor serves as a predictor for the next step, in accordance with some embodiments. In further embodiments, the sensor enables to indicate whether the treated water is sufficiently purified, post the water filtration process or post one of the steps of the water filtration process.

[0132] In a scenario where the sensor is being positioned upstream with respect to the NF and / or RO membranes, according to some embodiments, the water flow is contacting the sensor before flowing through the membrane. In some embodiments, this scenario implies that the sensor detects foulant at the water flow before being fed into the membrane, i.e. a water flow that hadn’t been treated by the NF and / or RO membranes yet. Therefore, the sensor enables to mimic and assess / predict the membrane’s extent of fouling, according to some embodiments.

[0133] In a scenario where the sensor is positioned within the NF and / or RO membranes itself, according to some embodiments, the water flow contacts the sensor as in the parallel scenario. Nevertheless, according to some embodiments, in this scenario, there is no physical void between the sensor and the membrane, as the sensor is situated in the membrane body and / or overall membrane-containing setup. In some embodiments, the sensor may be positioned at a center or at a corner of the membrane. In some embodiments, the membrane contains the sensor. In some embodiments, the membrane contains more than one sensor. The more than one sensor, in accordance with some embodiments, may be positioned at a center and / or at different locations and / or comers of the membrane.

[0134] According to some embodiments, there is a direct correlation between a level of permeate flux coming out of the membrane and the extent of the fouling of the membrane.

[0135] According to some embodiments, there is a direct correlation between the extent of the fouling of the membrane and the extent of fouling detected by the sensor.

[0136] According to some embodiments, there is a direct correlation between a level of permeate flux coming out of the membrane and the extent of fouling detected by the sensor.

[0137] According to some embodiments, there is a correlation between fouling indicators of permeate flux and hydraulic resistance, to the indicated adsorbed mass by the herein-provided fouling sensor.

[0138] There is provided herein a method of simulating and assessing fouling of NF and / or RO membranes before and / or during a simulation of water filtration and / or membrane cleaning, the method including: providing a fouling sensor configured to be positioned instead of NF and / or RO membranes to simulate and assess an extent of fouling in the membranes, wherein the sensor including noble metal nanoparticles associating with a polymer layer, wherein the polymer layer is characterized by similar physico-chemical properties as an active layer of the membranes, and thereby the polymer layer is configured to adsorb foulant to a similar extent as the active layer of the membranes before and / or during water filtration and / or membrane cleaning; flowing water such that the water flow contacts the sensor before and / or during the simulation of the water filtration and / or membrane cleaning; irradiating light on the sensor to induce a reflected and / or transmitted light with a characteristic range of wavelengths; detecting the reflected and / or transmitted light; and determining a change in a characteristic Xmax before and / or during the simulation of the water filtration and / or membrane cleaning, wherein the change in Xmax enables quantifying the adsorbed foulant to the sensor and therefore, is indicative of the extent of a simulated membrane’s fouling before and / or during water filtration and / or membrane cleaning.

[0139] According to some embodiments, the simulation system includes components and / or parameters that are similar to the parameters of the system for water filtration. According to some embodiments, the components and / or parameters may include, but are not limited to, membrane size, membrane type, number of membranes, flow rate, temperature, pressure, duration of flow, system’s size, non-RO / NF membrane(s), source of water, pre-treatment steps, or content of water.

[0140] According to some embodiments, the fouling sensor in the simulating system is configured to be positioned instead of the NF and / or RO membranes, such that the position is at one or more locations with respect to the simulated NF and / or RO membranes at the water filtration system. In some embodiments, the one or more locations is at the designated position of the simulated NF and / or RO membranes itself. In some embodiments, the one or more locations is in a vicinity to the designated position of the simulated NF and / or RO membranes. In some embodiments, the one or more locations is beside the designated position of the simulated NF and / or RO membranes. In some embodiments, the one or more locations is upstream with respect to the designated position of the simulated NF and / or RO membranes. In some embodiments, the one or more locations is downstream with respect to the designated position of the NF and / or RO membranes.

[0141] According to some embodiments, the method of simulating fouling is performed simultaneously with the water filtration method. According to some other embodiments, the method of simulating fouling is performed prior to operating the water filtration system. In some embodiments, a part of the water filtration system is simulated. In some embodiments, the simulation method serves as a prediction of fouling. In some embodiments, the simulation method facilitates the optimization of parameters and / or components in the water filtration system.

[0142] According to some embodiments, the extent of the fouling is assessed continuously, during the water filtration. According to some embodiments, the extent of the fouling is assessed in one or more selected time points. In some embodiments, the one or more selected time points includes, but is not limited, to the beginning of the water filtration process, prior to the beginning of the water filtration process, during the water filtration process, or after the water filtration process. Each possibility is a separate embodiment.

[0143] There is provided herein, a method of producing a fouling sensor for RO and / or NF membranes-based system, the method including: providing a substrate associated with noble metal nanoparticles; and applying a polymer layer atop the noble metal nanoparticles, thereby producing the fouling sensor.

[0144] A reference is made to FIG. 2 which schematically illustrates a flowchart of a method of producing the fouling sensor for RO and / or NF membranes-based system. As shown in FIG. 2, the production method 200 includes in step 210 providing a substrate (item 211) associated with a layer of noble metal nanoparticles (item 212). In some exemplary embodiments, the substrate is a base layer of silica. In some embodiments, the substrate is characterized by a thickness of between about 50 nm - 5 pm. According to some exemplary embodiments, the thickness of the silica substrate is about 70-200 nm. According to some embodiments, the noble metal nanoparticles are spaced with distances of about 10-1000 nm, for example, about 10-100 nm, about 100-300 nm, about 300-500 nm, about 500-700 nm, or about 700-1000 nm. Each possibility is a separate embodiment. In some exemplary embodiments, the noble metal nanoparticles are gold nano-discs. The noble metal nanoparticles may be deposited on the substrate via a chemical and / or physical assembly of pre-made noble metal nanoparticles. In some embodiments, the chemical deposition may include, but is not limited to, a surface premodification of the substrate with a functional chemical moiety followed by an association of the pre-made noble nanoparticles with the chemical functional moiety. According to some embodiments, the diameter size range of the noble metal nanoparticles is of about 70-150 nm, for example, about 90-135 nm, or about 110-130 nm. According to some embodiments, the noble metal nanoparticles may be deposited via a method of atom layer deposition (ALD), or alike, to form islands / discs of noble metal deposited on the substrate. In optional step 220, a coupling layer (item 221) is applied on the substrate to facilitate the subsequent application of the polymer layer. The coupling layer may be a silane coupling layer, such as, but not limited to, amino silane coupling layer. The amine chemical moiety mediates a subsequent chemical attachment of the mimicking polymer layer via common chemical interactions and / or chemical identity, according to some embodiments. An example of such interaction can include, but is not limited to, H-bonds, polar interactions, or van der Wais interactions. According to some embodiments, the coupling layer is deposited between the noble metal nanoparticles. In step 230, a polymer layer (item 231) is applied atop the noble metal nanoparticles. According to some embodiments, the polymer layer is applied to deposit the polymer in between the noble metal nanoparticles, on top of the surface of the noble metal nanoparticles, on the side surface of the noble metal nanoparticles, and any combination thereof. Each possibility is a separate embodiment. The deposition in the vicinity of the noble metal nanoparticles surfaces enables the sensitivity of the surface plasmon thereof to any change in a dielectric medium in its vicinity. According to exemplifying embodiments, the change in the dielectric medium is a result of an adsorption or desorption of a foulant. This change is correlated to the change in plasmons’ Xmax.

[0145] According to some embodiments, the method of producing the fouling sensor further including cleaning the substrate before applying the polymer layer. According to some embodiments, the cleaning includes a treatment selected from, but is not limited to, UV / ozone, plasma, sonication, solvent dip-washing, solvent spray-washing, acidic solution treatment, alkaline solution treatment, drying, or any combination thereof. Each possibility is a separate embodiment.

[0146] According to some embodiments, the method of producing the fouling sensor further includes applying a coupling layer on the substrate, to facilitate the application of the polymer layer. In some embodiments, the application of the coupling layer is performed via a technique selected from, but is not limited to, spin coating, drop casting, dip-coating, spraying, vapor deposition, and any combination thereof. Each possibility is a separate embodiment.

[0147] According to some embodiments, the application of the polymer layer is performed via a technique selected from, but is not limited to, interfacial polymerization, spin coating, drop casting, spraying, vapor deposition, or any combination thereof. Each possibility is a separate embodiment. According to some embodiments, the application of the polymer layer is via a technique of spin coating. In some embodiments, spin coating is utilized to apply Nylon 6,6 on the substrate. According to some embodiments, the application of the polymer layer is via a technique of interfacial polymerization. In some embodiments, interfacial polymerization is utilized to apply a crossed-linked aromatic polyamide. There is provided herein, in accordance with some embodiments, a system of NF- and / or RO-based water filtration, the system including:

[0148] NF and / or RO membranes; a fouling sensor for assessing the extent of fouling of the NF and / or RO membranes or membrane sets, wherein the sensor including a substrate having noble metal nanoparticles on a surface thereof, wherein the noble metal nanoparticles are associated with a polymer layer, wherein the polymer layer is characterized by similar physico-chemical properties as an active layer of the NF and / or RO membranes, and thereby the polymer layer is configured to adsorb / desorb foulant to a similar extent as the active layer of the NF and / or RO membranes during water filtration and / or membrane cleaning; a water flow conduit system configured to direct water flow to contact the sensor and the NF and / or RO membranes before and / or during the water filtration and / or membrane cleaning; a light source configured to irradiate light on the sensor; an optical detector configured to detect light reflected and / or transmitted from / through the sensor; and a processing circuitry configured to: determine a characteristic Xmax of the reflected and / or transmitted light; determine a change in Xmaxdetected before and / or during the water filtration and / or membrane cleaning; and calculate an extent of fouling of the sensor based on the change in Xmax, and accordingly assess the extent of fouling of the membrane’s active layer.

[0149] There is provider herein, a method of assessing and cleaning the RO / NF membrane, the method including: providing NF / RO membrane; providing a fouling sensor for assessing the extent of fouling of the NF and / or RO membranes, wherein the sensor is positioned in NF- and / or RO- based water filtration systems, the sensor including noble metal nanoparticles associating with a polymer layer, wherein the polymer layer is characterized by similar physico-chemical properties as an active layer of the NF and / or RO membranes, and thereby the polymer layer is configured to adsorb / desorb foulant to a similar extent as the active layer of the NF and / or RO membranes before / during membrane cleaning; introducing a water flow including a membrane cleaning solution to the RO / NF system such that the water flow contacts the sensor; irradiating light on the sensor to induce a reflected and / or transmitted light with a characteristic range of wavelengths; detecting the reflected and / or transmitted light; and determining a change in a characteristic Xmax before and / or during the membrane cleaning, wherein the change in Xmaxenables quantifying the adsorbed and / or desorbed foulant to the sensor and therefore, is indicative of the extent of membrane’s fouling before and / or during membrane cleaning.

[0150] According to some embodiments, the indicative Xmaxenables quantifying the extent of the desorbed foulant. In some embodiments, a level of membrane cleaning or regeneration is determined upon sensing the extent of the fouling with the method. Subsequently, a decision on further steps is made. The decisions are selected from continuing cleaning, stopping cleaning, changing the type of cleaning, and / or future maintenance frequency between operation periods RO and / or NF membranes.

[0151] EXAMPLES

[0152] Example 1 - Preparation of the fouling sensor

[0153] NPS Nano-X2 uncoated sensor composed of a NPS sensing structure (Au disk shape nanoparticles) on SiCh spacer was silanized with 3-aminopropyl triethoxysilane (APTES) and spin-coated with polyamide (Nylon 6-6) layer on top to mimic the polyamide layer.

[0154] Surface cleaning: Polyamide (Nylon 6-6) coating was conducted as follows: prior to coating, the residual organic matter was removed from the sensors' surface by 10 min sonication with 2-Propanol following 10 min of sonication with DDW, drying with 99.99% N2, and irradiation for 10 min in a UV / ozone chamber (BioFORCE Nanoscience, Ames, IA, USA). The sessile water drop contact angle (i.e., wetting angle) was measured (DataPhysics Instruments, Filderstadt, Germany) to determine surface hydrophobicity throughout the procedure.

[0155] Silanization: The sensor was silanized with APTES as follows: 40 pL of 1% solution of APTES in HPLC-grade absolute ethanol was uniformly distributed on the sensor’s surface in the hood for 4 h at room temperature. After a reaction was finished, the sensor was immersed in clean HPLC-grade absolute ethanol for 12 h at room temperature followed by a contact angle measurement, ensuring hydrophobicity was elevated to the expected value of approximately 56°.

[0156] Polymer coating: After additional wash with HPLC-grade absolute ethanol, and a drying step with 99.99% N2, 80 pL of 0.5% Polyamide (Nylon 6-6) solution in 99% Formic acid filtered through a 0.22-pm syringe filter (Millipore, PVDF) was spin-coated on the sensor surface at 2400 revolutions / second for 60 s with 15 s acceleration time (W S-400-6NPP, Laurell Technologies Corporation, North Wales, PA, USA). The sessile water drop contact angle on the surface (DataPhysics Instruments, Filderstadt, Germany) was then measured again, ensuring hydrophobicity was elevated to the expected values of approximately 73°. Example 2 - Wastewater effluent preparation

[0157] Tertiary wastewater was collected from the Yeruham WWTP, which employs conventional activated sludge treatment followed by direct coagulation, sand filtration, and chlorination. Processed wastewater was concentrated by a factor of 20 using a laboratory-scale RO system equipped with a spiral -wound Hydranautics 2540 ESPA1 membrane (Nitto Group) and kept in the dark at 4°C until use.

[0158] Example 3 - Wastewater EfOM fractionation

[0159] EfOM comprises the main group of substances responsible for the organic fouling of RO membranes during tertiary wastewater desalination.

[0160] Fractionation of EfOM from tertiary wastewater employed DAX-8 polymethylmethacrylate adsorbent resin (40-60 mesh; Superlite®, Sigma-Aldrich, USA) for hydrophobic fractions and XAD-4 non-ionic macroreticular polyaromatic resin (20-60 mesh; Amberlite®, Sigma-Aldrich) for transphilic fractions.

[0161] Five fractions were collected using a modification of Leenheer’s protocol based on: hydrophobic acid (HPOA), hydrophobic neutral (HPON), transphilic acid (TPIA), transphilic neutral (TPIN), and hydrophilic base (HPIB) eluents.

[0162] The resins were thoroughly cleaned before use by washing with 0.1 M NaOH for 24 h, followed by washing in a Soxhlet apparatus with methanol, acetonitrile, and methanol for 24 h each. The clean resins were placed in glass columns with glass frits and valves to control the flow rate and washed exhaustively with double-distilled water (DDW), 0.1 M NaOH, and 0.1 M HC1 until the total organic carbon (TOC) content of the effluent (measured by a TOC analyzer, Jana Analytic, Germany) was <0.5 mg L-1.

[0163] The EfOM solution was filtered using a 0.45 pm membrane filter and the pH adjusted to pH 2 using concentrated HC1. Samples loaded on columns comprised 1 L effluent with a TOC content of 30 mg L-1. EfOM solution was passed through the DAX-8 and XAD-4 columns in that order, with the hydrophobic fraction adsorbed on the former and the transphilic fraction on the latter. The hydrophilic fraction passed through both columns. The hydrophobic and transphilic acid fractions were eluted with 0.1 M NaOH. Neutral hydrophobic and transphilic fractions were diluted by 25% with DDW, and the acetonitrile was removed by rotary evaporation (Buchi Rotavapor R-210). The HPOA, TPIA, and HPIB fractions had high ion contents from the fractionation process and were desalted before further treatment. Samples were frozen in liquid nitrogen and lyophilized in the freeze dryer to remove 90% of the liquid volume before dialysis using 500-1000 Dalton dialysis membranes (Biotech CE Tubing, Spectra / Por®, USA). The concentrated fractions were dissolved in a background solution mimicking the effluent inorganic content, and the solution was adjusted to 5 TOC L-1by dilution with this solution.

[0164] Experiments were conducted under similar aquatic and carbon-equivalent conditions for all fractions including the original EfOM.

[0165] EfOM fractionation was undertaken five times using different samples of tertiary effluent from the City of Yeruham in the Negev highlands of Israel. The TOC contents of the five fractions (HPOA, HPON, TPIA, TP IN, and HPIB), relative to the TOC content of EfOM, are shown in FIG 3. HPIB included 31% of EfOM TOC (9.5 mg), 27% HPOA (8.2 mg), 19% TPIA (5.8 mg), 8% TPIN (2.4 mg), and 4.5% HPON (1.4 mg); non-recovered material contained 9.9% (2.7 mg).

[0166] Example 4 - Reverse Osmosis (RO) filtration experiments on EfOM fractions

[0167] EfOM fractions from tertiary effluents were separated with respect to hydrophobicity and acid-base properties to delineate their effects on RO membrane fouling, measured as the decrease in permeate flux resulting from the adhesion of fraction aggregates to the membrane. Membrane fouling by EfOM is a complex process affected by (i) RO system hydrodynamics including convective transport of foulant to membrane, shear stress, and concentration polarization; (ii) fraction aggregate size; (iii) interactions of fractions with the membrane surface; and (iv) the hydraulic resistance of each adhered-fraction layer.

[0168] The degrees of membrane fouling caused by each EfOM fraction and the EfOM mix were compared in RO crossflow filtration experiments using a laboratory-scale RO flow cell (FIG. 4) under constant pressure (11 bar) and crossflow velocity (0.87 m s ') at 25°C. Degrees of fouling were estimated from the reduction in permeate flux.

[0169] The scheme 300 in FIG. 4 schematically describes the experimental crossflow filtration system. An effluent-containing feed (item 301) was pumped into an RO cell equipped with XLE membrane (item 302). More specifically, the flow of the feed (item 301) pumped via a gear pump (item 303) and was controlled by a flow meter (item 304) and pressure meter (item 305). Upon contacting the membrane, the feed (item 301) was split into permeate (item 306) and retentate (item 307), wherein the permeate flow rate (item 306) was measured using a scale (item 308) and recorded in a computer (item 309) and the retentate (item 307) was directed into a cold trap (item 310). The retentate was flow-integrated in the cold trap with a diluted salt solution (item 311) in order to mimic the permeate (item 306) and to keep the water level constant during a cyclic filtration of the feed, wherein the introduction of the diluted salt solution was performed via a peristatic pump (item 312). The resulting integrated flow was then pushed via a gear pump (item 303) into the RO cell to keep the cyclic filtration via the RO cell (item 302).

[0170] A low-pressure RO membrane was used (XLE, Dupont, Filmtec, USA) with an effective surface area of 2.5 cm2. The fouling experiment was undertaken after stabilizing the XLE membrane using DDW, followed by desalination and stabilization using a background solution. When a permeate flux baseline was established, the background solution containing a dissolved EfOM fraction was filtered for 4 h. The five EfOM fractions and EfOM mix were adjusted to the same final TOC content (5 mg-L-1) before the experiment. A 1 :10 diluted background solution (based on -90% total salt rejection) was added to the feed tank during the experiments at a rate similar to the permeate flux to maintain similar ionic and EfOM concentrations in the feed. The RO fouling experiment approximates the conditions at the entrance to a commercial RO desalination process.

[0171] The effect of each fraction on a permeate flux during crossflow filtration (after setting membrane permeability with DDW and stabilizing the flux with background solution) is shown in FIG. 5. The RO crossflow experiments indicated that the two main fractions that reduced the permeate flux are TPIN and HPON, both of which caused flux reductions of -17%, whereas the other fractions and the original EfOM mix reduced the flux by 8%-l 1% (FIG. 5). It seems that the reduced polarity of the foulant, rather than hydrophobicity, plays the main role in the fouling of RO membranes under realistic crossflow filtration conditions. The greater flux reduction by HPON and TPIN could be explained by their adsorption on the surface or by their hydraulic resistance, or both.

[0172] Example 5 - Intrinsic hydraulic resistance of the EfOM fractions

[0173] The intrinsic hydraulic resistance of each EfOM fraction and the EfOM mix was determined in triplicate under dead-end filtration conditions with an ESPA1 membrane, using a pressure controller connected to a pressurized nitrogen system, a feedwater reservoir (250 mL), and a filtration cell with a membrane effective surface area of 2.5 x 10-4m2. The permeability of the membrane was determined at three different constant pressures in the range of 7.5-9.1 x 105Pa following a setting-up step with DDW at constant water flux, as follows: where Lp (m3nr2s-1Pa-1) is membrane permeability, V (m3) is the collected volume of water permeate, A (m2) is the membrane active area, t (s) is time, and AP (Pa) is applied pressure. After determining the permeability of the clean membrane with DDW (Lpdean), 15 mL of each EfOM fraction and the EfOM mix (TOC = 5 mg-L"1in a 0.01 mM LaCh solution) were filtered by the membrane to provide full adherence of OM. Following this adherence step, the fouled membrane permeability (Lpfouied) was determined with DDW at three different constant pressures in the range of 7.5-9.5 x 105Pa. The hydraulic resistance of each EfOM fraction and the EfOM mix (Rfouiing) was determined as follows:

[0174] 1 pclean ~ .. K (2) m where u is dynamic water viscosity (Pascal s), Rmis the hydraulic resistance of the membrane (m-1), and Rfouiing is the hydraulic resistance of the fouling layer for each fraction (m-1). Student’s t-test was used to assess the statistical significance of Rfouiing (p < 0.05 was taken as being statistically significant).

[0175] Fraction hydraulic resistance measured in the dead-end filtration system (FIG. 6) followed the order HPON > HPOA ~ TPIN > TPIA > EfOM mix > HPIB, which is consistent with the observed effects of HPON and TPIN on RO permeate flux reduction (FIG. 5). A statistically significant difference was observed between the TPIN fraction and the TPIA, HPIB, and mix foulant groups. Similarly, a significant difference was observed between the HPOA fraction and the TPIA, HPIB, and mix foulant groups. Moreover, the TPIA fraction was found to be significantly different from the HPIB and mix foulant groups. No significant differences were found between the other fractions. Although the HPOA layer had a relatively high hydraulic resistance, it did not reduce the permeate flux by more than the other polar fractions or the EfOM mix, likely because of its relatively low adsorption of dry molecular mass. To measure the amount of the “dry” as well as the hydrated molecular mass of these fractions that was adsorbed to the polyamide surface under parallel flow conditions, the fractions’ affinity was tested in both QCM-D and LSPR membrane mimetic sensors.

[0176] Example 6 - Localized surface plasmon resonance (LSPR) analysis of the accumulation of EfOM fractions on the membrane’s sensor

[0177] The accumulated dry masses of the EfOM fractions and EfOM mix on a polyamide surface were determined by nano plasmonic sensing (NPS) using a modified Nano-X2 device (Insplorion AB, Goteborg, Sweden). The Nano-X2 SiO2-base uncoated sensors (Insplorion AB, Goteborg, Sweden) covered by gold nanodisc plasmons (NPS sensing structures) were silanized with 3 -aminopropyl tri ethoxy silane (APTES) and spin coated with polyamide (Nylon 6-6) to mimic a polyamide layer, as described in Example 1.

[0178] The Nano-X2 flow system was operated initially with DDW at 50 pL min-1for >4 h to establish a DDW baseline. The system was then fed with background solution (Table 1) for 30 min to establish a background solution baseline before applying the organic fractions to the LSPR sensor. Each EfOM fraction or the EfOM mix (5 mg-L”1TOC) was fed through the system at a flow rate of 50 pl min-1for 90 min for adsorption on the polyamide layer. Table 1 presents the chemical information on the EfOM effluents sourced from Yeruham wastewater treatment plant (WWTP), according to some embodiments. Table 1.

[0179] The dry thickness, ds (nm), of the EfOM was estimated from the change in maximum light extinction as a function of wavelength (i.e., the sensor NPS response, Aljvrs). A refractive index (ns) of 1.37 was assumed for the EfOM layer, similar to an alginate layer, and an index (na) of 1.33 was assumed for the background solution. The sensor sensitivity, So, and decay length parameter, Lz(nm), provided by Insplorion AB were 100 nm- RIU-1and 30 nm, respectively. The layer thickness, ds (nm), was calculated as follows:

[0180] The EfOM dry thickness was assumed to be on the same order of magnitude as the probe depth (30 nm), with the relationship between the mass surface concentration, Ts (g cm-2), and layer thickness, ds, being calculated as follows based on the refractive index increment, dns / dc = 0.185 (cm3g-1), commonly applied to proteins and polysaccharides: To assess the dry adsorbed molecular mass on the polyamide surface, an LSPR membrane-mimetic sensor was fabricated (as described in Example 1), and the affinities of the different fractions for polyamide were examined (FIG. 7). The dry-molecular-mass surface concentration, s, of the adsorbed organic fractions on the polyamide surface was indicated by the shift in light-extinction maxima, AX, and the dry mass was calculated using Equations 4 and 5. The neutral fractions (HPON and TPIN) had the highest (and similar) adsorbed dry masses (FIG. 7); HPOA, HPIB, and EfOM mix had lower (and similar) dry masses; and TPIA had the lowest adsorbed mass. The adsorbed dry masses of the different fractions were consistent with their effects on membrane permeate flux, including their separation into two distinctive groups of effect. TPIA, which had the lowest adsorbed mass on the LSPR sensor (FIG. 7), also had the least effect on permeate flux.

[0181] The above results indicate an interplay between the LPSR adsorbed dry molecular mass and intrinsic hydraulic resistance of the different fraction layers. These characteristics explain the effect of the different fractions on RO permeate flux: HPON and TPIN (containing 12.5% of EfOM TOC) provide a combination of high hydraulic resistance (FIG. 6) and high adsorbed mass on the RO membrane-mimetic surface (FIG. 7), causing the greatest permeate flux reduction. The other fractions, including the EfOM mix, had lower adsorbed masses and less effect on RO permeate flux. The high hydraulic resistance of the HPOA fraction (FIG. 6) is unlikely to have reduced the permeate flux due to its lower dry-mass adsorption (FIG. 7).

[0182] It is not surprising that the more-hydrophilic TPIN and less-hydrophilic HPON affect RO fouling similarly, given their similar surface adsorbed dry masses (FIG. 7). HPON and TPIN are the “culprit” fractions in the EfOM mix despite their relatively small amounts (-12.5%), whereas the polar fractions (HPOA, TPIA, and HPIB) are the most abundant (totaling -77.7%), with notably lower dry-mass adsorption.

[0183] Polar fractions may screen and block the influence of HPON and TPIN during fouling by the EfOM mix, leading to reduced fouling. The degree of reduction in the flux of EfOM mix permeate was approximately the median of that of other fractions of similar adsorbed dry mass, so synergy can be precluded as a significant effect on the adsorption of EfOM mix. Example 7 - Polyamide-modified QCM (quartz crystal microbalance) sensor

[0184] The degree of adsorption of the model foulants and the dissolved organic matter in secondary wastewater effluents to a polyamide active layer was also determined by coating Gold-titanium-covered piezoelectric sensors (AW sensors, Valencia, Spain) using a Nylon 6- 6. QCM-D Sensor Preparation: Before coating the Gold-titanium-covered piezoelectric sensor (AW sensors, Valencia, Spain) with polyamide, the sensor was washed according to the following protocol: (i) immersing the sensor in a 2% SDS solution for 30 minutes followed by (ii) rinsing with double distilled water (DDW), (iii) drying in a jet stream of nitrogen gas (medical grade), and (iv) exposing the sensors to UV radiation for 10 minutes in a UV ozone cleaner (Pro cleaner plus, Bioforce Nanoscience, USA). The QCM-D sensor was coated with Nylon 6-6 as follows: 80 pL of 0.5% Nylon 6-6 solution in 99% Formic acid filtered through a 0.22-pm syringe filter (Millipore, PVDF) was spin-coated on the sensor surface at 2400 revolutions / second for 60 seconds with 40 seconds acceleration time (WS400-6NPP, Laurell Technologies Corporation, North Wales, PA, USA). QCM-D Fouling experiments: Continuous-flow adsorption experiments were undertaken to determine the increase in the adsorbed foulant on a QCM-D sensor surface (Gold-Titanium, AW Sensors, Valencia, Spain) coated with Nylon 6-6. A four-channel QCM-D device was used (Q-Sense Analyzer, Biolin Scientific, Sweden), and the 3rd, 5th, 7th, 9th, 11th, and 13th overtones were recorded .

[0185] The QCM-D adsorption experiments involved five steps: (i) The system was initially operated with DDW at a flow rate of 100 pL min-1 for >12 h to establish a baseline with a frequency fluctuation, Af, of <0.5 Hz hour-1; (ii) The system was then fed with the background solution for 30 minutes to establish a baseline; (iii) Then, each foulant was fed through the flow cell at a rate of 100 pl min-1 for 180 minutes followed by (iv) 30 minutes of background solution wash, and (v) 30 minutes of DDW wash. During all experiments, the frequency and dissipation-shift signals of the sensors were recorded continuously. The shear modulus, shear viscosity, and hydrated thickness of the adsorbed layer on the QCM-D coated crystal were calculated using Dfind software (Q-Sence, v. 1.2.7.; Biolin Scientific, Sweden) based on the Voigt model. Best-fit values for each parameter were calculated by modeling the frequency and dissipation shifts in each experiment for the different overtones (n = 5, 7, 9, and 11). Example 8 - Model foulants and secondary wastewater effluents

[0186] Three model foulants were examined for their fouling potential and examination of the LSPR as a fouling prediction tool. Very low viscosity Sodium Alginate (Sigma-Aldrich, Rehovot, Israel), Humic acid (Sigma-Aldrich, Rehovot, Israel), and Athletes' protein powder (87 % pea protein, maltodextrin, flavorings, silicone dioxide, sucralose - produced by "Vegan One", Sommer laboratories Ltd, Rosh Ha'ayin, Israel). For every fouling experiment, 100 mg / L of the model foulant was dissolved in three background solutions: 10 mM NaCl at pH 5, 10 mM NaCl at pH 7, and a background solution of 8.5 mM NaCl + 0.5 mM CaCh (providing a total ionic strength of 10 mM). Each solution was filtered in a 0.22-pm syringe filter (Millipore, PVDF) before every experiment. Fouling of secondary wastewater effluent with a DOC concentration of about 10.73±0.203 mg / L was also tested. The effluents were collected from the Yeruham WWTP, which employs conventional activated sludge treatment followed by direct coagulation and sand filtration and were kept in the dark at 4°C until use. For the QCM- D and LSPR experiments, a synthetic background solution similar to the effluent mineral composition for the stages before (baseline) and after fouling measurements was prepared according to the measured ion composition conducted with ICP.

[0187] Example 9 - RO filtration experiments assessing the fouling degree by the model foulants and the secondary wastewater effluent

[0188] The degree of membrane fouling caused by model foulants, and the secondary wastewater effluent were compared in RO crossflow desalination experiments using a laboratory-scale RO flow cell (CF042, Sterlitech), under constant pressure (10 bar) and crossflow velocity of 0.079 m s-1at 25°C. The degree of fouling was estimated from the reduction in permeate flux. A low-pressure high flux RO membrane was used (Hydranautics 2540 ESPA1 membrane, Nitto Group) with an effective surface area of 42.09 cm2. The fouling experiment was undertaken after compacting the membrane with DDW for 2 hours under constant pressure of 12 bar, followed by stabilization using DDW for 1 hour under constant pressure of 10 bar, and stabilization using background solution for 1 hour. When a permeate flux baseline was established, the (i) background solution containing the model foulant or (ii) the secondary effluents went through desalination stage for 2 hours. The model foulants were in a similar concentration of 100 mg / L for all experiments and filtered through 0.22-pm syringe filter (Millipore, PVDF) prior to the desalination stage. A 1 : 10 diluted background solution (based on a measured salt rejection of approximately 90% for this system’s operating conditions) was added to the feed tank during the experiments at a rate similar to the permeate flux to maintain similar aquatic conditions in the feed to the RO unit. The RO fouling experiment approximates the conditions at the entrance to a commercial RO desalination process, as the water recovery ratio is minor.

[0189] The effects of three model foulants (Alginate, Humic acid, and Athletes’ protein powder), and secondary effluents on RO permeate flux decline, tested in a crossflow system (illustrated in FIG. 4), are presented in FIG. 8a-8e. Each foulant solution was prepared at a concentration of 100 mg / L and then filtered through 0.22 pm filter before each fouling experiment. After stabilizing DDW membrane permeability and permeate flux with a background solution, the effect of each model foulant under different aquatic conditions, pH and the presence of calcium cations, on the rate of permeate flux decline is shown in FIG. 8b- 8d. The total flux decline for each foulant is presented in FIG. 8a.

[0190] The RO crossflow fouling experiments indicate a distinct effect of calcium cations for two foulants, Alginate and Humic acid, with a flux decline of 8.8% and 5.4% in the absence of calcium cations and 38.7% and 35.9% in the presence of calcium cations, respectively. The change between pH 7 to pH 5 showed a slight increase in flux decline, although not to the same extent as the effect of calcium cations (9.07% and 10.5% for Alginate and Humic acid, respectively). Moreover, none of the different treatments impacted the flux decline of the Athletes' protein powder, which is composed mainly of 87% of pea protein, food stabilizers, anticaking agents, flavorings, and polysaccharides.

[0191] For Alginate fouling, the significant flux decline may be due to the formation of a crossed-linked alginate gel layer caused by intermolecular bridging among alginate molecules. The change in pH within the range studied showed little effect on flux decline.

[0192] Compared to Alginate, the different flux decline of Humic acid is likely attributed to (de)protonation of various carboxylic functional groups at pH 7 / 5 and consequent enhanced / reduced electrostatic repulsion between humic acid molecules and the membrane surface. Also, for Humic acid fouling, calcium cations increase membrane fouling due to the interaction of calcium cations with humic acid carboxyl moieties, forming a compact fouling layer with elevated hydraulic resistance. Athletes' Protein effect on RO membrane fouling demonstrated no significant difference in permeate flux decline between different aquatic conditions. The mixture of proteins and polysaccharides composing the protein athletes’ powder was expected to provide a synergistic effect and a significant flux decline. Comparing the effect of alginate or humic acid at similar concentrations (FIG. 8b and FIG. 8c), to the effect of the protein athlete powder (FIG. 8d), only slightly higher flux decline was observed for protein athlete powder without calcium at both pH values, implying that the combination of polysaccharides and proteins in this fouling agent had no synergistic effects on RO membrane fouling. Interestingly the overall effect of calcium cations on Alginate and Humic acid fouling (as well as pH for humic acid) was significant while neither pH nor Calcium cations affected fouling behavior of the Athletes protein powder. This result might be attributed to interactions between all the components in this powder, mainly proteins and polysaccharides, obscuring effects of calcium addition or reducing pH. The effect of secondary effluents on the RO permeate flux decline (FIG. 8e) was compared to the ones of each of the model foulants (FIG. 8a-8d). The effect of secondary effluents on RO permeate flux decline was closest to the one of the Athletes' protein powder and slightly lower than the ones of alginate and Humic acid in the absence of calcium cations.

[0193] Example 10 - Hydraulic resistance of the fouling layers developed by the model foulants and the secondary effluents

[0194] The hydraulic resistance of each fouling layer, developed by the three model foulants and the secondary effluents, was measured at the end of the crossflow fouling experiments. Assessing hydraulic resistance of the fouling layers was done by comparing the hydraulic resistance of a pristine membrane, tested with DDW before the crossflow experiment, with that of the fouled membrane, tested with DDW after the fouling experiment. FIG. 9 shows that the hydraulic resistance of the secondary effluent deposits is slightly lower than the other model foulants in the absence of calcium cations. In the presence of calcium cations, the hydraulic resistance of Alginate and Humic acid increases significantly, reaching the same level in both foulants, while the level of the hydraulic resistance of the layer formed by the athlete’s protein powder remains unchanged. As expected, these results correlate with results of the RO crossflow fouling experiments, showing a similar trend in the presence and absence of calcium cations. The high hydraulic resistance in the presence of calcium cations for Humic acid and Alginate layers can be explained by the Cationic bridging between the molecules leading to a compact fouling layer.

[0195] Example 11 - Sensing and predicting fouling of RO membrane using LSPR

[0196] So, representing the sensitivity of the sensor, was measured before every set of experiments, by exposing the system to four elevated concentrations of Ethylene Glycol (5%, 10%, 15% and 20%), and shift in the maximum wavelength peak position, Z,max, was acquired as illustrated in FIG. 10. The observed A,max at each concentration were plotted versus the refractive index of each Ethylene Glycol concentration and illustrated in the inserted figure in FIG. 10. So is calculated by linear fitting and is used in the calculation of the dry mass accumulated on the LSPR sensor (Equations 4 & 5)

[0197] Refractive index increment, dn / dc, varies between materials according to their refractive index. The dn / dc measurement was conducted by determining the RI of known concentrations of the foulant. The results for the dn / dc refractive index increment for Alginate and Humic acid, which were used for calculating the layer thickness on the LSPR sensors, are presented in FIG. 11. A literature dn / dc value of 0.2 which is common for proteins was used for both cases of fouling with protein athletes’ powder and secondary effluents.

[0198] The dry-molecular-mass surface concentration (Ts) of the adsorbed model foulants and dissolved organic matter from secondary effluents on the polyamide surface was determined by observing the shift in light-extinction maxima, AZ, of the LSPR sensor (FIG. 12a-12d). The dry mass was calculated using Equations 4 and 5 (FIG. 13). Accumulation rate and the final adsorbed mass of the foulants are presented in FIG. 13a, and 13b.

[0199] Humic acid and Alginate exhibited the highest adsorbed mass in the presence of calcium cations of 128.06 ng / cm2and of 129.45±47.7 ng / cm2, respectively, (FIG. 13a and 13b), mirroring the trend observed in the RO experiments (FIG. 13a-13c). Additionally, the protein athletes’ powder demonstrated a relatively high adsorbed mass of 41.58±5.05 ng / cm2, irrespective of the chemical composition, similar to the results in the RO fouling experiments. The adsorbed dry masses of the model foulants were consistent with their impact on membrane permeate flux, categorizing them into two distinctive groups, in the presence and absence of calcium cations (FIG. 13e). Interestingly, the fouling of the sensor by the secondary effluents DOC provided a similar magnitude of surface concentration (~70 ng / cm2) while injecting to the sensor DOC with almost one order of magnitude lower concentration than the model foul ants.

[0200] Example 12 - SDI prediction of RO membrane fouling by the model foulants and the secondary effluents

[0201] As SDI is considered a method most desalination plants use to predict fouling, SDI measurements were conducted for the model foulants at pH 7, with and without calcium cations and for the secondary effluents (FIG. 14). As expected, the presence of calcium cations increased the SDI values for all foulants. Notably, a lower SDI value was measured for the secondary wastewater effluents. Calcium cations affect the SDI values of Humic acid and Alginate solutions, and the low SDI value of the secondary effluents provides a specific proxy for the RO fouling experiments (FIG. 14 and FIG. 8a-8e). SDI and turbidity measurements or a side stream with a membrane module that desalinates similar feed water of the RO stage, are all “golden standards” used for prediction of RO fouling scenarios. While SDI measurement provides rapid, though inaccurate information, accurate information of fouling propensity of the feed water is provided by a side stream RO membrane module design, though such an alarm is commonly, too late.

[0202] Example 13 - Statistical comparison of methods of predicting fouling in RO membrane

[0203] The compared methodologies for the prediction of RO membrane fouling included SDI, QCM-D and LSPR. This highlighted the potential inconsistencies between QCM-D and RO membrane fouling experiments when both permeate flux decline and fouling layer hydraulic resistance are linked to either, the decrease in the resonance frequency (at the 5thand the 7thovertones), or to the calculated hydrated mass (Table 2). This example also highlighted the potential inconsistencies between SDI and RO membrane fouling experiments, when both permeate flux decline and fouling layer hydraulic resistance are linked to the SDI results (Table 2). In contrast to QCM-D and SDI analyses, LSPR analysis confirms, well in advance, the interactions of foulants with a surface mimicking membrane material (e.g., polyamide) suggesting LSPR as a novel prediction tool for RO membrane fouling. Hence, the Pearson t- test statistical analysis indicates a significant and strong correlation between RO fouling indicators (permeate flux and fouling layer hydraulic resistance) and the LSPR adsorbed mass (Table 2) Table 3 shows the comparative results taken for the Pearson t-test correlation. Results were obtained by RO crossflow filtration experiment, LSPR mass surface concentration sensing, QCM sensing, hydraulic resistance experiment, and SDI measurement.

[0204] Table 2,

[0205] Table 3,

Claims

CLAIMSWhat is claimed is:

1. A fouling sensor for predicting and / or assessing the extent of fouling of nanofiltration (NF) and / or Reverse Osmosis (RO) membranes before and / or during water filtration and / or membrane cleaning, the sensor comprising: a substrate having noble metal nanoparticles on a surface thereof; and a polymer layer associated with the noble metal nanoparticles, wherein the polymer layer is characterized by similar physico-chemical properties as an active layer of the NF and / or RO membranes, and thereby the polymer layer is configured to mimic the fouling of the membranes active layer before and / or during the water filtration and / or membrane cleaning, wherein when light impinges the sensor, it is reflected and / or transmitted in a characteristic ,max, wherein a change in Xmax enables quantifying the adsorbed foulant to the sensor and therefore, is indicative of the extent of membrane’s fouling before and / or during water filtration and / or membrane cleaning.

2. The sensor of claim 1, wherein the physico-chemical properties comprise properties of surface hydrophobicity and / or surface charge.

3. The sensor of claim 2, wherein the hydrophobicity of the polymer layer is characterized by a wetting angle of about 50°-80°.

4. The sensor of any one of claims 2 and 3, wherein the surface charge is a negative charge expressed by a zeta potential of about (-30)-(-60) mV in conditions of 10 mM solution of NaCl and pH 7.

5. The sensor of any one of claims 1-4, wherein the polymer is selected from a group consisting of linear polyamide, aromatic polyamide, crossed-linked aromatic polyamide, cellulose-based polymer, polyamine, polymethacrylate, polyethersulfone (PES), polysulfone (PSU), polyester, polyvinylidene fluoride (PVDF), polyacrylonitrile, and any combination thereof.

6. The sensor of claim 5, wherein the linear polyamide comprises Nylon 6,6.

7. The sensor of any one of claims 1 -6, wherein water treated by the water filtration is selected from the group consisting of seawater, wastewater, sewage water, drinking water, irrigation water, groundwater, pool water, physiological water, and membrane cleaning solution.

8. The sensor of any one of claims 1-7, wherein the noble metal nanoparticles are in a form selected from the group consisting of nano-discs, nano-rods, nano-spheres, nano-plates, nano-dots, nano-islands, and any combination thereof.

9. The sensor of any one of claims 1-8, wherein the noble metal nanoparticles comprise a metal selected from the group consisting of gold, silver, and platinum.

10. The sensor of any one of claims 1-9, wherein the noble metal nanoparticles comprise gold.

11. The sensor of any one of claims 1-10, wherein the noble metal nanoparticles have a diameter of about 12-150 nm.

12. The sensor of claim 11, wherein the noble metal nanoparticles have a diameter of about 110-140 nm.

13. The sensor of any one of claims 1-12, wherein the substrate is selected from a group consisting of silica, alumina, titania, and zirconia.

14. The sensor of any one of claims 1-13, wherein the substrate is a silica substrate.

15. The sensor of any one of claims 1-14, further comprising a coupling agent for associating the substrate with the polymer layer.

16. The sensor of claim 15, wherein the coupling agent is a silane coupling agent.

17. The sensor of claim 16, wherein the silane coupling agent comprises a functional moiety selected from the group consisting of amine, amide, pyridine, alcohol, carbonyl, alkyl, nitrile, ester, and any combination thereof.

18. The sensor of any one of claims 16 and 17, wherein the silane coupling agent is an amino silane.

19. Use of the sensor of any one of claims 1-18 to assess fouling of the NF and / or RO membranes before and / or during water filtration.

20. Use of the sensor of any one of claims 1-18 to assess removal of fouling from the NF and / or RO membranes during cleaning thereof.

21. A method of predicting and / or sensing fouling of nanofiltration (NF) and / or Reverse Osmosis (RO) membranes before and / or during a water filtration and / or membrane cleaning, the method comprising: providing NF and / or RO membranes; providing a fouling sensor for predicting and / or assessing the extent of fouling of the NF and / or RO membranes, wherein the sensor is positioned in NF- and / or RO- based water filtration system, the sensor comprising noble metal nanoparticles associating with a polymer layer, wherein the polymer layer is characterized by similar physico-chemical properties as an active layer of the NF and / or RO membranes, and thereby the polymer layer is configured to adsorb and / or desorb foulant to a similar extent as the active layer of the NF and / or RO membranes before and / or during water filtration and / or membrane cleaning; introducing a water flow to the NF- and / or RO- based water filtration system such that the water flow contacts the sensor before and / or during the water filtration or membrane cleaning; irradiating light on the sensor to induce a reflected and / or transmitted light with a characteristic range of wavelengths; detecting the reflected and / or transmitted light; and determining a change in a characteristic Xmax before and / or during the water filtration and / or membrane cleaning, wherein the change in Xmax facilitates quantifying the adsorbed and / or desorbed foulant to the sensor and therefore, is indicative of the extent of membrane’s fouling before and / or during water filtration and / or membrane cleaning.

22. The method of claim 21, wherein the sensor is configured to be positioned beside, upstream, downstream, and / or within the membrane.

23. A method of simulating and predicting and / or assessing fouling of NF and / or RO membranes before and / or during a simulation of water filtration and / or membrane cleaning, the method comprising:providing a fouling sensor configured to be positioned instead of NF and / or RO membranes to simulate and assess an extent of fouling in the membranes, wherein the sensor comprising noble metal nanoparticles associating with a polymer layer, wherein the polymer layer is characterized by similar physico-chemical properties as an active layer of the membranes, and thereby the polymer layer is configured to adsorb foulant to a similar extent as the active layer of the membranes before and / or during water filtration and / or membrane cleaning; flowing water such that the water flow contacts the sensor before and / or during the simulation of the water filtration and / or membrane cleaning; irradiating light on the sensor to induce a reflected and / or transmitted light with a characteristic range of wavelengths; detecting the reflected and / or transmitted light; and determining a change in a characteristic Xmax before and / or during the simulation of the water filtration and / or membrane cleaning, wherein the change in Xmax enables quantifying the adsorbed foulant to the sensor and therefore, is indicative of the extent of a simulated membrane’s fouling before and / or during water filtration and / or membrane cleaning.

24. The method of any one of claims 21-23, wherein the extent of the fouling is assessed continuously, during the water filtration.

25. The method of any one of claims 21-23, wherein the extent of the fouling is assessed in one or more selected time points.

26. A method of producing a fouling sensor for RO and / or NF membranes, the method comprising: providing a substrate associated with noble metal nanoparticles; and applying a polymer layer atop the noble metal nanoparticles, thereby producing the fouling sensor.

27. The method of claim 26, further comprising cleaning the substrate before applying the polymer layer.

28. The method of claim 27, wherein the cleaning comprises a treatment selected from UV / ozone, plasma, sonication, solvent dip-washing, solvent spray-washing, acidic solution treatment, alkaline solution treatment, drying, and any combination thereof.

29. The method of any one of claims 26-28, further comprising applying a coupling layer on the substrate, to facilitate the application of the polymer layer.

30. The method of any one of claims 26-29, wherein the application of the polymer layer is via a technique selected from a group consisting of interfacial polymerization, spin coating, drop casting, spraying, vapor deposition, and any combination thereof.

31. A system of NF- and / or RO-based water filtration, the system comprising:NF and / or RO membranes; a fouling sensor for assessing the extent of fouling of the NF and / or RO membranes or membrane sets, wherein the sensor comprising a substrate having noble metal nanoparticles on a surface thereof, wherein the noble metal nanoparticles are associated with a polymer layer, wherein the polymer layer is characterized by similar physico-chemical properties as an active layer of the NF and / or RO membranes, and thereby the polymer layer is configured to adsorb / desorb foulant to a similar extent as the active layer of the NF and / or RO membranes during water filtration and / or membrane cleaning; a water flow conduit system configured to direct water flow to contact the sensor and the NF and / or RO membranes before and / or during the water filtration and / or membrane cleaning; a light source configured to irradiate light on the sensor; an optical detector configured to detect light reflected and / or transmitted from and / or through the sensor; and a processing circuitry configured to: determine a characteristic kmax of the reflected and / or transmitted light; determine a change in kmax detected before and / or during the water filtration and / or membrane cleaning; and calculate an extent of fouling of the sensor based on the change in kmax, and accordingly assess the extent of fouling of the membrane’s active layer.

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