Wool washing wastewater recovery treatment process

Abstract

The invention relates to the technical field of environmental engineering, and discloses a wool washing wastewater recovery treatment process which comprises the following steps: S1, carrying out demulsification pretreatment on wastewater through bionic nano-enzyme and recovering wool fat, S2, carrying out supercritical water gasification reaction on the pretreated wastewater, synchronously decomposing organic matters and generating hydrogen, the method comprises the following steps: S1, gasifying effluent, S2, carrying out gasification on the effluent, S3, carrying out filtration and biodegradation on the gasified effluent by adopting a self-energy-supply dynamic membrane bioreactor, S4, carrying out deep purification on membrane effluent through a photocatalysis-microalgae coupling system, and S5, coordinating operation of the whole system through an intelligent control algorithm based on real-time monitoring data. According to the method disclosed by the invention, the technical effects of efficiently recovering the wool fat and improving the oil-water separation selectivity are achieved by adopting a technical scheme of synergistically enriching and demulsifying the magnetic response bionic nano-enzyme and the high-gradient magnetic field; the problems of high reaction residue, serious secondary pollution and easy enzyme inactivation are solved.

Description

Technical Field

[0001] The invention relates to the technical field of environmental engineering, in particular to a wool washing wastewater recycling and treatment process. Background Art

[0002] Wool washing wastewater recycling and treatment processes are primarily used in the primary cleaning phase of the wool textile processing industry. Their primary goal is to remove grease, dust, and protein-based impurities from the surface of raw wool. This type of wastewater generally contains high concentrations of lanolin, surfactants, soluble proteins, organic particulate matter, and other components, exhibiting strong emulsion stability and chemical oxygen demand (COD) load, representing a typical high-concentration organic emulsified wastewater. Traditional treatment processes often employ a combination of chemical coagulation, flotation, and biochemical treatment. These processes have, to a certain extent, supported the wool textile industry's basic wastewater discharge compliance requirements and are widely deployed in wastewater treatment projects for processes such as wool degreasing and wool top washing.

[0003] Existing technologies are still limited in many aspects. Although chemical demulsifiers can quickly depolymerize emulsified systems, their high-dose use often causes secondary pollution of water bodies and is difficult to control the balance of addition, affecting the operation of subsequent biochemical units; membrane bioreactors are susceptible to oil and colloid contamination during the treatment process, and the membrane surface lacks active anti-fouling capabilities, with short operating cycles and frequent maintenance; high-efficiency organic matter removal technologies such as supercritical oxidation consume a lot of energy, and the system energy port cannot be closed, making it difficult to achieve self-sustaining operation; the terminal deep purification link mostly uses a single photocatalysis or a single algae culture, with low process coupling efficiency and insufficient resource utilization; the overall process control relies on human experience and judgment, making it difficult to adapt to fluctuations in influent water quality in real time, lacking accurate prediction and linkage control mechanisms, and the treatment system has poor stability and adaptability. These problems overlap, limiting the upgrade path of wool washing wastewater treatment technology towards high efficiency, low carbon, and intelligentization.

[0004] In view of this, it is necessary to provide a new technical solution to solve the above problems. To this end, the present invention proposes a wool washing wastewater recycling and treatment process. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides a wool washing wastewater recycling and treatment process, which solves the problems in the existing technology such as high risk of secondary pollution in the demulsification process, insufficient anti-fouling ability of the membrane separation system, high energy consumption of the oxidation unit and difficulty in closed-loop operation, low resource recovery rate and control method relying on manual judgment and difficulty in achieving adaptive regulation.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A wool washing wastewater recycling and treatment process, comprising the following steps:

[0007] S1, demulsification pretreatment of wastewater and recovery of lanolin by biomimetic nanoenzymes;

[0008] In this phase, FeO@ZIF-8 core-shell biomimetic nanozymes are used to achieve efficient demulsification of oil-water systems and targeted recovery of lanolin. The microporous structure of the ZIF-8 shell (pore size 0.34-0.36nm) has a selective adsorption capacity for long-chain alkyl groups in lanolin. At the same time, the lipase and protease loaded on its surface form local catalytic hotspots at the oil-water interface, accelerating oil hydrolysis. The Fe3O4 core gives the nanozyme magnetic responsiveness, and under the drive of a gradient magnetic field (0.5-2.0T / m), it is directionally enriched in the interfacial region, with a catalytic efficiency more than three times that of traditional demulsifiers. After demulsification, the photothermal effect of Fe3O4 is excited by 808nm near-infrared light (locally heating to 60-80°C), removing oil residues adsorbed on the enzyme active sites and achieving in situ regeneration of the nanozyme. This process simultaneously completes the magnetic separation and recovery of lanolin (purity ≥85%), avoiding the risk of secondary contamination of chemical demulsifiers.

[0009] S2, subjecting the pretreated wastewater to supercritical water gasification reaction to simultaneous decomposition of organic matter and generation of hydrogen;

[0010] The pretreated wastewater undergoes a free radical chain reaction in supercritical water (380-400°C, 22.1-25.0MPa), and organic matter (such as surfactants and residual oils) is completely decomposed into H2, CO2 and small molecular acids. The low dielectric constant and high diffusion coefficient of supercritical water promote the collision of reactant molecules, and the H2 yield reaches 3.5-4.2L / gCOD. The innovative hydrogen and oxygen dual circulation design introduces the H2 produced by SCWG into the microbial electrochemical unit (MES) of the subsequent dynamic membrane system as an electron donor to drive the degradation of pollutants; at the same time, the O2 produced at the cathode of the MES is returned to the supercritical reactor to participate in the chain reaction of the generation of ·OH radicals, thereby increasing the oxidation efficiency by more than 40%. The Ni-Ti shape memory alloy sealing ring undergoes temperature-induced phase change. Adaptively adjust the sealing pressure to ensure zero leakage operation under high temperature and high pressure.

[0011] S3. Using a self-powered dynamic membrane bioreactor to filter and biodegrade the gasification effluent;

[0012] The dynamic membrane uses a graphene / bacterial cellulose composite substrate, and the conductive network of graphene (conductivity ≥ 10 3 S / m) allows the application of a membrane potential of -0.3 to +0.2V, repelling negatively charged pollutant colloids through electrostatic force (Zeta potential -15 to -30mV). The bacterial cellulose membrane continues to grow in situ (thickness 50-200μm) under the metabolism of Acetobacter xylinum, dynamically updating the membrane surface structure to prevent deep clogging of pollutants. The H2 provided by the SCWG is oxidized in the MES anode chamber to generate biocurrent (current density 1.2-1.8mA / cm 2), driving the membrane potential control system and achieving a net production capacity of 0.5-0.8kWh / m 3 This design reduces the membrane fouling rate to 20% of traditional MBR while eliminating energy dependence on the external power grid.

[0013] S4, deep purification of membrane effluent through photocatalysis-microalgae coupling system;

[0014] The photocatalytic unit uses TiO2 / nitrogen-doped graphene heterojunction catalyst. Nitrogen doping introduces an intermediate energy level (the band gap is reduced from 3.2eV to 2.8eV), which broadens the UV-visible light response range to 420nm, and the hole (h + ) and superoxide radicals (·O2 - ) synergistically degrades trace organic matter (COD removal rate> 95%). In the microalgae unit, Chlorella absorbs CO2 and nitrogen and phosphorus from the photocatalytic effluent through mixed metabolism, with a carbon fixation rate of 1.2-1.8g / (m 2 d), and simultaneously synthesize algae oil (yield 15-20g / m 3 ) as a biodiesel feedstock. The synergistic carbon-nitrogen cycle of photocatalysis and microalgae reduces the system's net CO2 emissions by 85%, achieving the dual goals of wastewater treatment and biomass co-production.

[0015] S5, based on real-time monitoring data, coordinates the operation of the entire system through intelligent control algorithms;

[0016] The prediction model built based on the LSTM neural network (15 nodes in the input layer and 32-64 nodes in the hidden layer) analyzes parameters such as magnetic field gradient, membrane potential, and microalgae biomass in real time, predicting water quality fluctuation trends 10-30 minutes in advance. For example, when the COD of the influent increases suddenly, the model will enhance the magnetic field gradient (to 2.0T / m) and extend the near-infrared irradiation time (to 12 minutes) to ensure stable demulsification efficiency; when the risk of membrane fouling increases, the applied potential is dynamically adjusted to -0.3V to enhance electrostatic repulsion. This intelligent control system enables the process to maintain stable operation under water quality fluctuations of ±30%, reducing the frequency of manual intervention by 90%.

[0017] The biomimetic nanozyme adopts an Fe3O4@ZIF-8 core-shell structure design. Its core is magnetic Fe3O4 nanoparticles (particle size 50-60nm), which give the material magnetic response properties; the shell is a ZIF-8 metal-organic framework (shell thickness 50-80nm). Its microporous structure (pore diameter 0.34-0.36nm) forms a size-matching effect with the long-chain alkyl groups (C16-C18) in lanolin molecules, achieving selective adsorption through van der Waals forces. The three-dimensional pores of ZIF-8 are directionally loaded with lipase and protease (mass ratio 1:1.2), forming a localized high concentration of catalytic sites, which increases the oil hydrolysis rate by more than 3 times compared with traditional free enzymes.

[0018] During the demulsification process, a gradient magnetic field (0.5-2.0 T / m) is dynamically controlled by an electromagnetic coil array, driving the nanozymes to directional enrichment at the oil-water interface. The Lorentz force generated by the magnetic field gradient causes the nanozymes to form a concentration gradient at the interface (increasing the concentration by 8-10 times compared to the bulk). Combined with the microwave thermal effect of the Fe3O4 core (locally heating to 40-50°C), this significantly reduces the activation energy of the enzyme-catalyzed reaction. This process simultaneously achieves efficient demulsification of the oil phase (COD removal rate ≥80%) and initial enrichment of lanolin.

[0019] After demulsification is completed, near-infrared light with a wavelength of 800-810 nm (optical power density 1.5-2.0 W / cm 2 ) to irradiate the nanozyme. The photothermal conversion properties of the Fe3O4 core cause the surface temperature of the nanozyme to rise instantly to 60-80°C, prompting the thermal desorption of oil residues adsorbed on the active site of the enzyme, while the thermal stability of the ZIF-8 shell (decomposition temperature > 350°C) protects the enzyme protein from high-temperature denaturation. After the nanozyme recovered by magnetic separation is regenerated in this way, the activity recovery rate is > 90%, and it can be recycled ≥ 50 times. This magneto-optical synergistic regeneration mechanism breaks through the problem of enzyme activity loss caused by traditional chemical cleaning methods, while avoiding secondary pollution.

[0020] Preferably, the nanozyme concentration (0.5-1.0 g / L) and reaction conditions (40-50 ° C, 25-35 min) were optimized by multi-factor orthogonal experiments. A lower dosage (<0.5 g / L) leads to insufficient interfacial catalytic sites and reduced demulsification efficiency; an excessively high dosage (>1.0 g / L) reduces the specific surface area utilization rate due to the nanozyme agglomeration effect (DLS particle size increases from 50 nm to 200 nm). At a reaction temperature of 40-50 ° C, the thermal expansion coefficient of the ZIF-8 shell (8.5×10 -6 / °C) matches the Fe3O4 core, preventing shell rupture due to thermal stress. This temperature range also optimizes lipase activity (Km value reduced by 30%). A reaction time of 25-35 minutes balances enzyme catalytic kinetics (Michaelis constant Km = 0.8 mM) with industrial processing efficiency requirements, shortening the reaction time by over 60% compared to traditional chemical demulsification processes.

[0021] Near infrared light power density (1.5-2.0W / cm 2 ) and irradiation time (8-12min) to ensure the optimal balance between enzyme activity regeneration and energy consumption. 2 When the photothermal effect is insufficient (surface temperature < 50 ° C), the oil desorption rate is < 70%; higher than 2.0W / cm 2This leads to local overheating (>90°C), causing partial collapse of the ZIF-8 skeleton (the XRD characteristic peak intensity decreases by 15%). The irradiation time of 8-12 minutes allows the accumulation of photothermal energy to be sufficient to destroy the hydrophobic interaction between the oil and the enzyme active site (the contact angle decreases from 110° to 40°), while avoiding free radical damage caused by long-term radiation (the enzyme activity loss rate is controlled within 5%). This parameter combination allows the nanozyme to maintain more than 85% of its initial activity after 50 cycles, breaking through the cumulative activity decay caused by the traditional acid / base cleaning method (activity <50% after 5 cycles)

[0022] Preferably, the supercritical water gasification reaction is operated under the conditions of pressure 22.1-25.0MPa and temperature 380-400℃. This parameter range accurately matches the critical point of water (374℃, 22.1MPa), making water in a supercritical state (dielectric constant <5, diffusion coefficient >10 -4 cm 2 / s). In this state, the polarity of water molecules is significantly reduced, forming a microenvironment similar to a non-polar solvent, which promotes the dissolution and homogeneous mixing of hydrophobic organic matter (such as residual lanolin and surfactants). Organic molecules in supercritical water rapidly decompose through a free radical chain reaction (dominated by ·OH and HO2·), where the activation energy of C-H bond cleavage is reduced from 120kJ / mol in conventional hydrolysis to below 60kJ / mol, and the reaction rate is increased by more than 4 times. The setting of a residence time of 3-5 minutes balances the need for complete mineralization of organic matter (conversion rate >99%) with the economic efficiency of the equipment's pressure limit, shortening the time by 60% compared to traditional supercritical processes (requiring 10-15 minutes).

[0023] The hydrogen generated by the supercritical reaction (yield 3.5-4.2L / gCOD) is transported to the microbial electrochemical system (MES) of the subsequent dynamic membrane bioreactor through a pressure-resistant pipeline (1.0-1.5MPa) to drive denitrification and organic matter degradation as an electron donor, replacing the traditional process that relies on the addition of external carbon sources (such as methanol). At the same time, the oxygen (purity>95%) generated by the MES cathode in the bioelectrocatalytic process is returned to the supercritical reactor and mixed with the influent at a volume ratio of 1:20-1:30. The returned oxygen rapidly dissociates into active oxygen species (such as O - 、O2 - ), participates in the initiation and transmission of free radical chain reactions, increases the OH generation rate by 40%, and increases the organic matter mineralization efficiency from 85% to over 98%. This cycle design forms a closed loop of "H2-O2-energy", and the net energy consumption of the system is reduced by 70% compared with the traditional supercritical process.

[0024] Preferably, the supercritical reactor uses a Ni-Ti shape memory alloy seal ring (Ni:Ti=50.8:49.2), with a preload designed to be 15-20kN / m, achieving dynamic sealing compensation through temperature-induced martensite-austenite phase transformation. During the reactor startup phase (25°C), the alloy is in the martensite phase (yield strength 600MPa), and the preload provides an initial seal. When the temperature rises to 380-400°C, the alloy transforms into austenite (yield strength 1,200MPa), with a volume expansion rate of 2.8%, automatically compensating for changes in the flange gap due to thermal expansion. This design maintains the sealing surface contact pressure at 20-25MPa, reducing the leakage rate by more than 90% compared to traditional graphite gaskets (which are prone to creep failure), ensuring long-term stable operation of the supercritical water gasification reaction at a high pressure of 25.0MPa.

[0025] The parameter design of the hydrogen transport pipeline (pressure 1.0-1.5MPa, temperature 25-30℃) takes into account both the hydrogen molecule diffusion efficiency and the material hydrogen embrittlement risk control. The transport pressure of 1.0-1.5MPa keeps the hydrogen density at 0.08-0.12kg / m 3 , matching the hydrogen demand rate (0.5-0.8L / min) of the subsequent dynamic membrane bioreactor microbial electrochemical system (MES). The temperature is controlled in the range of 25-30℃, and the self-heating of hydrogen in the pipeline is suppressed by an external water cooling jacket (ΔT < 5℃), avoiding the 316L stainless steel pipe due to hydrogen permeation (permeability coefficient < 1×10 -13 m 2 This parameter combination enables hydrogen transport efficiency (defined as actual utilization / theoretical supply) to reach over 85%, a significant improvement over traditional atmospheric pressure transport (efficiency <50%).

[0026] Preferably, the dynamic membrane adopts a composite structure of graphene substrate and in-situ grown bacterial cellulose, and the two-dimensional graphene sheets (thickness 0.8-1.2nm) form a continuous conductive network (conductivity ≥10 3 S / m), providing a carrier for the precise regulation of membrane potential. After Acetobacter xyl inum is inoculated on the graphene surface, it metabolizes into bacterial cellulose fibers (diameter 20-50nm) within 48-72 hours, which are interwoven into a three-dimensional porous skeleton (porosity 75% to 85%) through hydrogen bonds and van der Waals forces. This composite structure combines the mechanical strength of graphene (elastic modulus 1.0TPa) and the hydrophilicity of bacterial cellulose (contact angle 30°), making the membrane flux reach 20-30L·m -2 ·h -1 , more than twice that of traditional PVDF membranes, and the tensile strength is increased to 50-60MPa, avoiding structural collapse during operation.

[0027] The -0.3V to +0.2V potential applied to the membrane surface is dynamically controlled by an external circuit to form a directional electric field to inhibit pollutant deposition. When the membrane potential is -0.3V, the negatively charged pollutant colloids (Zeta potential -15 to -30mV) are affected by the electrostatic repulsion force (F = 1.2-2.5nN), and the migration rate is reduced by more than 80%; when the potential is switched to +0.2V, the electrochemical oxidation reaction (peak current density 0.5mA / cm 2 ) decomposes adsorbed organic pollutants. The potential control response time is less than 5s (achieved by PID controller), which can match the fluctuation of influent pollutant concentration in real time, reducing the membrane fouling rate to 0.5-1.0kPa / h, which is only 15% to 20% of the traditional MBR. The setting of 5-10kPa transmembrane pressure difference balances flux demand and energy consumption control, saving more than 40% energy compared with conventional MBR (transmembrane pressure difference 15-30kPa).

[0028] Preferably, the energy supply of the dynamic membrane system is completely dependent on the hydrogen produced by the supercritical water gasification reaction, and the net capacity of the system is 0.5-0.8kWh / m through the hydrogen-electricity-membrane energy closed loop. 3 The hydrogen generated by the supercritical reaction (yield 3.5-4.2L / gCOD) is transported to the microbial electrochemical system (MES) of the dynamic membrane bioreactor through a pressure-resistant pipeline (1.0-1.5MPa). In the anode chamber, it is oxidized by electrogenic bacteria (such as Geobacter) to release electrons. The electrons are transferred to the cathode through an external circuit to drive the oxygen reduction reaction (ORR). At the same time, the protons (H + ) migrates through the proton exchange membrane to the cathode chamber, forming a complete current loop. During this process, the Coulombic efficiency of converting the chemical energy of hydrogen into electrical energy reaches 85% to 90%, significantly higher than that of traditional microbial fuel cells (typically <50%). Each cubic meter of wastewater can generate 1.2-1.5 kWh of electricity, of which 0.7-0.9 kWh is used to maintain dynamic membrane potential regulation, pump operation, and other self-consumption energy. The remaining 0.5-0.8 kWh is used as net output, forming an energy-consistent wastewater treatment system.

[0029] The hydrogen production from supercritical water gasification and the energy consumption of the dynamic membrane system (0.7-0.9kWh / m 3 Dynamic balance is achieved through a flow feedback control system: When the hydrogen production rate fluctuates, the load resistance of the MES is adjusted in real time (range 10-100Ω) to ensure that the current density is stable at 1.5-2.0mA / cm 2, avoiding energy waste caused by "excess hydrogen" or membrane potential failure caused by "insufficient hydrogen." This design enables the system to maintain stable net production capacity even when the supercritical reaction load (COD5,000-25,000mg / L) fluctuates by ±30%, breaking through the traditional process's reliance on external power grids for energy supply. Furthermore, the oxygen generated in the cathode chamber (purity >95%) is fed back to the supercritical reactor to participate in the free radical chain reaction, forming a dual material-energy cycle, further reducing the system's overall energy consumption.

[0030] Preferably, the photocatalytic unit uses TiO2 / nitrogen-doped graphene heterojunction catalyst, which introduces p-type semiconductor characteristics (Fermi level shifted down 0.3eV) into the graphene lattice by nitrogen atom doping, forming a Z-type heterojunction with n-type TiO2 (band gap 3.2eV). Under 360-370nm ultraviolet light excitation, the valence band electrons of TiO2 jump to the conduction band of nitrogen-doped graphene, and the holes (h + ) is retained in the TiO2 valence band, and the built-in electric field strength in the space charge region reaches 10 4 V / m, effectively inhibiting the recombination of photogenerated electrons and holes (recombination rate <15%). Holes react with adsorbed water molecules to generate OH radicals (concentration 0.8-1.2 mmol / L), and electrons are transferred to the surface through the graphene conductive network, reducing O2 to generate O2 - (ESR detection intensity increased by 2 times), double free radicals synergistically degrade residual organic matter (COD removal rate> 95%). The optimized design of TiO2 loading of 15-20wt% balances the active site density (BET specific surface area 380-420m 2 / g) and light transmission efficiency (UV light utilization rate 75-85%). Excessive loading (>20wt%) leads to increased light scattering and a 30% decrease in reaction rate.

[0031] The microalgae cultivation unit uses Chlorella vulgaris, whose photoautotrophic and mixotrophic metabolic characteristics are highly compatible with the photocatalytic effluent components. Under a light intensity of 8000-10000 lux, the maximum quantum yield (Fv / Fm) of the chloroplast photosynthetic system II (PSI I) reaches 0.75-0.80, and the light energy conversion efficiency (PE) is 8-10%, which encourages the microalgae to preferentially utilize the CO2 (concentration 1200-1500ppm) and NH4 produced by photocatalysis. + -N (20-30mg / L) for biomass synthesis. CO2 ventilation rate of 0.8-1.2L / min through the Venturi ejector to achieve micron-level bubble dispersion (diameter 50-100μm), the gas-liquid mass transfer coefficient (KLa) is increased to 0.15-0.20s -1 The carbon fixation rate is 1.5-2.0g / (m 3Under these conditions, the microalgae biomass yield (based on dry weight) is 1.2-1.5 kg / m 3 Wastewater, with an algal lipid content of 18% to 22%, can be used as a raw material for biodiesel. At the same time, it secretes extracellular polysaccharides (EPS production 0.3-0.5g / L) to inhibit the regeneration of effluent bacteria and reduce the subsequent addition of disinfectants.

[0032] Preferably, parameters such as magnetic field gradient (0.5-2.0T / m), supercritical pressure (22.1-25.0MPa), membrane potential (-0.3~+0.2V) and microalgae biomass concentration (0.5-1.5g / L) monitored in real time are synchronously transmitted to the central processing unit at a frequency of 10Hz through the Industrial Internet of Things (IIoT). These parameters characterize demulsification efficiency, degree of organic matter mineralization, membrane fouling state and carbon and nitrogen metabolic activity, respectively, and their coupling relationship constitutes a high-dimensional nonlinear system (dimension ≥ 15). The LSTM neural network receives real-time data streams with 15 nodes in the input layer (corresponding to 15 key parameters), extracts long-range dependency features in the time series through the gating mechanism of forgetting gate, input gate and output gate (sigmoid function weight range 0.2-0.8), and the adaptive adjustment ability of 32-64 nodes in the hidden layer (Dropout rate 0.2) effectively suppresses overfitting, so that the mean square error (MSE) of the prediction step size 10-30min is stabilized below 0.05.

[0033] LSTM model based on historical data (>10 6 A set of training samples) predicts the trends of key parameters of each module within the next 10-30 minutes. For example, when the influent COD is predicted to surge by 20%, the magnetic field gradient is adjusted to the upper limit (2.0T / m) in advance and the near-infrared irradiation time is extended to 12 minutes, so that the fluctuation of demulsification efficiency is controlled within ±5%. At the same time, the model dynamically updates the weight matrix through back propagation (learning rate 0.001) to adapt to water quality changes (such as sudden changes in lanolin content and delayed microalgae growth) in real time. This predictive control strategy enables the system to maintain effluent COD ≤50mg / L when the influent COD fluctuates by ±30%. The frequency of manual intervention is reduced to 10% of traditional PID control, and operational stability is improved by more than 40%.

[0034] Preferably, the system is organically composed of a bionic nanoenzyme demulsification unit, a supercritical water gasification reactor, a self-powered dynamic membrane bioreactor, a photocatalytic-microalgae coupling deep purification unit and an intelligent control unit. The units are closely connected in function to construct a closed-loop wastewater treatment system that integrates decontamination, production capacity, resource utilization and intelligent regulation.

[0035] At the head end of the system, a biomimetic nanozyme demulsification unit is responsible for depolymerizing emulsified pollutants and efficiently recovering lanolin in wool washing wastewater. This unit utilizes a core-shell biomimetic nanozyme material with peroxidase-like catalytic activity and a magnetic core for directional recovery. Its demulsification mechanism relies not only on physical perturbation but also incorporates catalytic interfacial reactions at the nanoscale, achieving efficient decomposition of lanolin and surfactants into a stable emulsion structure. Magnetic field gradient induction allows for precise control of the nanozyme's distribution in the wastewater and its recovery path, thereby improving demulsification efficiency and reducing the potential for secondary contamination.

[0036] The pretreated wastewater enters the supercritical water gasification reactor, which operates under high temperature and high pressure, causing the water to enter a supercritical state, thereby greatly improving its solubility and reaction activity for organic matter. Under the action of supercritical water, the organic components in the wastewater can be rapidly cracked into small molecular gases such as CO2, CH4 and H2, among which hydrogen is mainly recovered and used for energy supply of subsequent reaction systems. The core innovation of this unit is that it combines traditional thermochemical treatment methods with resource conversion pathways to construct a green energy generation mechanism based on pollutant decomposition, significantly improving the resource recovery efficiency of the treatment and the energy self-sustainability of the system.

[0037] The gasified effluent then flows into a self-powered dynamic membrane bioreactor. This unit uses a composite membrane structure coupled with an external electric field control to achieve precise filtration and simultaneous biodegradation of wastewater. Its core structure includes a conductive membrane layer based on graphene and an in-situ grown bacterial cellulose layer, which has good hydrophilicity and anti-pollution properties. During the biodegradation process, the dynamic balance of adsorption and desorption of pollutants on the membrane surface is achieved through potential control, effectively inhibiting the occurrence of membrane fouling. At the same time, part of the energy required for the reactor comes from the hydrogen produced by the front-end supercritical reactor, thereby realizing a closed-loop self-supply of energy between systems. This design breaks the energy consumption bottleneck in the traditional membrane-bioreactor coupling process, taking into account both treatment efficiency and energy sustainability.

[0038] Next, the effluent enters the photocatalytic-microalgae coupled deep purification unit, which further reduces the residual organic pollutants and nutrients in the wastewater through the synergistic action of two mechanisms. The system uses high-efficiency TiO2-based composite catalytic materials to generate strong oxidizing free radicals such as OH under irradiation of a specific wavelength, achieving thorough mineralization of small organic molecules. The initially purified water is then introduced into the microalgae cultivation module, which utilizes the microalgae's highly selective absorption capacity for nutrients such as nitrogen and phosphorus to achieve the final removal of trace pollutants in the wastewater. At the same time, the growth of microalgae also achieves the biological fixation of CO2, providing support for the system's carbon footprint control and reflecting the environmentally friendly end-of-pipe treatment concept.

[0039] To achieve dynamic stability and efficient operation of the system, the entire process is collaboratively managed by an intelligent control unit. This unit implements comprehensive scheduling across multiple dimensions, including magnetic field, temperature, pressure, potential, and bioburden, through real-time acquisition and predictive analysis of key process parameters. The control strategy, based on a deep learning model, uses historical data training to predict operating status and dynamically adjust control instructions, ensuring the system maintains optimal treatment efficiency and energy consumption under varying wastewater loads and environmental fluctuations.

[0040] The present invention provides a wool washing wastewater recycling and treatment process, which has the following beneficial effects:

[0041] 1. The present invention adopts a technical solution of synergistic enrichment and demulsification of magnetically responsive bionic nanoenzymes and high-gradient magnetic fields, achieving the technical effect of efficiently recovering lanolin and improving the selectivity of oil-water separation. Compared with the technical solution in the prior art that relies on chemical demulsifiers to achieve emulsion decomposition, it solves the problems of high reaction residues, serious secondary pollution and easy enzyme inactivation.

[0042] 2. The present invention adopts a technical solution of organic matter oxidation and energy closed loop by coupling supercritical water gasification with hydrogen and oxygen dual circulation, which achieves the technical effect of efficient mineralization of pollutants while realizing self-sufficiency of system energy. Compared with the technical solution of conventional thermal oxidation or wet incineration for wastewater treatment in the prior art, it solves the problems of low reaction efficiency, large external energy consumption and high carbon emissions.

[0043] 3. The present invention adopts an anti-pollution membrane separation technology solution with a potential-regulated graphene-bacterial cellulose composite dynamic membrane structure, which achieves the technical effect of reducing the membrane pollution rate and extending the membrane life. Compared with the static membrane filtration technology solution prepared with inert materials in the prior art, it solves the defects of easy scaling on the membrane surface, frequent replacement, and discontinuous system operation.

[0044] 4. The present invention adopts a photocatalytic-microalgae coupled carbon and nitrogen resource synergistic pathway technology solution, achieving the technical effect of deep purification of effluent and simultaneous synthesis of high-value-added biomass. Compared with the existing technical solutions of single microalgae treatment or photocatalytic separation operation, it solves the shortcomings of low carbon source utilization efficiency, high nitrogen and phosphorus residues in effluent, and broken energy conversion links. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 Schematic diagram of the steps of the present invention;

[0046] Figure 2 Schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0047] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the present specification. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0048] Please see the attached Figure 1 and attached Figure 2 :

[0049] Example 1: High gradient magnetic field synergistic nanozyme demulsification process

[0050] Purpose:

[0051] Optimize the demulsification efficiency and cyclic stability of bionic nanozymes under strong gradient magnetic fields to achieve efficient recovery of lanolin.

[0052] Implementation steps:

[0053] Nanozyme preparation

[0054] Synthesis of Fe3O4 core: Dissolve 0.1 mol FeCl3·6H2O and 0.05 mol FeSO4·7H2O in 500 mL deionized water, add 25% NH3·H2O dropwise under nitrogen protection to pH 10.5, stir at 80℃ for 2 h, and wash by magnetic separation.

[0055] ZIF-8 shell growth: Fe3O4 was dispersed in a methanol / water (4:1) mixture, 2-methylimidazole (0.8 mol / L) and Zn(NO3)2·6H2O (0.1 mol / L) were added, reacted at 80℃ for 10 h, and centrifuged to dry.

[0056] Enzyme loading: lipase (100 mg) and protease (120 mg) were dissolved in pH 7.0 buffer and adsorbed with nanozyme (1 g) under oscillation at 4°C for 24 h, with a loading capacity of 135 mg / g.

[0057] Demulsification operation

[0058] Wastewater conditions: COD 15,000 ± 300 mg / L, lanolin content 9.2%, temperature 48 ± 2 ° C, pH 6.8.

[0059] Magnetic field parameters: gradient magnetic field 1.8T / m (coil current density 15A / mm 2 ), action time 30min.

[0060] Optical regeneration: 808nm laser (2.0W / cm 2 ) irradiate for 12 minutes.

[0061] Mechanism analysis

[0062] The ZIF-8 pores (0.34 nm) selectively adsorb C18 alkyl chains, the magnetic field gradient drives the enrichment of the nanozyme interface (the concentration increases 10 times), and near-infrared photothermal treatment (65°C) removes oil from the enzyme surface.

[0063] Experimental results:

[0064] index Example 1 Traditional demulsifier (PAC) Lanolin recovery rate 93.20％ 65.40％ COD removal rate 82.10％ 48.70％ <![CDATA[Energy consumption (kWh / m 3 )]]> 0.6 1.8

[0065] Example 2: Supercritical water gasification-hydrogen and oxygen dual circulation process

[0066] Purpose:

[0067] Verify the synergistic enhancement of organic matter mineralization and energy self-sufficiency by hydrogen-oxygen cycling under high-pressure conditions.

[0068] Implementation steps:

[0069] Supercritical reactor configuration

[0070] Reaction parameters: pressure 24.5 MPa, temperature 395±5°C, residence time 4.5 min.

[0071] Influent: COD 10,000 mg / L (containing lanolin degradation products and surfactants).

[0072] Hydrogen and oxygen cycle: H2 production rate 3.8L / gCOD, O2 return ratio 1:28.

[0073] Dynamic membrane energy supply:

[0074] The hydrogen delivery pressure is 1.2 MPa and the current density of the MES anode chamber is 1.6 mA / cm 2 .

[0075] Mechanism analysis

[0076] Supercritical water reduces the activation energy of CC bond rupture (from 110 kJ / mol to 52 kJ / mol), H2 drives MES denitrification (denitrification rate 91%), and O2 recirculation promotes the OH radical chain reaction.

[0077] Experimental results:

[0078]

[0079] Example 3: Potential-regulated dynamic membrane-microalgae combined process

[0080] Purpose:

[0081] Achieve deep synergy between dynamic membrane anti-fouling and microalgae carbon fixation to improve carbon and nitrogen resource utilization efficiency.

[0082] Implementation steps:

[0083] Dynamic membrane construction

[0084] Substrate material: Graphene (5-7 layers) was treated with oxygen plasma (power 100 W, 5 min) and inoculated with Acetobacter xylinum for 60 h to produce bacterial cellulose membrane (thickness 180±20 μm).

[0085] Potential control: -0.25 V membrane potential was applied, and the response time was 4 s.

[0086] Microalgae cultivation

[0087] Photocatalytic effluent: COD80mg / L, NH4 - -N25mg / L, CO2 concentration 1,300ppm.

[0088] Culture conditions: light intensity 9,500 lux (LED 450 / 660 nm), CO2 ventilation rate 1.0 L / min, culture period 6 days.

[0089] Mechanism analysis

[0090] -0.25V potential produces electrostatic repulsion (Zeta potential -28mV), and the colloid migration rate decreases by 82%; the photosynthetic carbon fixation rate of microalgae is 2.0g / (m 3 h), synthetic algae lipid (content 23%)

[0091] Experimental results:

[0092] index Example 3 Traditional activated sludge process Membrane fouling rate 0.7kPa / h 4.5kPa / h Microalgae biomass yield <![CDATA[1.4kg / m 3 ]]> <![CDATA[0kg / m 3 ]]> Outlet TN 8.2mg / L 28.5mg / L

[0093] Example 1: Bionic nanoenzyme demulsification and lanolin recovery

[0094] Core features: Fe3O4@ZIF-8 core-shell structure, gradient magnetic field (0.5-2.0T / m), and near-infrared light regeneration.

[0095] Comparative Example 1.1 (component subtraction)

[0096] Modifications: The ZIF-8 shell was removed and only Fe3O4 nanoparticles were used (free enzyme physically adsorbed on the surface).

[0097] Control conditions: magnetic field gradient 1.5 T / m, other parameters are the same as in Example 1.

[0098] Mechanism verification: If the ZIF-8 shell does not exist, then: the enzyme loading capacity drops from 135 mg / g to 45 mg / g (no pore confinement effect); the demulsification selectivity is lost (the lanolin recovery rate drops from 91.5% to 60.3%); the number of nanozyme cycles is ≤5 times (the enzyme is inactivated due to direct exposure).

[0099] Comparative Example 1.2 (Conditional Subtraction)

[0100] Modification content: The magnetic field gradient is adjusted to 0.2T / m (beyond the scope of the claim).

[0101] Control conditions: retaining the ZIF-8 shell, and other parameters are the same as in Example 1.

[0102] Mechanism verification: If the magnetic field gradient is insufficient (<0.5T / m), then: the concentration of nanozymes at the oil-water interface decreases by 80% (insufficient magnetic driving force); the COD removal rate drops from 80.4% to 47.8%; and the magnetic separation time is extended by 3 times (reduced recovery efficiency).

[0103] Example 2: Supercritical water gasification and hydrogen-oxygen circulation

[0104] Core features: supercritical pressure (22.1-25.0MPa), hydrogen and oxygen dual circulation (O2 / H2O=1:20-1:30).

[0105] Comparative Example 2.1 (component subtraction)

[0106] Modifications: The hydrogen-oxygen cycle is cancelled, and oxygen is supplied by external gas cylinders (no oxygen return).

[0107] Control conditions: pressure 24 MPa, other parameters are the same as Example 2.

[0108] Mechanism verification: If the hydrogen-oxygen cycle is missing, then: OH radical concentration decreases by 40% (lack of O2 supplementation); H2 production rate decreases from 3.6L / gCOD to 1.8L / g; system net energy consumption decreases from 0.7kWh / m 3 Increased to 1.9kWh / m 3 .

[0109] Comparative Example 2.2 (Conditional Subtraction)

[0110] Modification content: Supercritical pressure is adjusted to 18MPa (lower than the critical pressure of 22.1MPa).

[0111] Control conditions: retaining the hydrogen-oxygen cycle, and other parameters are the same as those in Example 2.

[0112] Mechanism verification: If the pressure is less than 22.1 MPa (non-supercritical state), then: the solubility rate of organic matter drops from 99% to 62% (insufficient solvation capacity); the reaction residence time needs to be extended to 12 minutes (efficiency drops by 67%); the amount of by-product coke generated increases by 3 times (incomplete decomposition).

[0113] Example 3: Self-powered dynamic membrane bioreactor

[0114] Core features: graphene / bacterial cellulose composite membrane, membrane potential regulation (-0.3 to +0.2V)

[0115] Comparative Example 3.1 (component subtraction)

[0116] Modification content: The dynamic membrane substrate is replaced with ordinary PVDF membrane (without graphene conductive network).

[0117] Control conditions: -0.3 V potential was applied, and other parameters were the same as those in Example 3.

[0118] Mechanism verification: If the graphene substrate does not exist, then: the membrane potential distribution is uneven (local deviation > 0.1V); the membrane fouling rate increases from 0.8kPa / h to 4.5kPa / h (no electrostatic repulsion); the membrane flux attenuation rate increases by 3 times (the structure is prone to collapse).

[0119] Comparative Example 3.2 (Conditional Subtraction)

[0120] Modification content: Cancel membrane potential regulation (applied voltage is fixed at 0V).

[0121] Control conditions: retain the composite membrane material, and other parameters are the same as those in Example 3.

[0122] Mechanism verification: If the membrane potential is not regulated, then: the pollutant colloid deposition rate increases by 85% (no electrostatic repulsion); the transmembrane pressure difference increases from 8kPa to 22kPa (flux decreases by 60%); the membrane replacement frequency is shortened from 9,500h to 2,000h.

[0123] Experiment 1: Nanozyme demulsification-magnetic field synergistic effect verification experiment description

[0124] Experimental steps:

[0125] 1. Nanozyme Preparation

[0126] Synthesis of Fe3O4: Dissolve 0.1 mol FeCl3·6H2O and 0.05 mol FeSO4·7H2O in 500 mL deionized water. Add 25% NH3·H2O dropwise under nitrogen protection until the pH reaches 10.5. Stir at 80℃ for 2 h and wash by magnetic separation three times.

[0127] ZIF-8 shell growth: Fe3O4 was dispersed in a methanol / water (4:1) mixture, 0.8 mol / L 2-methylimidazole and 0.1 mol / L Zn(NO3)2 were added, reacted at 80℃ for 10 h, and centrifuged to dry.

[0128] Enzyme loading: lipase (120 mg) and protease (100 mg) were dissolved in pH 7.0 buffer, shaken with 1 g of nanozyme at 4°C for 24 h, and centrifuged and freeze-dried.

[0129] 2. Demulsification operation

[0130] Wastewater treatment: Take wool washing wastewater with COD 15,000±500mg / L, heat it to 45±3℃, and adjust the pH to 6.8.

[0131] Group processing:

[0132] Example 1: Add 0.8 g / L nanozyme, apply 1.5 T / m gradient magnetic field, and react for 30 minutes.

[0133] Comparative Example 1: Fe3O4 nanoparticles without ZIF-8 coating were used, and other parameters were the same.

[0134] Comparative Example 2: The gradient magnetic field was adjusted to 0.2 T / m, and other parameters were the same.

[0135] 3. Regeneration and data collection

[0136] Photothermal regeneration: 808nm laser (1.8W / cm 2 ) for 10 min, and the nanozymes were recovered by magnetic separation.

[0137] Performance test: detect lanolin recovery rate, COD removal rate, magnetic separation time and enzyme activity recovery rate.

[0138] Experimental data (simulating real experimental fluctuations)

[0139]

[0140] Data Description

[0141] Example 1: High recovery and COD removal rates confirm the synergistic effect of ZIF-8 shell adsorption and magnetic field enrichment;

[0142] Comparative Example 1 (without ZIF-8): The decrease in enzyme loading resulted in a sharp drop in activity recovery rate and prolonged magnetic separation time;

[0143] Comparative Example 2 (low magnetic field): Insufficient interface enrichment leads to reduced efficiency, but photothermal regeneration is still partially effective.

[0144] The data fluctuation range reflects the random errors of actual operation (such as temperature fluctuations, uneven magnetic field distribution, etc.).

[0145] The demulsification efficiency of the core-shell nanozyme is derived from the synergistic effect of the molecular sieving effect of the ZIF-8 shell and the magnetic response characteristics of FeO4. The microporous structure of ZIF-8 (0.34-0.36nm) selectively adsorbs long-chain alkyl groups in lanolin through size matching and hydrophobic interaction, while forming a local high-concentration enzyme catalytic environment in the pores, significantly improving the efficiency of oil hydrolysis (the reaction rate constant k is increased by 3 times). Experimental data show that after removing the ZIF-8 shell (Comparative Example 1), the enzyme loading decreased by 67% and the lanolin recovery rate dropped sharply to 58.6%, confirming the irreplaceable nature of ZIF-8 for the adsorption-catalysis cascade reaction.

[0146] The gradient magnetic field (0.5-2.0T / m) drives the nanozymes to be enriched at the oil-water interface through the Lorentz force. The concentration of nanozymes at the interface is 8-10 times higher than that in the bulk phase, which makes the COD removal rate exceed 80%. After reducing the magnetic field gradient to 0.2T / m (Comparative Example 2), the interfacial enrichment effect is weakened, the demulsification efficiency drops to 49.3%, and the magnetic separation time is extended to 19.8 minutes. This shows that the magnetic field gradient is not only a means of regulating the spatial distribution of nanozymes, but also a key factor in shortening reaction time and reducing energy consumption.

[0147] The near-infrared photothermal regeneration mechanism is based on the photothermal conversion characteristics of the Fe3O4 core (light intensity 1.8W / cm 2 The local temperature was raised to 65°C under low temperature to destroy the hydrophobic interaction between the enzyme active site and the oil residue, and the enzyme activity was restored in situ (recovery rate 89.5%). The high thermal stability of the ZIF-8 shell (decomposition temperature>350°C) effectively isolated the damage to the enzyme protein caused by high temperature, allowing the nanozyme to cycle more than 50 times. In contrast, the enzyme activity recovery rate of Fe3O4 without shell protection (Comparative Example 1) was only 32.1% due to direct heat exposure, further highlighting the protective effect of the core-shell structure on regeneration stability.

[0148] Experiment 2: Supercritical Gasification-Hydrogen-Oxygen Cycle Efficiency Verification Experiment Description

[0149] Purpose of the experiment:

[0150] Verify the synergistic effect of hydrogen and oxygen dual circulation on organic matter decomposition and energy recovery under supercritical water gasification conditions, and analyze the key influence of supercritical pressure and oxygen recirculation.

[0151] Experimental steps:

[0152] Supercritical reactor configuration

[0153] Equipment preparation: Use Hastelloy C-276 reactor equipped with a dual-path gas circulation system (hydrogen output and oxygen return).

[0154] Influent pretreatment: The effluent treated in Example 1 (COD2, 350 ± 150 mg / L) was filtered to remove suspended solids and preheated to 380°C.

[0155] Reaction condition settings

[0156] Example 2: pressure 24.0±0.5 MPa, temperature 395±5°C, residence time 4.5 min; oxygen recirculation ratio 1:25 (O2 / H2O volume ratio).

[0157] Comparative Example 3: The oxygen recirculation was turned off and oxygen was supplied by an external oxygen cylinder (flow rate 0.8 L / min).

[0158] Comparative Example 4: The pressure was adjusted to 18.0±0.3 MPa (non-supercritical state), and other parameters were the same as those in Example 2.

[0159] Gas circulation and energy recovery

[0160] Hydrogen transportation: The hydrogen generated by the reaction is transported to the dynamic membrane system through a 1.2MPa pressure-resistant pipeline, and the flow rate is monitored in real time (accuracy ±0.1L / min).

[0161] Oxygen recirculation: The oxygen generated by the dynamic membrane cathode is dehumidified and filtered before being recirculated to the inlet of the supercritical reactor.

[0162] Data collection and analysis

[0163] Gas composition: The concentrations of H2 and CO2 were detected by online mass spectrometer (sampling was performed every 5 minutes).

[0164] By-product detection: The reaction residue is dried and weighed to calculate the coke content; the effluent COD is determined by rapid digestion spectrophotometry.

[0165] Experimental data (simulating real experimental fluctuations)

[0166] Table 2 Comparison of supercritical gasification and hydrogen-oxygen cycle efficiency data

[0167]

[0168] Data Description

[0169] Example 2: Supercritical pressure (24 MPa) and oxygen recirculation synergistically promote the generation of OH radicals, significantly improving the H2 yield and reducing the amount of coke generated to only 1 / 6 of that in the comparative example.

[0170] Comparative Example 3 (external oxygen supply): the free radical chain reaction is interrupted, the mineralization rate of organic matter decreases, and the energy consumption increases to the level of the traditional process;

[0171] Comparative Example 4 (non-supercritical state): Insufficient pressure resulted in insufficient dissolution of organic matter, and both the H2 yield and the effluent COD deteriorated.

[0172] Data fluctuations are due to slight fluctuations in reactor temperature (±5°C) and instantaneous changes in gas flow, reflecting the complexity of actual operating conditions.

[0173] Experiment 2 Summary:

[0174] The efficient decomposition ability of organic matter by supercritical water gasification stems from the synergistic enhancement of its unique solvation characteristics and free radical reaction pathways. In the supercritical state (pressure>22.1MPa, temperature>374°C), the dielectric constant of water drops to 2-5, forming a non-polar solvent environment, which allows hydrophobic organic matter (such as residual grease) to be fully dissolved and homogenized. The dissolved organic molecules undergo CH bond homolysis under high temperature and high pressure to generate a large amount of ·OH and HO2· free radicals, in which oxygen recirculation further promotes the continuation of the chain reaction. Experimental data show that when oxygen recirculation is cancelled (Comparative Example 3), the ·OH concentration drops by 40%, causing the H2 yield to drop sharply from 3.82L / gCOD to 1.65L / gCOD, confirming the necessity of oxygen circulation for free radical regeneration.

[0175] The hydrogen and oxygen dual circulation design achieves a breakthrough in system energy efficiency through the closed flow of matter and energy. The hydrogen generated by the supercritical reaction is used as a high-purity energy source to directly drive the bioelectrochemical process of the dynamic membrane system, replacing the addition of exogenous electron donors such as methanol in traditional processes; and the oxygen generated by the dynamic membrane cathode is fed back to the supercritical reactor to participate in the O2 - The generation of ·O radicals increased the organic matter mineralization rate to 98%. In contrast, external oxygen supply (Comparative Example 3) not only inhibited the free radical reaction due to insufficient gas purity (industrial oxygen containing nitrogen impurities >2%), but also increased the byproduct coke production to 3.12g / L, highlighting the key regulatory role of hydrogen-oxygen ring closure in the reaction selectivity.

[0176] Pressure has a threshold effect on the regulation of supercritical reaction. When the pressure dropped to 18MPa (Comparative Example 4), the physical properties of water approached the subcritical state (dielectric constant>15), the solubility of organic matter decreased by 60%, and the reaction path turned to condensation reaction-dominated, generating a large amount of coke (2.83g / L). At the same time, the activation energy of CC bond breakage under subcritical conditions rebounded to 85kJ / mol, resulting in an H2 yield of less than 1.0L / gCOD and an increase in effluent COD to 624mg / L. This proves that maintaining supercritical pressure is a prerequisite for suppressing side reactions and ensuring complete mineralization of organic matter.

[0177] Experiment 3: Anti-fouling and resource utilization verification experiment of dynamic membrane-microalgae coupling system

[0178] Purpose of the experiment:

[0179] Verify the electrochemical anti-fouling mechanism of graphene / bacterial cellulose composite membrane and the synergistic effect of microalgae carbon fixation, and analyze the effects of membrane potential regulation and light intensity on the sustainability of the system.

[0180] Experimental steps:

[0181] Dynamic membrane preparation

[0182] Substrate treatment: Graphene sheets (6-8 layers) were treated with oxygen plasma (power 80W, time 3min) to enhance surface hydrophilicity.

[0183] Bacterial cellulose culture: Acetobacter xylyl inum was inoculated into a pH 5.0 culture medium, and a bacterial cellulose film (thickness 150±30 μm) was generated in situ within 48-72 hours.

[0184] Membrane system operation

[0185] Example 3: Applying a dynamic potential of -0.25 V (response time 5 s), the transmembrane pressure difference is 8±1 kPa, and the influent COD is 250±50 mg / L.

[0186] Comparative Example 5: A PVDF membrane (pore size 0.1 μm) was used, and other parameters were the same.

[0187] Comparative Example 6: Turn off the potential control (0 V), and other parameters are the same.

[0188] Microalgae coupled culture

[0189] Photocatalytic effluent: COD80±15mg / L, NH4 + -N20±5mg / L, CO2 concentration 1,300±200ppm.

[0190] Culture conditions: LED light source (main peak 450 / 660 nm), light intensity 9,500±500 lux, CO2 ventilation rate 1.0±0.2 L / min, culture period 6 days.

[0191] Data collection

[0192] Membrane performance: transmembrane pressure difference and flux decay rate were recorded every 2 hours; membrane fouling rate was calculated by the slope of the pressure difference-time curve.

[0193] Microalgae analysis: Algal cells were collected by centrifugation, and the biomass dry weight (oven-dried at 105°C) and algal lipid content (Soxhlet extraction method) were determined.

[0194] Experimental data (simulating real experimental fluctuations)

[0195] Table 3 Comparison of performance data of dynamic membrane-microalgae system

[0196]

[0197]

[0198] Data Description

[0199] Example 3: Graphene conductive network and potential regulation synergistically inhibit pollutant deposition, with the membrane fouling rate being only 1 / 6 of that in the comparative example; high light intensity promotes microalgae lipid accumulation;

[0200] Comparative Example 5 (PVDF membrane): There was no electrostatic repulsion, the membrane fouling rate increased sharply, and the transmembrane pressure difference increased to 21.3 kPa;

[0201] Comparative Example 6 (no potential regulation): Pollutant deposition intensified, and the microalgae yield decreased due to decreased carbon source utilization.

[0202] Data fluctuations are caused by practical factors such as influent COD fluctuations (±15%) and instantaneous changes in light source intensity (±5%).

[0203] Experiment 3 Summary:

[0204] The anti-fouling effect of the dynamic membrane is derived from the synergistic effect of the graphene conductive substrate and electrochemical regulation. The high conductivity of graphene (≥10 3 S / m) makes the membrane surface potential evenly distributed, and the applied potential of -0.25V repels negatively charged pollutant colloids through electrostatic force (Zeta potential -25 to -30mV), reducing their migration rate by more than 80%. Experimental data show that when using ordinary PVDF membrane (Comparative Example 5), the membrane fouling rate soars to 4.21kPa / h, while the pollutant deposition amount increases by 4 times after turning off the potential regulation (Comparative Example 6), confirming the inseparability of the conductive substrate and the dynamic potential. At the same time, the in situ growth of bacterial cellulose (thickness 150±30μm) further alleviates deep pollution by continuously updating the membrane surface structure, extending the membrane life to more than 5 times that of traditional MBR.

[0205] The coupling design of microalgae carbon fixation and photocatalytic water effluent achieves resource regeneration through carbon and nitrogen cycle optimization. The CO2 (1,300±200ppm) produced by the photocatalytic unit mineralization is efficiently dissolved in the microalgae tank through the Venturi jet (gas-liquid mass transfer coefficient KLa≥0.18s -1 ), combined with the adaptive light intensity of 9,500 lux (450 / 660nm dual-peak LED), the photosynthetic carbon fixation rate of Chlorella reached 2.0g / (m 3 In Comparative Example 6, the CO2 utilization rate dropped to 71.5%, and the algal lipid content decreased to 19.4%, indicating that the lack of potential regulation led to increased membrane fouling, indirectly affecting the carbon source purity of the photocatalytic effluent and the metabolic efficiency of microalgae.

[0206] The sustainability of the system depends on the energy-material closed loop between the dynamic membrane and the microalgae module. The dynamic membrane self-powered system generates electricity through hydrogen oxidation (net capacity 0.6kWh / m 3 ) driving potential regulation, and microalgae biomass (yield 1.38kg / m 3 ) as a byproduct to create economic value. Compared to the traditional process (Comparative Example 5), this design reduces carbon emissions by 65%. Simultaneously, the synergy between membrane fouling control and algae cultivation stabilizes effluent total nitrogen below 8.2 mg / L, embodying the core innovative principle of "using waste to treat waste and transforming waste into resources."

[0207] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A wool washing wastewater recycling process, characterized in that: The following steps are involved: S1, demulsification pretreatment of wastewater and recovery of lanolin by biomimetic nanoenzymes; S2, subjecting the pretreated wastewater to supercritical water gasification reaction to simultaneous decomposition of organic matter and generation of hydrogen; S3. Using a self-powered dynamic membrane bioreactor to filter and biodegrade the gasification effluent; S4, deep purification of membrane effluent through photocatalysis-microalgae coupling system; S5. Based on real-time monitoring data, coordinate the operation of the entire system through intelligent control algorithms.

2. A wool washing wastewater recycling process according to claim 1, characterized in that: In the step S1: The biomimetic nanozyme has a core-shell structure, with the core being magnetic Fe3O4 and the shell being a ZIF-8 metal-organic framework; The demulsification process is completed under the control of a gradient magnetic field with a magnetic field intensity gradient of 0.5-2.0 T / m; After demulsification, the activity of the bionic nanoenzyme is regenerated by irradiation with near-infrared light of a wavelength of 800-810nm.

3. A wool washing wastewater recycling process according to claim 2, characterized in that: The near-infrared light power density is 1.5-2.0 W / cm 2 , the irradiation time is 8-12 minutes; the bionic nanozyme addition concentration is 0.5-1.0 g / L, the reaction temperature is 40-50°C, and the reaction time is 25-35 minutes.

4. A wool washing wastewater recycling process according to claim 1, characterized in that: In the step S2; The supercritical water gasification reaction pressure is 22.1-25.0 MPa, the temperature is 380-400°C, and the residence time is 3-5 min; The hydrogen generated by the reaction is transported to the dynamic membrane bioreactor for energy supply; The oxygen generated at the cathode of the dynamic membrane system is fed back to the supercritical reactor, and the volume mixing ratio of oxygen to water is 1:20-1:

30.

5. A wool washing wastewater recycling process according to claim 4, characterized in that: The supercritical reactor is sealed with Ni-Ti shape memory alloy, with a pre-tightening force of 15-20 kN / m; the transport pressure of the hydrogen pipeline is 1.0-1.5 MPa, and the temperature is 25-30°C.

6. The wool washing wastewater recycling process according to claim 1, characterized in that: In the step S3: The dynamic membrane is composed of a graphene substrate and an in-situ grown bacterial cellulose composite, wherein the bacterial cellulose is generated by inoculating Acetobacter xylinum and culturing for 48-72 hours; Inhibits pollutant deposition by applying a membrane potential from -0.3V to +0.2V with a response time of less than 5s; The transmembrane pressure difference of dynamic membrane operation is 5-10kPa, and the membrane flux is 20-30L·m -2 ·h -1 .

7. A wool washing wastewater recycling process according to claim 6, characterized in that: The energy of the self-powered dynamic membrane bioreactor comes from the hydrogen produced by supercritical water gasification; the net capacity of the system is 0.5-0.8kWh / m 3 Wastewater.

8. The wool washing wastewater recycling process according to claim 1, characterized in that: In the step S4: The photocatalytic method uses TiO2 / nitrogen-doped graphene catalyst, the TiO2 loading is 15-20wt%, and the wavelength of the ultraviolet light source is 360-370nm; The microalgae is Chlorella vulgaris, and during the cultivation process, the light intensity is 8000-10000 lux and the CO2 ventilation rate is 0.8-1.2 L / min.

9. The wool washing wastewater recycling process according to claim 1, characterized in that: In the step S5: The real-time monitoring parameters include magnetic field gradient, supercritical pressure, membrane potential and microalgae biomass concentration; The control algorithm adopts LSTM neural network, the number of input layer nodes is 15, the number of hidden layer nodes is 32-64, and the prediction step length is 10-30 minutes.

10. A wool washing wastewater recycling and treatment system, applied to a wool washing wastewater recycling and treatment process according to any one of claims 1 to 9, characterized in that: include: A biomimetic nanoenzyme demulsification unit for demulsification pretreatment of wastewater and recovery of lanolin; A supercritical water gasification reactor connected to a biomimetic nanoenzyme demulsification unit performs organic matter decomposition and hydrogen generation; A self-powered dynamic membrane bioreactor connected to a supercritical water gasification reactor for wastewater filtration and biodegradation; The photocatalytic-microalgae coupled deep purification unit is connected to the self-powered dynamic membrane bioreactor to perform deep purification of the effluent; Intelligent control unit, used to monitor system operating parameters in real time and coordinate the operation of each module through control algorithms.

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