A method for analyzing performance of an electric field reinforced charged nanofiltration membrane separating pharmaceutical wastewater based on molecular simulation

Abstract

The application discloses a method for analyzing the performance of an electric field reinforced charged nanofiltration membrane in separating medical wastewater based on molecular simulation, which comprises the following steps: 1) establishing a medical wastewater model according to the density and composition of an actual medical wastewater system; 2) constructing a polymer structure model of the charged nanofiltration membrane and performing energy minimization and annealing operation; 3) assembling the medical wastewater model and the polymer structure model, and optimizing the structure of the assembled model; and 4) performing molecular dynamics simulation on the optimized assembled model, counting the distribution of different particles on the surface of the polymer, and performing subsequent data analysis. According to the difficulty of the particles entering the membrane, a suitable charged nanofiltration membrane material is selected to separate the medical wastewater. The application can quickly reduce the number of membrane materials for experimental investigation, screen potential excellent nanofiltration membrane materials, effectively shorten the experimental period, and provide a beneficial theoretical reference for rationally designing and selecting the charged membrane material and the group modification of the membrane surface.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of water treatment, and particularly relates to a method for analyzing the performance of an electric field reinforced charged nanofiltration membrane in separating pharmaceutical wastewater based on molecular simulation. BACKGROUND

[0002] Pharmaceutical and chemical wastewater is relatively complex in composition, high in organic solvent content, and relatively high in inorganic salt concentration. If wastewater containing a large amount of toxic drugs is directly discharged, it will not only cause serious pollution to the environment, but also may be transferred to the human body through animals and plants. At the same time, a large amount of high-value pharmaceutical molecules are contained in pharmaceutical and chemical wastewater, and the interception and recovery of the pharmaceutical molecules have great economic value. The environmental and ecological pollution problems of pharmaceutical wastewater in China are increasingly prominent. At present, the annual output of antibiotic raw materials in China exceeds 200,000 tons, and the annual discharge of antibiotic wastewater exceeds 3,500,000 tons. The commonly used chemical oxidation and biological treatment methods for treating antibiotic drugs in pharmaceutical wastewater have low cost, but the direct decomposition of the drugs will cause great waste of resources. Physical methods such as filtration, sedimentation, coagulation and adsorption technology will not degrade the antibiotics in wastewater, but the separation efficiency is low. Membrane separation technology has the advantages of strong separation capacity, low energy consumption and easy coupling, and has been widely concerned by researchers in the field of water treatment.

[0003] Electric field assisted membrane separation technology can further improve the permeation selectivity, anti-fouling and anti-membrane pollution ability. Generally speaking, the strengthening mechanism of electric field assisted membrane separation technology mainly includes three kinds, namely, electric enhanced adsorption / desorption, electric enhanced Donna effect and electrochemical oxidation-reduction reaction on the membrane surface. The electric auxiliary method not only can enhance the removal of monovalent and divalent ions and pollutants, but also can almost completely restore the lost membrane flux by electric auxiliary backwashing of the contaminated membrane.

[0004] Since the use of experimental methods cannot obtain the microcosmic motion behavior of particles on the molecular level and picosecond scale on the surface of membrane materials under different electric field intensities, which may be the key to determine the membrane separation performance and separation mechanism. With the improvement of computer simulation technology and computing power, intelligent technology assisted chemical research has become an important trend. Therefore, it is necessary to develop a theoretical prediction method to directly explore the ability of electrically assisted charged membrane in separating pharmaceutical wastewater at the microcosmic level, effectively reduce the experimental cost, significantly improve the design efficiency, and provide a beneficial theoretical reference for the rational design and selection of charged membrane materials and membrane surface group modification in the future. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application aims to provide a molecular dynamics simulation method for electric field reinforced charged membrane in separating pharmaceutical wastewater, which reveals the interaction mechanism between the membrane material and the solvent and drug molecules in the pharmaceutical wastewater, so as to evaluate the working efficiency of the charged membrane separation, and further guide the development of the membrane material.

[0006] To achieve the above object, the technical scheme of the present application is:

[0007] A method for analyzing the performance of an electric field reinforced charged nanofiltration membrane in separating pharmaceutical wastewater based on molecular simulation, comprising the following steps:

[0008] Step one: according to the density and composition of the actual pharmaceutical wastewater system, the size and composition of the simulation system are set, a pharmaceutical wastewater model for evaluating the separation performance of the charged membrane is established, and the model optimization conditions are set to reach equilibrium.

[0009] Step two: a charged nanofiltration membrane polymer structure model is constructed, and energy minimization and annealing operation are performed on the charged nanofiltration membrane polymer structure model. By adjusting the annealing cycle operation temperature and cycle number, the membrane surface structure is ensured to be neat, the internal stress of the polymer membrane is reduced, and the polymer membrane structure is closer to the real material.

[0010] Step three: the pharmaceutical wastewater model and the charged nanofiltration membrane polymer structure model are assembled to obtain a polymer-wastewater model, the polymer-wastewater model is optimized in structure, and the running conditions are set to reach the lowest energy balance state before the kinetic operation.

[0011] Step four: the polymer-wastewater model after structure optimization is simulated by molecular dynamics simulation, and after the simulation is completed, the distribution of different particles in the pharmaceutical wastewater solution on the surface of the polymer membrane under different electric field intensities is counted, the binding energy between the particles and the polymer membrane is calculated, and the difficulty of the particles entering the charged nanofiltration membrane is analyzed. According to the difficulty of the particles entering the membrane, a suitable charged nanofiltration membrane material is selected to separate the pharmaceutical wastewater.

[0012] Preferably, in step one, the optimization of the established pharmaceutical wastewater model includes geometry optimization and molecular dynamics calculation, and the optimization method (steepest descent, gradient descent method) and temperature and pressure control method are adjusted. With the increase of simulation time, the density, temperature and energy fluctuation of the system are smaller (less than 10%), and when the fitting straight line slope is close to 0, it is considered that a more reasonable structure of the pharmaceutical wastewater model is obtained.

[0013] Preferably, in step two, when constructing the charged nanofiltration membrane polymer structure model, in order to prevent excessive stacking of chain segments and piercing or coupling of benzene rings, the charged nanofiltration membrane polymer structure model is established under conditions far lower than the experimental density value of the material (generally 0.1-0.5 g / cm 3 ).

[0014] Preferably, in step three, when assembling the polymer-wastewater model, in order to eliminate the influence of the periodic boundary on the simulation results, a vacuum layer is added above the pharmaceutical wastewater solution.

[0015] Preferably, in step four, the molecular dynamics simulation adopts a non-equilibrium molecular dynamics simulation, and the polymer membrane bottom in the polymer-wastewater model is fixed during the simulation, an external electric field is applied to the polymer-wastewater model, and the ensemble is selected as NVT.

[0016] As a preferred technical solution of the present application, in step four, the binding energy between the particles in the wastewater and the polymer membrane is calculated according to formula (1).

[0017] E Interaction = E Total - (E Membrane + E Molecules ) formula (1)

[0018] Wherein, E Total is the total energy of the system containing the polymer membrane assembly and the particles being explored, E Membrane is the energy of the polymer membrane assembly without the solution layer, E Molecules is the energy of the particles being explored in the solution layer after removing the polymer membrane assembly, and E Interaction is the interaction energy.

[0019] The present application has the following beneficial effects: the molecular dynamics simulation can effectively predict the separation capacity of the electrically assisted charged membrane for the pharmaceutical wastewater, quickly judge the separation effect of a charged membrane in a short time, not only can effectively reduce the cost consumption caused by the experiment, quickly reduce the number of membrane materials for experimental investigation, screen potential excellent nanofiltration membrane materials, but also can simulate the experiment which cannot be accurately performed and completed due to equipment and material limitations, provide beneficial theoretical reference for future rational design and selection of nanofiltration membrane materials and modification of groups on the membrane surface, and shorten the research and development period. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 is the molecular dynamics simulation flowchart provided by the preferred embodiment of the present application

[0021] Figure 2 is the solution layer model structure and related particle model.

[0022] Figure 3 is the optimized and balanced (a) PAN (b) HPAN and (c) PAN 1:1 polymer membrane assembly model.

[0023] Figure 4 is the optimized and balanced (a) SPSf and (b) SPSf-Na polymer membrane assembly model.

[0024] Figure 5 is a schematic diagram of the molecular dynamics simulation of the polymer-wastewater model.

[0025] Figure 6Cefuroxime is a polymer membrane surface wastewater - Distribution intensity (a) PAN (b) HPAN (c) PAN 1:1.

[0026] Figure 7 Cefuroxime is a PAN polymer membrane module and ion binding energy E int (a) Cl - -Membrane (b) Cefuroxime - -Membrane. DETAILED DESCRIPTION

[0027] The present application is further illustrated by the following specific examples, which should be understood as merely representative and illustrative of the present application and should not be construed as limiting the scope of the present application. Any technology achieved based on the above description of the present application is included in the scope intended to be protected by the present application.

[0028] Example 1

[0029] (1) Pharmaceutical wastewater (solution layer) model construction and optimization:

[0030] H2O, Na + , Cl - , SO4 2- and Cefuroxime ions (Cefuroxime - ) were drawn using the Visualizer module of Materials Studio 2017 software, and then the 5 particles used were optimized using the DMol3 module. The structure model of the solution layer was constructed using the Amorphous Cell module, and the system included 1000 water molecules and a certain number of ions added in proportion.

[0031] After the solution layer model was constructed, the Forcite module was used to perform geometry optimization (Geometry Optimization) on the resulting amorphous cell, with the force field being COMPASS II; the model geometry optimization used the Smart Minimizer method, with the maximum number of iterations being 30000 times, so that the energy of the system reached a relative minimum value and remained stable.

[0032] After the system energy and structure reach the relative optimal value, the system is simulated by dynamic simulation. First, the system is relaxed by using NPT ensemble, the particles are given random initial velocity, the pressure is set to 1 bar, the simulation temperature is 298 K, and the relaxation process is 1 nS. The temperature controller selects Andersen, the pressure controller selects Berendsen; the Velocity Verlet integral method is used to solve the Newton motion process, the initial velocity of the atom is determined by the Boltzmann random distribution method; the calculation of van der Waals interaction adopts the Atom-based summation method. After relaxation, the system is simulated by NVT ensemble for 1 ns, the simulation step is 1 fs, and a frame is output every 5000 steps, and finally the final structure file is output.

[0033] (2) PAN polymer model construction and optimization:

[0034] The repeat unit structure model of PAN film before and after hydrolysis is established by the Visualizer module of Materials Studio software. After optimizing the repeat unit structure, the head and tail atoms are set, and the "build-polymer" function is used to construct a polymer chain with a certain number of repeat segments, and each molecular chain contains 10 repeat segments. The "Geometry Optimization" task option in the Forcite module of MS software is used to minimize the energy of the three molecular chain structures, so that the polymer molecular chain structure morphology is more consistent with the actual situation. Then the Amorphous Cell module is used to construct a polymer film component model, each unit contains 20 molecular chains, in order to prevent the phenomenon of excessive stacking of chain segments, the model is usually established under the condition of much lower than the experimental density value of the material, and the density of the initial model in this part is selected as 0.2 g / cm 3 .

[0035] After the above initial optimization, annealing operation is performed first to adjust the conformation of the polymer molecular chain and reduce the total energy of the system. The specific steps are as follows: using NPT ensemble, under 1 bar, the simulation system is slowly heated from 298 K to 700 K and then slowly cooled to 298 K, repeating 5 cycles, the total time is 2 ns. After the polymer film component model is relaxed for many times under high temperature-low temperature cycle, the internal stress of the model is released to reach the equilibrium density. Select the structure of the last frame of the annealing simulation, and perform 1 ns of dynamics simulation under NPT ensemble, the pressure is set to 1 bar, and the simulation temperature is 298 K. Then under this equilibrium density, NVT ensemble is selected, and 1 ns is simulated under the periodic boundary condition of 298 K, the time step is 1 fs, and a frame of trajectory information is output every 1000 steps.

[0036] (3) PAN film polymer-medical waste model construction and optimization:

[0037] A two-layer structure model of the PAN membrane module (polymer) and solution layer (wastewater) was constructed using the Build Layer module. To eliminate the influence of periodic boundaries on the simulation results, a layer with a thickness of [thickness value missing] was added above the solution layer. The vacuum layer. Energy minimization calculations were performed on the PAN membrane polymer-pharmaceutical wastewater model using the "Geometry Optimization" task option in the Forcite module of MS software.

[0038] (4) Molecular dynamics simulation and analysis of PAN membrane polymer-pharmaceutical wastewater model:

[0039] Using the Perl script included in Materials Studio, an electric field of intensity of 1000 kJ / m² was applied to the optimized model. and The external electric field. Due to the Cefroxime in the simulated system. - The model carries a negative charge, so the electric field direction is the negative Z-axis. To reduce simulation time and increase computational efficiency, the electric field strength applied to the model is much greater than the actual voltage. This strong electric field also helps overcome errors caused by the simulation duration. In the dynamic simulation of particle motion on the membrane surface, the lower part of the membrane module is fixed, an NVT ensemble is used, the simulation step size is 1 fs, the total simulation time is 2.5 ns, one frame is output every 1000 steps, and the last 0.5 ns is used for analysis.

[0040] Using the Forcite module in Materials Studio software, kinetic parameters can be extracted to obtain concentration distribution, energy, and state parameter information for each output frame. By statistically analyzing the distribution of different particles in the PAN polymer surface solution layer under different electric field intensities, the Donna effect is enhanced and the effect on Cefuroxime is strengthened after applying an external electric field. - The repulsion ability of ions is analyzed. By examining the binding energy between ions and the PAN polymer under different electric field strengths, it can be concluded that as the electric field strength increases, the resistance of charged ions to passing through the membrane to the other side increases. The electric field has a significant impact on ion transport in nanofiltration membranes.

[0041] Example 2

[0042] (1) Model construction and optimization of pharmaceutical wastewater (solution layer):

[0043] Use the Visualizer module of Materials Studio 2017 software to draw H2O, Na + ,Cl - SO4 2- and cefuroxime- ), and then the five kinds of particles used were optimized using the DMol3 module. The structural model of the solution layer was constructed using the Amorphous Cell module, and the system included 1000 water molecules, to which a certain amount of ions was added in proportion.

[0044] After the solution layer model was constructed, the resulting amorphous cell was subjected to geometry optimization (Geometry Optimization) using the Forcite module, and the force field was COMPASS II; the model geometry optimization used the Smart Minimizer method, with a maximum of 30000 iterations, so that the energy of the system reached a relative minimum value and remained stable.

[0045] After the energy and structure of the system reached a relative optimum value, the system was subjected to dynamic simulation. First, the system was relaxed using the NPT ensemble, and the particles were given random initial velocities, the pressure was set to 1 bar, and the simulation temperature was 298 K, and the relaxation process lasted for 1 ns. The temperature controller selected Andersen, and the pressure controller selected Berendsen; the Velocity Verlet integration method was used to solve the Newtonian motion process, and the atomic initial velocity was determined using the Boltzmann random distribution method; the calculation of van der Waals interaction used the Atom-based summation method. After relaxation, the system was subjected to 1 ns of dynamic simulation using the NVT ensemble, with a simulation step of 1 fs, and a frame was output every 5000 steps, and finally the final structure file was output.

[0046] (2) SPSf polymer model construction and optimization:

[0047] The structure model of the repeating unit of SPSf film before and after hydrolysis was established by the Visualizer module of the Materials Studio software. After optimizing the repeating unit structure, the head and tail atoms were set, and the "build-polymer" function was used to construct a polymer chain with a certain number of repeating segments, and each molecular chain contained 10 repeating segments. The "Geometry Optimization" task option in the Forcite module of the MS software was used to perform energy minimization operation on the three molecular chain structures, so that the polymer molecular chain structure morphology was more in line with the actual situation. Subsequently, the Amorphous Cell module was used to construct a polymer film component model, and each unit contained 20 molecular chains. In order to prevent excessive stacking of chain segments, the model was usually established at a value much lower than the experimental density of the material. The density of the initial model in this part was selected as 0.2 g / cm 3 .

[0048] After the initial optimization, an annealing operation is performed to adjust the conformation of the polymer molecular chains and reduce the total energy of the system. The specific steps are as follows: using the NPT ensemble, the simulation system is slowly heated from 298K to 700K at 1 bar, then slowly cooled back to 298K, repeated for 5 cycles, with a total duration of 2 ns. After multiple relaxations under high-temperature-low-temperature cycling, the polymer membrane module model releases internal stress and reaches equilibrium density. The structure of the last frame of the annealing simulation is selected, and a 1 ns dynamic simulation is performed under the NPT ensemble with a pressure of 1 bar and a simulation temperature of 298K. Then, under this equilibrium density, the NVT ensemble is used to simulate 1 ns under periodic boundary conditions at 298K, with a time step of 1 fs, outputting one frame of trajectory information every 1000 steps.

[0049] (3) Construction and optimization of SPSf membrane polymer-pharmaceutical wastewater model:

[0050] A two-layer structure model of the PAN membrane module (polymer) and solution layer (wastewater) was constructed using the Build Layer module. To eliminate the influence of periodic boundaries on the simulation results, a layer with a thickness of [thickness value missing] was added above the solution layer. The vacuum layer. Energy minimization calculations were performed on the PAN membrane polymer-pharmaceutical wastewater model using the "Geometry Optimization" task option in the Forcite module of MS software.

[0051] (4) Molecular dynamics simulation and analysis of SPSf membrane polymer-pharmaceutical wastewater model:

[0052] Using the Perl script included in Materials Studio, an electric field of intensity of 1000 kJ / m² was applied to the optimized model. and The external electric field. Due to the Cefroxime in the simulated system. - The model carries a negative charge, so the electric field direction is the negative Z-axis. To reduce simulation time and increase computational efficiency, the electric field strength applied to the model is much greater than the actual voltage. This strong electric field also helps overcome errors caused by the simulation duration. In the dynamic simulation of particle motion on the membrane surface, the lower part of the membrane module is fixed, an NVT ensemble is used, the simulation step size is 1 fs, the total simulation time is 2.5 ns, one frame is output every 1000 steps, and the last 0.5 ns is used for analysis.

[0053] The dynamic index parameters are extracted by using Forcite module in Materials Studio software, and the concentration distribution, energy and state parameter information of each output frame can be obtained. By counting the distribution of different particles in the surface solution layer of SPSf polymer under different electric field intensities, the Donna effect is strengthened and the repulsion ability to Cefuroxime - is enhanced after the external electric field is applied. By analyzing the binding energy between ions and SPSf polymer under different electric field intensities, it can be concluded that the resistance of the charged ions to enter the other side of the membrane increases with the increase of the electric field intensity. The electric field has a great influence on the ion transport of the nanofiltration membrane.

[0054] The above examples illustrate the embodiments of the present application. However, the present application is not limited to the above-mentioned embodiments, and any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for analyzing the performance of an electric field reinforced charged nanofiltration membrane for separating pharmaceutical wastewater based on molecular simulation, characterized in that, The steps are as follows: Step one: according to the actual medical wastewater system density and composition, set the size and composition of the simulation system, establish the medical wastewater model for evaluating the separation performance of the charged membrane, and set the model optimization conditions to reach equilibrium; Step two: construct a charged nanofiltration membrane polymer structure model, and perform energy minimization and annealing operation on the charged nanofiltration membrane polymer structure model; by adjusting the annealing cycle operation temperature and cycle number, the membrane surface structure is ensured to be neat, the internal stress of the polymer membrane is reduced, and the polymer membrane structure is closer to the real material; Step three: assemble the medical wastewater model and the charged nanofiltration membrane polymer structure model to obtain a polymer-wastewater model, optimize the structure of the polymer-wastewater model, and set the operating conditions to reach the energy minimum equilibrium state before kinetic operation; Step four: perform molecular dynamics simulation on the structure-optimized polymer-wastewater model, count the distribution of different particles in the medical wastewater solution on the surface of the polymer membrane under different electric field strengths after the simulation, calculate the binding energy between the particles and the polymer membrane, and analyze the difficulty of the particles entering the charged nanofiltration membrane; according to the difficulty of the particles entering the membrane, select a suitable charged nanofiltration membrane material to separate medical wastewater; The binding energy between the particles in the wastewater and the polymer membrane is calculated according to formula (1): formula (1); wherein, Etotai is the total energy of the system comprising the polymer membrane assembly and the particle of interest, Epm is the energy of the polymer membrane assembly removing the solution layer, Epi is the energy of the particle of interest in the solution layer after removing the polymer membrane assembly, Eint is the interaction energy.

2. The method for analyzing the performance of an electric field reinforced charged nanofiltration membrane in separating pharmaceutical wastewater based on molecular simulation according to claim 1, characterized in that, In step one, the established medical wastewater model is optimized including geometric optimization and molecular dynamics calculation, and the optimization method and temperature and pressure control method are adjusted; with the increase of simulation time, the density, temperature and energy fluctuation of the system are small, and when the fitting straight line slope is close to 0, it is considered that a more reasonable medical wastewater model structure is obtained.

3. The method of claim 1, wherein the method is characterized by, In step two, when constructing the charged nanofiltration membrane polymer structure model, to prevent excessive stacking of chain segments and piercing or coupling of benzene rings, the charged nanofiltration membrane polymer structure model is established under conditions much lower than the experimental density value of the material.

4. The method of claim 1, wherein the method is based on molecular simulation analysis of the performance of the electric field enhanced charged nanofiltration membrane for separating pharmaceutical wastewater. In step three, when assembling the polymer-wastewater model, to eliminate the influence of periodic boundary on the simulation results, a vacuum layer is added above the medical wastewater solution.

5. The method of claim 1, wherein the method is based on molecular simulation analysis of the performance of the electric field enhanced charged nanofiltration membrane for separating pharmaceutical wastewater. In step four, the molecular dynamics simulation adopts non-equilibrium molecular dynamics simulation, the bottom of the polymer membrane in the polymer-wastewater model is fixed during the simulation, an external electric field is applied to the polymer-wastewater model, and the ensemble is selected as NVT.

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