Method for estimating molecular weight cutoff of porous membrane by using positioning-searching-determining three-step method

Abstract

The invention provides a method for estimating the molecular weight cutoff of a porous membrane by using a positioning-searching-determining three-step method, which belongs to the field of membrane-method seawater desalination and comprises three steps of positioning, searching and determining. A fitting formula capable of preliminarily predicting the MWCO range of the to-be-tested film is obtained through theoretical modeling and a known commodity film experiment result, preliminary positioning of the to-be-tested film is achieved, and the approximate position of the to-be-tested film is determined; selecting two standard substances of which the molecular weights are close to a predicted value to carry out a rejection rate experiment, and further narrowing the MWCO range; and carrying out linear fitting based on experimental data so as to determine the MWCO value of the to-be-detected membrane. Through a mode of combining theoretical modeling and experimental verification, the evaluation period of the MWCO of the porous membrane is remarkably shortened, the types and the dosage of chemical reagents required by experiments are reduced, the test cost is reduced, quantitative regulation and control of the middle layer of the high-performance desalination membrane can be realized, and the method is suitable for large-scale popularization and application. And efficient research and development of the high-performance desalination membrane and construction of a desalination membrane knowledge base under data driving are facilitated.

Description

Technical Field

[0001] The present invention relates to the technical field of membrane-based seawater desalination, and particularly to a method for estimating the molecular weight cut-off of a porous membrane by using a three-step method of positioning-search-determination. Background Art

[0002] As a new type of membrane structure widely used in seawater desalination and wastewater treatment in recent years, the thin-film composite membrane based on the intermediate layer can optimize the structure and morphology of the desalination membrane by constructing the intermediate layer, thereby improving the separation performance of the membrane. The polyamide separation layer of the thin-film composite membrane is the key to determining the performance of the desalination membrane. However, the composite membrane is not simply a combination of the polyamide separation layer and the support layer. The formation of the polyamide separation layer depends to a great extent on the support layer. Research has shown the influence of the pore size of the support layer on the formation of the polyamide layer and the transport of water molecules, and numerous experimental studies have also confirmed the importance of the pore size of the support layer. The current commonly used methods for quantifying the pore size of porous membranes are divided into direct methods and indirect methods. The direct method is a method of directly obtaining information such as the surface morphology and pore size of the porous membrane by using large-scale measuring instruments, mainly including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and atomic force microscopy (AFM); the indirect method is a method of indirectly obtaining the equivalent pore size of the membrane by using physical phenomena related to the pore size of the porous membrane, measuring the corresponding experimental parameters through experiments, and according to the corresponding formula, mainly including the bubble point method, the molecular weight cut-off (MWCO) method, etc. However, these methods have some deficiencies in evaluating the pore size of porous membranes, such as complicated operation steps, high test costs, and high equipment investment costs. Summary of the Invention

[0003] The present invention provides a method for estimating the molecular weight cut-off of a porous membrane by using a three-step method of positioning-search-determination, which solves the above-mentioned problems. The specific steps include: a positioning step, a search step, and a determination step;

[0004] The positioning step is used to predict the numerical range of the molecular weight cut-off of the ultrafiltration membrane with the pore size to be measured;

[0005] The search step is used to select two standard substances with molecular weights close to the numerical range and measure the rejection rates of the two standard substances;

[0006] In the determination step, calculate the linear correlation between the rejection rates of the two standard substances and the molecular weight cut-off, and determine the accurate value of the molecular weight cut-off of the ultrafiltration membrane with the pore size to be measured.

[0007] In a preferred embodiment, in the positioning step, experiments are carried out on commercial ultrafiltration membranes with different pore sizes, and through polynomial fitting, the convective permeability coefficient L d , rejection rate R tThe fitting formula between the cut-off molecular weight, the convective permeability coefficient L of the ultrafiltration membrane with the pore size to be measured d , the pure water permeability coefficient A and the rejection rate R t Based on the fitting formula, calculate the predicted value of the cut-off molecular weight of the ultrafiltration membrane with the pore size to be measured.

[0008] In a preferred embodiment, in the positioning step, measure the rejection rate of the porous membrane to sodium polystyrene sulfonate, and establish the approximate correlation between the convective permeability coefficient L d and the rejection rate R t :

[0009] 1 / R t =[A(1 - Δπ / Δp)+2L d / [A(1 - Δπ / Δp)+L d (2);

[0010] Let α represent A(1 - Δπ / Δp), and equation (2) is transformed into:

[0011] R t =(α + L d ) / (α + 2L d ) (3);

[0012] Perform logarithmic operations on both sides of the equation, and equation (3) is transformed into:

[0013]

[0014] According to the Taylor series expansion, equation (4) is transformed into:

[0015]

[0016] lnR t Approximately represented by a polynomial with L d / A as a variable:

[0017]

[0018] where Δp is the transmembrane pressure difference, ΔΠ is the osmotic pressure difference, and B s is the solute permeability coefficient.

[0019] In a preferred embodiment, the specific steps to determine the approximate correlation between the cut-off molecular weight MWCO and the rejection rate R t are as follows:

[0020] Establish the relationship between the solute diameter D s and the solute rejection rate through the Gaussian error function:

[0021]

[0022] In the formula, the variable x is represented by the following formula:

[0023]

[0024] The correlation between D and the molecular weight MW is established through the Einstein formula: s and the molecular weight MW:

[0025] lnD s = lnβ + 1 / 3 lnMW (9);

[0026] where β is a parameter related to the intrinsic viscosity of the solute, and Equation (9) is simplified to:

[0027] InD s = lnγ + δlnMW (10);

[0028] where γ and δ are correlation parameters;

[0029] Substituting Equation (10) into Equation (8) gives:

[0030]

[0031] MWCO corresponds to R t = 90%, MW PSS corresponds to R t , and the following formula is obtained:

[0032]

[0033] Subtracting Equation (13) from Equation (12) gives:

[0034]

[0035] R t The polynomial related to MWCO is:

[0036]

[0037] where a i and b are correlation parameters;

[0038] Combining (6) and (15) gives the approximate correlation between the convective permeability coefficient L d , the rejection rate R t and MWCO.

[0039] In the preferred embodiment, the rejection rate R of the reference substance is calculated by the following formula: t through the following formula:

[0040]

[0041] where C pRepresents the concentration of the permeate, C f Represents the concentration of the feed solution.

[0042] In a preferred embodiment, the convective permeability coefficient L d Is calculated by the following formula:

[0043] J s = C p ΔV / A m Δt (17);

[0044] J s / C f = L d ΔP + B s (C f - C p ) / C f (18);

[0045] Wherein, J s Is the solute diffusion flux, ΔV is the permeation volume, A m Is the effective filtration area of the membrane, Δt is the permeation time, B s Is the solute permeability coefficient, and ΔP is the operating pressure.

[0046] In a preferred embodiment, the pure water permeability coefficient A is obtained by the following formula:

[0047] J w = ΔV / A m Δt (19)

[0048] J w = (A + L d )ΔP (20);

[0049] Wherein, J w Is the water flux.

[0050] In a preferred embodiment, a i And b in formula (15) vary with (lnMW) Rt＝50％ / lnMW PSS And (lnMW) Rt＝84.13％ / lnMW PSS And change.

[0051] Beneficial technical effects: The present invention explores a simple, effective and economical method to estimate the molecular weight cut-off of porous membranes, which is of great significance for improving the quantification accuracy of porous membrane pore sizes and reducing costs. The three-step method of positioning-search-determination couples the MWCO prediction method based on R t Or L d / A with the traditional MWCO measurement method, integrating the advantages of pure prediction methods and pure measurement methods, thereby improving reliability and reducing test costs. Brief Description of the Drawings

[0052] Figure 1 It is a flow diagram for determining MWCO by a three-step method;

[0053] Figure 2 In (a), it is the L d value and A value of commercial membranes with different pore sizes, and in (b), it is a list of the predicted R t value deviation of the polynomial fitting formula and the fitting parameters of the polynomial fitting formula;

[0054] Figure 3 It is a schematic diagram of the positioning-search-determination hybrid strategy;

[0055] Figure 4 It is a comparison chart of the measured and predicted values of Rt for PCM / 300, PCM / 1000, and PCM / 2000;

[0056] Figure 5 It is to predict the MWCO of PCM and compare it with the measured MWCO value by measuring L d / A and R t respectively; Detailed Embodiments

[0057] The embodiments of the present invention will be described below in conjunction with the specific embodiments of the present invention.

[0058] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following detailed description of the specific embodiments of the present invention is provided. Many specific details are set forth in the following description in order to fully understand the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0059] A method for estimating the molecular weight cut-off of a porous membrane using a three-step method of positioning-search-determination, the specific steps including positioning, searching, and determining;

[0060] The positioning: establishing a theoretical model through a mathematical formula to describe the fitting relationship between the convective permeability coefficient (L d ), rejection rate (R t ), and MWCO. Conducting experiments using commercial ultrafiltration membranes with different pore sizes, and determining an approximate fitting formula among the three through polynomial fitting. Based on this formula, substituting the measured L d , A, and R t values of the ultrafiltration membrane with the pore size to be measured, predicting the numerical range of the molecular weight cut-off of the ultrafiltration membrane with the pore size to be measured, and achieving its preliminary "positioning".

[0061] The search: According to the predicted numerical range of the molecular weight cut-off of the ultrafiltration membrane to be measured in "positioning", select two standard substances with molecular weights close to the numerical range (selected from the standard substance library). Conduct a retention rate experiment on the membrane to be measured, and measure the retention rates of the two standard substances respectively. Through the experimental data, further narrow down the numerical range of the molecular weight cut-off of the ultrafiltration membrane to be measured to achieve further "search".

[0062] The determination: According to the retention rate data obtained in "search", determine the MWCO value of the membrane to be measured through the linear correlation between the retention rates of the two standard substances and MWCO in the "search" step, so as to achieve the "determination" of the accurate value of the final MWCO.

[0063] A method for estimating the molecular weight cut-off of a porous membrane using a three-step method of positioning-search-determination, including the following steps:

[0064] S1. Positioning: Establish an approximate correlation between the convective permeability coefficient (L d ) and the retention rate (R t ), which can be obtained by measuring the retention rate of the porous membrane to sodium polystyrene sulfonate (PSS, MW = 70 kDa):

[0065] (1 - R t ) / R t = (L d Δp + B s ) / [A(Δp - ΔΠ) + L d Δp] (1);

[0066] In the formula, Δp is the transmembrane pressure difference (bar), ΔΠ is the osmotic pressure difference (bar), B s is the solute permeability coefficient (LMH), and A is the pure water permeability coefficient (LMH / bar).

[0067] Simplified to

[0068] 1 / R t = [A(1 - Δπ / Δp) + 2L d / [A(1 - Δπ / Δp) + L d (2);

[0069] Using the substitution parameter α to represent the number group A(1 - ΔΠ / Δp), formula (2) can be transformed into

[0070] R t = (α + L d ) / (α + 2L d ) (3);

[0071] Performing logarithmic operations on both sides of the equation, formula (3) can be transformed into

[0072]

[0073] According to the Taylor series expansion, Equation (4) can be transformed into

[0074]

[0075] By selecting appropriate operating pressure and feed liquid concentration, α can be approximately represented by A. Based on this, lnR t can be approximately represented by a polynomial with L d / A as the variable:

[0076]

[0077] In addition, the approximate correlation between MWCO and R t can be determined by the following formula:

[0078] The solute diameter (D s ) and the solute rejection rate can be established through the Gaussian error function:

[0079]

[0080] In the formula, the variable x can be expressed by the following formula:

[0081]

[0082] In addition, the correlation between D s and MW (molecular weight) can be established through the Einstein formula:

[0083] InD s = lnβ + 1 / 3 lnMW (9);

[0084] Among them, β is a parameter related to the intrinsic viscosity of the solute, and the intrinsic viscosity is related to MW. Therefore, lnβ can be expressed as a function of lnWM. Based on this, Equation (9) can be simplified to:

[0085] lnD s = lnγ + δ lnMW (10);

[0086] Among them, the correlation parameters γ and δ can be approximately regarded as constants. Substituting Equation (10) into Equation (8) gives:

[0087]

[0088] MWCO corresponding to R t = 90%, MW PSS corresponding to R t , the following formula can be obtained:

[0089]

[0090] Subtracting Equation (13) from Equation (12) gives:

[0091]

[0092]

[0093] Based on Equation (14), R t The polynomial related to MWCO can be described as:

[0094]

[0095] Combining (6) and (15) can obtain the approximate correlation between the convective permeability coefficient (L d ), the rejection rate (R t ) and MWCO.

[0096] The correlation parameters a i and b in Equation (15) vary with (lnMW) Rt＝50％ / lnMW PSS and (lnMW) Rt＝84.13％ / lnMW PSS . (lnMW) Rt＝50％ / lnMW PSS and (lnMW) Rt＝84.13％ / lnMW PSS are defined as the relative molecular weight, represented by β 1 and β 2 respectively, and both vary with the pore size difference of the porous membrane, but the change trend is not significant.

[0097] Using commercial ultrafiltration membranes with different pore sizes for experiments, measure their R t , MWCO and L d values (here the R t and L d values are both for selected specific reference substances, such as PSS), and determine the fitting parameters according to the fitting formula constructed above. Then, by measuring the L d , A and R t values of the membrane to be measured, according to the obtained fitting formula, preliminarily predict its MWCO range to achieve preliminary "positioning".

[0098] In a preferred embodiment, the MWCO of a commercial ultrafiltration membrane is measured using the traditional MWCO method, and the rejection rate (R t ) of the commercial membrane for standard substances with different molecular weights is calculated by the following formula:

[0099]

[0100] In this equation, C prepresents the concentration of the permeate (g / L), while C f represents the concentration of the feed solution (g / L). A rejection rate graph is made against a standard substance, and the molecular weight corresponding to 90% rejection rate on the curve represents the molecular weight retained by the sample membrane. The mathematical relationship between MWCO and R t is established by polynomial fitting between R t and lnMWCO.

[0101] In a preferred embodiment, the flux permeability coefficient (L d ) can be calculated by the following formula:

[0102] J s = C p ΔV / A m Δt (17)

[0103] J s / C f = L d ΔP + B s (C f - C p ) / C f (18)

[0104] where J s is the solute diffusion flux (gMH), ΔV is the permeate volume (L), A m is the effective filtration area of the membrane (m 2 ), Δt is the permeation time (h), B s is the solute permeability coefficient (LMH), and ΔP is the operating pressure (bar).

[0105] In a preferred embodiment, the pure water permeability coefficient A is obtained by the following formula:

[0106] J w = ΔV / A m Δt (19)

[0107] J w = (A + L d )ΔP (20)

[0108] J w is the water flux. Based on the obtained L d , substituting them into Equation (20) can obtain A.

[0109] S2. Search: According to the numerical range of the molecular weight cut-off of the ultrafiltration membrane to be measured predicted in "Positioning", select two standard substances with molecular weights close to the numerical range (selected from the standard substance library). Conduct a rejection rate experiment on the ultrafiltration membrane to be measured, and measure the rejection rates of the two standard substances respectively. Through the experimental data, further narrow the numerical range of the molecular weight cut-off of the ultrafiltration membrane to be measured to achieve further "search".

[0110] S3. Determination: According to the rejection rate data obtained in "Search", determine the MWCO value of the membrane to be measured through the linear correlation between the rejection rates of the two standard substances and MWCO in step S2, so as to achieve the "determination" of the accurate value of the final MWCO.

[0111] The present invention will be further described below through specific embodiments.

[0112] Example 1:

[0113] Select five commercial ultrafiltration membranes with nominal MWCO of 20 / 30 / 50 / 80 / 100 kDa, named CUF-1 / 2 / 3 / 4 / 5. Measure their L d and A values (as shown in Figure 2 (a)), and perform polynomial fitting on lnR t and L d / A according to Equation 6 (as shown in Table 1). After fourth-order polynomial fitting, R 2 =1, and the deviation through the fitting polynomial is less than 0.2% (as shown in Figure 2 (b)). Based on this, a mathematical expression for describing the relationship between R t and L d / A of the porous membrane is obtained.

[0114] Table 1 List of fitting parameters for polynomial fitting of LnR t and L d / A

[0115]

[0116]

[0117] After that, through the conventional method for measuring the molecular weight cut-off, measure the MWCO value of the commercial membrane (as shown in Figure 3 (a)), and perform polynomial fitting (odd order) on R t and lnMWCO according to Equation 15, as shown in Table 2. After fifth-order polynomial fitting, R 2 =1, and the deviation of predicting MWCO through the R t fitting polynomial is less than the deviation of predicting through the L d / A fitting polynomial, but the deviations of both are less than ±5% (as shown in Figure 3(as shown in (b)). In addition, the relative molecular weights β 1 and β 2 vary with the pore size of the commercial membrane as shown in Table 3. The change in relative molecular weight is not significant, ensuring that the approximate correlation between MWCO and Rt of porous membranes with different pore sizes can be fitted by a polynomial formula.

[0118] Table 2 List of fitting parameters for the polynomial fitting of R t and lnMWCO

[0119]

[0120] Table 3 Relative molecular weights β 1 and β 2 values of commercial membranes with different pore sizes

[0121]

[0122] Example 2:

[0123] A comparison graph of the measured and predicted values of Rt for PCM / 300, PCM / 1000, and PCM / 2000, which are porous composite membranes (PCM) fabricated by forming UF-level layers on a microfiltration (MF) substrate based on ZIF-8 nanoparticles of different sizes, is shown as Figure 4 shown. When R t is in the CUF (commercial membrane) membrane region (0.80 - 0.97), the predicted MWCO values of PCM / 300, PCM / 1000, and PCM / 2000 are close to the measured MWCO values. In addition, when R t is far from the CUF membrane region, the deviation between the predicted and measured MWCO becomes larger. This result indicates that it is easy to generate a rather large error when using the existing fitting equation to predict R t and the measured L d / A to obtain an approximate MWCO. Subsequently, by measuring L d / A and R t respectively to predict the MWCO of PCM and comparing it with the measured MWCO value, as shown in Figure 5 shown. The deviation between the predicted value and the measured value obtained by the latter is smaller, but when the membrane to be measured deviates significantly from the calibrated membrane, the deviation of the predicted value increases. In addition, the relative molecular weights β 1 and β 2 values of porous composite membranes with different pore sizes are shown in Table 4.

[0124] Table 4 Relative molecular weights β 1 and β 2 values of porous composite membranes with different pore sizes

[0125]

[0126]

[0127] The B value represents the dosage (ml) of the ZIF-8 nanoparticle suspension.

[0128] Example 3:

[0129] According to Example 1 and Example 2, it can be seen that it is difficult to effectively obtain an accurate MWCO solely by using the prediction method. Therefore, a three-step method of positioning-search-determination is proposed to determine the MWCO of the porous membrane (as Figure 1 shown). First, predict the MWCO value of the PCM (MWCO 1 ) according to the fitting formula. By measuring the convective permeability coefficient (L d ) of the PCM and combining the mathematical relationship between L d and MWCO established on the CUF membrane, calculate MWCO 1 . Quickly locate an approximate MWCO value to provide a general range for the subsequent search step. According to the value of MWCO 1 , select two standard substances with molecular weights located on both sides of MWCO 1 respectively. Measure the rejection rates of these two standard substances on the PCM to ensure that the measured rejection rate is equal to 90%, so as to more accurately locate the true MWCO and further narrow the range of MWCO. Based on the rejection rates and rejection molecular weights of the two standard substances measured in the search step, calculate the MWCO value (MWCO 2 ) corresponding to a 90% rejection rate by linear interpolation to determine an accurate MWCO value as the final result of the PCM pore size evaluation. Select two adjacent standard substances and calculate the corresponding rejection rates, as shown in Table 5. The MWCO 2 of PCM / 3000-0.25 is calculated to be 368.73, and its error % is -3.95%. In addition, except for PCM / 1000-0.75, the error values of MWCO 2 are not greater than 10%, indicating that the method proposed by the present invention can provide a relatively accurate MWCO value for the porous composite membrane.

[0130] Table 5 Retention molecular weights of PCM measured by the method proposed by the present invention and measurement errors

[0131]

[0132]

[0133] Explanation of Positioning: If R t,2 <90%, it indicates that the true value of MWCO is on the right side of MWPSS, and vice versa on the left side.

[0134] Err% is the MWCO 2The ratio of the difference from the MWCO true value to the true value, where the MWCO true value is obtained by measuring the rejection rates of 7 reference substances.

[0135] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can hardly think of changes or substitutions, which should be covered within the protection scope of the present invention; without conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for estimating the molecular weight cut-off of a porous membrane using a three-step method of positioning, searching and determining, characterized in that: include: Positioning step, search step, determination step; The positioning step is used to predict the numerical range of the molecular weight cut-off of the ultrafiltration membrane with the pore size to be measured; The searching step is used to select two standard substances with molecular weights close to the numerical range, and determine the retention rates of the two standard substances; The determination step calculates the linear correlation between the retention rates and the molecular weight cut-offs of the two standard substances, and determines the accurate value of the molecular weight cut-off of the ultrafiltration membrane with the pore size to be measured.

2. The method for estimating the molecular weight cut-off of a porous membrane using the three-step method of positioning-searching-determining according to claim 1, characterized in that: In the positioning step, experiments were conducted using commercial ultrafiltration membranes with different pore sizes, and the convective permeability coefficient L was obtained by polynomial fitting. d , interception rate R t The fitting formula between the molecular weight cut-off and the convective permeability coefficient L of the ultrafiltration membrane to be tested is d , pure water permeability coefficient A and retention rate R t Based on the fitting formula, the predicted value of the molecular weight cut-off of the ultrafiltration membrane with the pore size to be measured is calculated.

3. The method for estimating the molecular weight cut-off of a porous membrane using the three-step method of positioning-searching-determining according to claim 2, characterized in that: In the positioning step, the retention rate of the porous membrane for sodium polystyrene sulfonate is measured to establish the convective permeability coefficient L d and the retention rate R t Approximate correlation: 1 / R t =[A(1-ΔΠ / Δp)+2L d ] / [A(1-ΔΠ / Δp)+L d ] (2); Using α to represent A(1-Δπ / Δp), equation (2) is transformed into: R t =(α+L d ) / (α+2L d ) (3); Performing logarithmic operations on both sides of the equation, equation (3) is transformed into: According to Taylor series expansion, equation (4) is transformed into: LqCy t Use L d / A is the polynomial approximation of the variable: Among them, Δp is the transmembrane pressure difference, ΔΠ is the osmotic pressure difference, and B s is the solute permeability coefficient.

4. The method for estimating the molecular weight cut-off of a porous membrane using the three-step method of positioning-searching-determining according to claim 3, characterized in that: Determine the molecular weight cut-off MWCO and the retention rate R t The specific steps of approximate correlation are: The solute diameter D is established by the Gaussian error function. s The relationship with solute retention rate: Here, the variable x is expressed by the following formula: Establishing D through Einstein's formula s Correlation with molecular weight MW: lnD s =lnβ+1 / 3lnMW (9); Where β is a parameter related to the intrinsic viscosity of the solute, and formula (9) is simplified to: lnD s =lnγ+δlnMw (10); Among them, γ and δ are correlation parameters; Substituting formula (10) into formula (8), we get: MWCO corresponds to R t =90%,MW PSS Corresponding to R t , we get the following formula: Subtracting formula (13) from formula (12) yields: R t The polynomial related to MWCO is: Among them, a i and b are correlation parameters; Combining (6) and (15) we can get the convective permeability coefficient L d , interception rate R t Approximate correlation with MWCO.

5. The method for estimating the molecular weight cut-off of a porous membrane using the three-step method of positioning-searching-determining according to claim 4, characterized in that: The retention rate R of the standard substance t Calculated by the following formula: Among them, C p represents the concentration of the permeate, C f Indicates the concentration of the feed solution.

6. The method for estimating the molecular weight cut-off of a porous membrane using the three-step method of positioning-searching-determining according to claim 5, characterized in that: Convective permeability coefficient L d Calculated by the following formula: J s =C p ΔV / A m Δt (17); J s / C f =L d ΔP+B s (C f -C p) / C f (18); Among them, J s is the solute diffusion flux, ΔV is the permeation volume, A m is the effective filtration area of ​​the membrane, Δt is the permeation time, B s is the solute permeability coefficient, and ΔP is the operating pressure.

7. The method for estimating the molecular weight cut-off of a porous membrane using the three-step method of positioning-searching-determining according to claim 6, characterized in that: The pure water permeability coefficient A is obtained by the following formula: J w =ΔV / A m Δt (19) J w =(A+L d )ΔP (20); Among them, J w is the water flux.

8. The method for estimating the molecular weight cut-off of a porous membrane using the three-step method of positioning-searching-determining according to claim 4, characterized in that: a in formula (15) i and b as (lnMW) Rt＝50％ / lnMW PSS and (lnMW) Rt＝84.13％ / lnMW PSS And changes.

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