Method for comprehensively screening eutectic solvent as extracting agent for separating dimethyl carbonate-methanol-water system

Abstract

The invention discloses a method for comprehensively screening an eutectic solvent as an extracting agent for separating a dimethyl carbonate-methanol-water system, and belongs to the field of separation and purification. The method comprises the following steps: firstly, collecting a synthesizable eutectic solvent, and calculating three pure substances in a mixture and a hydrogen bond donor and a hydrogen bond acceptor of the eutectic solvent by using quantum chemistry calculation software so as to obtain an imaginary frequency-free energy minimization structure and a cosmo file; and 2, performing preliminary prediction based on a COSMO-RS model to obtain an infinite dilution activity coefficient of the eutectic solvent, and further obtaining the selectivity and solubility of the ternary azeotropic mixture. And 3, obtaining a comprehensive evaluation index by using a TOPSIS entropy weight method to obtain the optimal eutectic solvent. According to the method, the problem that the ternary azeotropic mixture is difficult to screen is effectively solved, the calculation cost is reduced through preliminary pre-screening, and the screening accuracy is improved; the preparation process of the obtained deep-eutectic solvent is mild and green in condition, simple and convenient to operate, cheap in reaction raw materials and low in cost, azeotropy can be effectively broken, and the deep-eutectic solvent can be recycled.

Description

Technical Field

[0001] The invention belongs to the field of separation and purification, and particularly relates to a method for comprehensively screening a low eutectic solvent as an extractant for separating a ternary azeotropic mixture. Background Art

[0002] Extractive distillation is an energy-intensive separation process, and its energy consumption and production capacity are highly dependent on the choice of extractant. In recent years, effective methods for separating binary azeotropic systems have matured and achieved industrial application, and a wealth of research results have been accumulated in the field of extractant screening. These results not only provide a basis for extractant selection for mixture separation but also provide theoretical guidance for process design. However, ternary azeotropic systems present significantly greater separation challenges due to the more complex interactions between the components compared to binary systems, resulting in often unsatisfactory results in the selection of suitable extractants. For example, the dimethyl carbonate-methanol-water system is currently primarily produced industrially on a large scale through the oxidative carbonylation of methanol. However, the reactor outlet stream typically contains a ternary mixture of dimethyl carbonate, methanol, and water. Due to the binary azeotropic nature of both dimethyl carbonate and methanol, and dimethyl carbonate and water, extractive distillation is commonly used to separate and purify dimethyl carbonate. While traditional organic solvents such as aniline are widely used, their toxicity and limited selectivity are becoming increasingly prominent, necessitating the development of more efficient and environmentally friendly alternative extractants.

[0003] Deep eutectic solvents (DESs), a promising class of green solvents, have emerged as environmentally friendly alternatives to organic solvents due to their low volatility, high thermal stability, and high solubility. Deep eutectic solvents can be easily prepared by mixing and heating hydrogen bond acceptors and hydrogen bond donors in specific proportions. Their cost is significantly lower than that of ionic liquids, making them a more cost-effective alternative. By rationally designing the combination of hydrogen bond donors and hydrogen bond acceptors, deep eutectic solvents can be customized to meet industrial needs, making the development of efficient deep eutectic solvent screening methods of great significance.

[0004] Conventional methods for screening deep eutectic solvents require experimental data, which is time-consuming and labor-intensive. However, the Conductor-like Screening Model for Real Solvents (COSMO-RS), proposed by Klamt, can predict the thermodynamic properties and fluid phase equilibrium of pure liquids and liquid mixtures without experimental data by combining quantum chemical calculations with statistical thermodynamic methods. This model places solutes and solvents on an equal footing in quantum chemistry and statistical mechanics, making it widely applicable to the prediction of thermodynamic properties of substances. Furthermore, the COSMO-RS model does not require extensive experimental data and can be implemented solely through quantum chemistry software. Combining the COSMO-RS model with the TOPSIS entropy weighting method allows for the construction of a systematic, highly objective screening process, enabling the precise identification of the optimal DES. Therefore, how to screen deep eutectic solvents through computer simulations to achieve a simple, efficient, and environmentally friendly separation solution is an urgent challenge for those skilled in the art. Summary of the Invention

[0005] The object of the present invention is to provide a method for comprehensive screening of deep eutectic solvents as extractants for separating ternary azeotropic mixtures. The method provided by the present invention can significantly reduce the time and cost of screening, is more efficient, and can accurately screen and obtain deep eutectic solvent extractants with good separation effects and environmental friendliness.

[0006] In order to achieve the above object, the technical solution of the present invention is: a method for comprehensively screening a deep eutectic solvent as an extractant for separating a ternary azeotropic mixture, comprising the following steps: S1. Collect synthesizable deep eutectic solvents and calculate the hydrogen bond donors and hydrogen bond acceptors of the deep eutectic solvents using the quantum chemistry calculation software Gaussian 16 to obtain their energy-minimized structures and cosmo files without imaginary frequencies. S2. Based on the COSMO-RS model, we preliminarily predicted the infinite dilution activity coefficient of the deep eutectic solvent and further derived the selectivity and solubility of the ternary system. S3. Use the TOPSIS entropy weight method to obtain a comprehensive evaluation index, re-rank all deep eutectic solvents according to the comprehensive index, and obtain the best deep eutectic solvent.

[0007] Furthermore, in step S1, a synthesizable deep eutectic solvent is collected, and the hydrogen bond donors and hydrogen bond acceptors of the deep eutectic solvent are calculated using quantum chemical calculation software Gaussian 16 to obtain its energy-minimized structure without imaginary frequency and cosmo file, as follows: S11. Collect hydrogen bond donors and hydrogen bond acceptors of synthesizable deep eutectic solvents, construct a two-dimensional material structure using ChemDraw software, and then draw a three-dimensional material structure using Chem3D software and save it as a gjf format file; S12, using Gaussian 16 software to perform geometry optimization and frequency calculation on the gjf file obtained in step S11 to obtain its energy-minimized structure without imaginary frequency; S13. Use Gaussian 16 software to perform COSMO solvation calculation based on the structure optimized in step S12 to obtain a cosmo file.

[0008] Furthermore, in step S2, the infinite dilution activity coefficient of the deep eutectic solvent is preliminarily predicted based on the COSMO-RS model, and the selectivity and solubility of the ternary system in the deep eutectic solvent are further obtained, and the steps are as follows: S21. Use the COSMO-RS model to calculate the infinite dilution activity coefficients of substance 1 and substance 2 in the deep eutectic solvent, and further calculate the selectivity of the deep eutectic solvent for the system (substance 1-substance 2). and the solubility of substance 1 in the deep eutectic solvent ; S22. Use the COSMO-RS model to calculate the infinite dilution activity coefficients of substance 2 and substance 3 in the deep eutectic solvent, and further calculate the selectivity of the deep eutectic solvent for the system (substance 2-substance 3) and the solubility of substance 2 in the deep eutectic solvent ; S23. Use the COSMO-RS model to calculate the infinite dilution activity coefficients of substance 1 and substance 3 in the deep eutectic solvent, and further calculate the selectivity of the deep eutectic solvent for the system (substance 1-substance 3) and the solubility of substance 3 in deep eutectic solvents ; Furthermore, in step S3, a comprehensive evaluation index is obtained using the TOPSIS entropy weight method, and the deep eutectic solvents are reordered according to the size of the comprehensive index to obtain the optimal deep eutectic solvent, and the steps are as follows: S31. Based on the TOPSIS method, all selectivities and solubilities (6 indicators) are listed as an initial thermodynamic property matrix , complete the dimensionless processing of the indicators to obtain the normalized matrix , the formula is as follows:

[0009]

[0010] in, Indicates thei The first evaluation object j indicators.

[0011] S32. Determine the ideal solution and negative ideal solutions , the formula is as follows:

[0012]

[0013] S33, calculate the i The degree of closeness between an evaluation object and the ideal solution and the negative ideal solution is as follows:

[0014]

[0015] in, It is j The weight of an indicator.

[0016] S34, based on the entropy weight method to complete the distribution of the weights of various indicators, first based on the normalized matrix Calculate the probability matrix P , and then weights are assigned according to the degree of difference between each indicator and the mark value. The formula is as follows:

[0017]

[0018]

[0019]

[0020]

[0021] in, For the i The first evaluation object j The proportion of the indicator in this indicator, For the j The information entropy of the indicator, is the information utility value of the j-th indicator.

[0022] S35, calculate the i Comprehensive evaluation index of an evaluation object ,according to The evaluation results are sorted by size, and the formula is as follows:

[0023] Furthermore, in step S11, hydrogen bond donors and hydrogen bond acceptors of some synthesizable deep eutectic solvents are derived from the COSMO-RS database, and the remaining hydrogen bond donors and hydrogen bond acceptors are calculated, with 15 hydrogen bond donors and 9 hydrogen bond acceptors, which are combined to form 45 synthesizable deep eutectic solvents.

[0024] Furthermore, in step S11, the hydrogen bond acceptor for forming the deep eutectic solvent includes choline chloride, betaine, tetrabutylammonium bromide, tetrabutylammonium chloride, tetramethylammonium bromide, tetramethylammonium bromide, betaine hydrochloride, tartaric acid and methyl urea, and the hydrogen bond donor for forming the deep eutectic solvent includes methyl urea, urea, lactic acid, oxalic acid, levulinic acid, ethylene glycol, malonic acid, phenol, benzoic acid, glycerol, 1,2-butanediol, p-toluenesulfonic acid, malic acid, thiourea, 1,3-dimethyl-2-imidazolidinone, and the molar ratio of the hydrogen bond donor to the hydrogen bond acceptor is 1:1 to 1:9.

[0025] The 45 synthesizable deep eutectic solvents were combined as follows: 1ChCl:2Ur, 1ChCl:2Ur, 1ChCl:9La, 1ChCl:1OA, 1ChCl:2Lev, 1ChCl:3Lev, 1ChCl:2EG, 1ChCl:2MA, 1ChCl:1MA, 1ChCl:2Phe, 1ChCl:2OA, 1ChCl:2BA, 1ChCl:2Gly, 1ChCl:3BG, 1Bet:1PG, 1ChCl:2Lev, 1ChCl:1Ma, 1ChCl:2Tur, 1TBAB:2Lev, 1TBAB:2EG, 1TBAB:2BA , 1TBAB:2Gly, 1TMAB:2Ur, 1TMAB:2EG, 1Bet:2OA, 1Bet:1La, 1Bet:2Lev, 1Bet:3Lev, 1Bet:1EG, 1Bet:2EG, 1Bet:3EG, 1Bet:3.5PG, 1Bet:4PG, 1Bet:2Gly, 1Bet:3Gly, 1Bet:2La, 1Bet:3La, 1TBAC:2Gly, 1TBAB:2BA, 1TBAB:2OA, 1TMAC:2Ur, 1TMAC:3EG, 1BetC:4Ur, 1TC:3MTu, 1MU:2DMI.

[0026] Furthermore, in steps S12 and S13, in order to generate COSMO data, a virtual conductor environment is first created for the molecule using a continuous medium solvation model. After quantum chemical calculations are performed using density functional theory (DFT), a screening charge density called sigma (σ) is formed on the nearby conductor. The distribution of the molecular surface screening charge density is then converted into a function of the surface composition, called the molecular surface screening charge density distribution (σ-profile). The screening charge density σ is then calculated using a quantum chemical program to obtain a COSMO file. Based on this file, the infinite dilution activity coefficient is calculated using the principles of statistical thermodynamics.

[0027] Furthermore, in steps S12 and S13, the initial configuration is subjected to geometry optimization and frequency calculation using Gaussian 16 software at the B3LYP-D3 functional and def2-TZVPD basis set levels, and COSMO solvation calculations are performed based on the optimized structure using the BP86 functional and def2-TZVPD basis set.

[0028] Furthermore, in steps S21, S22 and S23, the software used is COSMOthermX. and solubility The calculation formula is as follows:

[0029]

[0030] in, and Components i and j Infinite dilution activity coefficient in deep eutectic solvents Furthermore, in steps S31 to S35, the TOPSIS entropy weight method is used to perform a final comprehensive evaluation of the performance of the deep eutectic solvent from the perspective of six thermodynamic property indicators.

[0031] Compared with the prior art, the present invention has the following beneficial effects: the present invention first collects synthesizable low eutectic solvents, and uses the quantum chemical calculation software Gaussian 16 to calculate the hydrogen bond donors and hydrogen bond acceptors of the three pure substances and the low eutectic solvent in the mixture to obtain its energy-minimized structure and cosmo file without imaginary frequency. The second step is to preliminarily predict the infinite dilution activity coefficient of the low eutectic solvent based on the COSMO-RS model, and further obtain the selectivity and solubility of the ternary azeotropic mixture. The third step is to use the TOPSIS entropy weight method to obtain a comprehensive evaluation index, and re-rank all the low eutectic solvents according to the size of the comprehensive index to obtain the best low eutectic solvent. The preparation process of the low eutectic solvent obtained by the screening method provided by the present invention is mild and green, easy to operate, and the reaction raw materials are cheap and low in cost. It can effectively break the azeotropy as an extractant for separating the ternary azeotropic mixture, and can be recycled. It is a new type of green solvent. This method effectively solves the screening difficulties of separating ternary azeotropic mixtures, while reducing the calculation cost and improving the screening accuracy through preliminary pre-screening. The deep eutectic solvent prepared by the screening method provided by the present invention features mild, green preparation conditions, simple operation, and inexpensive raw materials. As an extractant for separating ternary azeotropic mixtures, it effectively breaks the azeotrope and can be recycled, making it a novel green solvent. This method effectively addresses the screening difficulties associated with separating ternary azeotropic mixtures, while also reducing computational costs and improving screening accuracy through preliminary pre-screening. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a flow chart of a method according to an embodiment of the present invention.

[0033] Figure 2 is the surface shielding charge map of the cosmo file.

[0034] Figure 3 This is a graph showing the solubility calculation results for deep eutectic solvents.

[0035] Figure 4 This is a graph showing the selectivity calculation results for deep eutectic solvents.

[0036] Figure 5 This is a graph showing the calculation results of comprehensive indicators for the top 25 deep eutectic solvents. DETAILED DESCRIPTION

[0037] To better understand the technical solutions of the present invention, the present invention includes but is not limited to the specific embodiments described below. Similar technologies and methods should be considered within the scope of protection of the present invention. To further clarify the technical problems, technical solutions, and advantages to be solved by the present invention, the following detailed description is provided in conjunction with the accompanying drawings and specific embodiments.

[0038] It should be understood that the embodiments described herein are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work are within the scope of protection of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the art to which this application belongs.

[0039] The present invention provides a method for comprehensive screening of deep eutectic solvents as an extractant for separating ternary azeotropic mixtures. The method flow chart is as follows: Figure 1 As shown, the following steps are included: Step S1, collecting synthesizable deep eutectic solvents, and calculating hydrogen bond donors and hydrogen bond acceptors of three pure substances and the deep eutectic solvent using quantum chemical calculation software Gaussian 16 to obtain their energy-minimized structures and cosmo files without imaginary frequencies; Step S2: Preliminarily predicting the infinite dilution activity coefficient of the deep eutectic solvent based on the COSMO-RS model, and further determining the selectivity and solubility of dimethyl carbonate-methanol-water; Step S3: Using the TOPSIS entropy weight method to obtain a comprehensive evaluation index, all deep eutectic solvents are reordered according to the comprehensive index to obtain the best deep eutectic solvent.

[0040] The present invention provides a method for comprehensive screening of deep eutectic solvents as extractants for separating ternary azeotropic mixtures. The deep eutectic solvents obtained by the screening method of the present invention feature mild, green preparation conditions, simple operation, and inexpensive raw materials. As extractants for separating ternary azeotropic mixtures, they effectively break the azeotrope and are recyclable, representing a novel green solvent. This method effectively addresses the difficulty of screening for separating ternary azeotropic mixtures while simultaneously reducing computational costs and improving screening accuracy through preliminary pre-screening.

[0041] The following are specific implementation examples of the present invention.

[0042] like Figure 1 As described above, this example provides a method for comprehensive screening of deep eutectic solvents as a dimethyl carbonate-methanol-water extractant, and the specific steps are as follows: Step S1, collecting hydrogen bond donors and hydrogen bond acceptors of a synthesizable deep eutectic solvent, referring to Table 1, constructing a two-dimensional material structure based on ChemDraw software, and then drawing a three-dimensional material structure in Chem3D software, and saving it as a gjf format file; There are 15 hydrogen bond donors and 9 hydrogen bond acceptors, which can be combined to form 45 synthesizable deep eutectic solvents. As shown in Table 1, the hydrogen bond acceptors that form the deep eutectic solvents include choline chloride, betaine, tetrabutylammonium bromide, tetrabutylammonium chloride, tetramethylammonium bromide, tetramethylammonium bromide, betaine hydrochloride, tartaric acid, and methylurea. The hydrogen bond donors that form the deep eutectic solvents include, but are not limited to, methylurea, urea, lactic acid, oxalic acid, levulinic acid, ethylene glycol, malonic acid, phenol, benzoic acid, glycerol, 1,2-butanediol, p-toluenesulfonic acid, malic acid, thiourea, and 1,3-dimethyl-2-imidazolidinone. The molar ratio of hydrogen bond donors to hydrogen bond acceptors ranges from 1:1 to 1:9. The combinations formed are: 1ChCl:2Ur, 1ChCl:2Ur, 1ChCl:9La, 1ChCl:1OA, 1ChCl:2Lev, 1ChCl:3Lev, 1ChCl:2EG, 1ChCl:2MA, 1ChCl:1MA, 1ChCl:2Phe, 1ChCl:2OA, 1ChCl:2BA, 1ChCl:2Gly, 1ChCl:3BG, 1Bet:1PG, 1ChCl:2Lev, 1ChCl:1Ma, 1ChCl:2Tur, 1TBAB:2Lev, 1TBAB:2EG, 1TBAB:2BA, 1TBA B:2Gly、1TMAB:2Ur、1TMAB:2EG、1Bet:2OA、1Bet:1La、1Bet:2Lev、1Bet:3Lev、1Bet:1EG、1Bet:2EG、1Bet:3EG、1Bet:3.5PG、1Bet:4PG、1B et:2Gly, 1Bet:3Gly, 1Bet:2La, 1Bet:3La, 1TBAC:2Gly, 1TBAB:2BA, 1TBAB:2OA, 1TMAC:2Ur, 1TMAC:3EG, 1BetC:4Ur, 1TC:3MTu, 1MU:2DMI.

[0043] Table 1 Names and abbreviations of collected hydrogen bond acceptors and hydrogen bond donors

[0044] Step S2: Use Gaussian 16 software to perform geometry optimization and frequency calculation on the gjf file obtained in step S1 to obtain its energy-minimized structure without imaginary frequency. Perform solvation calculation based on the optimized structure to obtain the cosmo file (surface shielding charge diagrams of dimethyl carbonate, methanol, water, betaine and levulinic acid are shown in Figure 2). Figure 2 shown); Step S3: Using COSMO based on the COSMO-RS model therm The infinite dilution activity coefficients of dimethyl carbonate, methanol and water in deep eutectic solvents were calculated by X software. Step S4: further calculate and obtain three solubility indices ( 、 、 , the results are as follows Figure 3 shown) and 3 selectivity indicators ( 、 、 , the results are as follows Figure 4 As shown), the formula is as follows:

[0045]

[0046] in, and Components i and j Activity coefficients at infinite dilution in deep eutectic solvents.

[0047] Step S4: Calculate the first i Comprehensive evaluation index of an evaluation object ,according to Sort by size to give the evaluation results; Step S5: Based on the TOPSIS method, all selectivities and solubilities (6 indicators) are listed as an initial thermodynamic property matrix. , complete the dimensionless processing of the indicators to obtain the normalized matrix and determine the ideal solution and negative ideal solutions , the formula is as follows:

[0048]

[0049]

[0050]

[0051] in, Indicates the i The first evaluation object j indicators, It is j The weight of an indicator.

[0052] Step S6: Based on the entropy weight method, the weights of various indicators are assigned (see Table 2 for the results). Calculate the probability matrix P Then, weights are assigned based on the degree of difference between each indicator and the mark value, and the first iComprehensive evaluation index of an evaluation object , the formula is as follows:

[0053]

[0054]

[0055]

[0056]

[0057]

[0058] in, For the i The first evaluation object j The proportion of the indicator in this indicator, For the j The information entropy of the indicator, is the information utility value of the j-th indicator.

[0059] Table 2 Weight calculation results based on entropy weight method

[0060] The TOPSIS entropy weight method was used to conduct a final comprehensive evaluation of the performance of the deep eutectic solvent from the perspective of six thermodynamic property indicators, and the optimal deep eutectic solvent 1Bet:2Lev was obtained. The calculation results are as follows Figure 5 shown.

[0061] The above embodiments are only used to illustrate the present invention, and any equivalent transformations and improvements based on the technical solution of the present invention should not be excluded from the protection scope of the present invention.

Claims

1. A method for comprehensive screening of deep eutectic solvents as extractants for separating dimethyl carbonate-methanol-water systems, characterized in that: The steps include: S1. Collect synthesizable deep eutectic solvents and calculate the hydrogen bond donors and hydrogen bond acceptors of the deep eutectic solvents using the quantum chemistry calculation software Gaussian to obtain the energy-minimized structure and cosmo file without imaginary frequencies; S2. Based on the COSMO-RS model, we preliminarily predicted the infinite dilution activity coefficient of the deep eutectic solvent and further derived the selectivity and solubility of the ternary system. S3. Use the TOPSIS entropy weight method to obtain a comprehensive evaluation index related to the selectivity and solubility of dimethyl carbonate, methanol, and water. Reorder all low eutectic solvents according to the comprehensive index to obtain the best low eutectic solvent.

2. The method according to claim 1, characterized in that The step S1 includes the following sub-steps: S11. Collect hydrogen bond donors and hydrogen bond acceptors of synthesizable deep eutectic solvents, construct a two-dimensional material structure using ChemDraw software, and then draw a three-dimensional material structure using Chem3D software and save it as a gjf format file; S12, using Gaussian software to perform geometry optimization and frequency calculation on the gjf file obtained in step S11 to obtain an energy-minimized structure without imaginary frequencies; S13. Use Gaussian software to perform COSMO solvation calculation based on the structure optimized in step S12 to obtain a cosmo file.

3. The method according to claim 2, characterized in that In step S11, there are 15 hydrogen bond donors and 9 hydrogen bond acceptors, which are combined to form 45 synthesizable deep eutectic solvents.

4. The method according to claim 3, characterized in that In step S11, the hydrogen bond acceptor for forming the deep eutectic solvent includes choline chloride, betaine, tetrabutylammonium bromide, tetrabutylammonium chloride, tetramethylammonium bromide, tetramethylammonium bromide, betaine hydrochloride, tartaric acid and methyl urea, and the hydrogen bond donor for forming the deep eutectic solvent includes methyl urea, urea, lactic acid, oxalic acid, levulinic acid, ethylene glycol, malonic acid, phenol, benzoic acid, glycerol, 1,2-butanediol, p-toluenesulfonic acid, malic acid, thiourea, and 1,3-dimethyl-2-imidazolidinone, and the molar ratio of the hydrogen bond donor to the hydrogen bond acceptor is 1:1 to 1:

9.

5. The method according to claim 2, characterized in that In steps S12 and S13, in order to generate a COSMO file, a virtual conductor environment is created for the molecule using a continuous medium solvation model, and a screening charge density called sigma (σ) is formed after quantum chemical calculations are performed using density functional theory. The distribution of the molecular surface screening charge density is then converted into a function of the surface composition, called the molecular surface screening charge density distribution σ-profile. The screening charge density σ is then calculated using a quantum chemistry program to obtain the COSMO file.

6. The method according to claim 2, characterized in that In steps S12 and S13, the initial configuration is subjected to geometry optimization and frequency calculation using Gaussian software at the B3LYP-D3 functional and def2-TZVPD basis set levels, and COSMO solvation calculations are performed based on the optimized structure using the BP86 functional and def2-TZVPD basis set.

7. The method according to claim 1, characterized in that The step S2 includes the following sub-steps: S21. Use the COSMO-RS model to calculate the infinite dilution activity coefficients of substance 1 and substance 2 in the deep eutectic solvent, and further calculate the selectivity of the deep eutectic solvent for the system substance 1-substance 2. and the solubility of substance 1 in the deep eutectic solvent ; S22. Use the COSMO-RS model to calculate the infinite dilution activity coefficients of substance 2 and substance 3 in the deep eutectic solvent, and further calculate the selectivity of the deep eutectic solvent for the system substance 2-substance 3 and the solubility of substance 2 in the deep eutectic solvent ; S23. Use the COSMO-RS model to calculate the infinite dilution activity coefficients of substance 1 and substance 3 in the deep eutectic solvent, and further calculate the selectivity of the deep eutectic solvent for the system substance 1-substance 3 and the solubility of substance 3 in deep eutectic solvents .

8. The method according to claim 7, characterized in that Calculation of selectivity based on infinite dilution activity coefficients and solubility The calculation formula is as follows: ； ； in, and Components i and j Activity coefficients at infinite dilution in deep eutectic solvents.

9. The method according to claim 1, characterized in that The step S3 includes the following sub-steps: S31. Selectivity and solubility are listed as an initial thermodynamic property matrix based on the TOPSIS method. , complete the dimensionless processing of the indicators to obtain the normalized matrix , the formula is as follows: ； ； in, Indicates the i The first evaluation object j indicators; S32. Determine the ideal solution and negative ideal solutions , the formula is as follows: ； ； S33, calculate the i The degree of closeness between an evaluation object and the ideal solution and the negative ideal solution is as follows: ； ； in, It is j The weight of each indicator; S34, based on the entropy weight method to complete the distribution of the weights of various indicators, first based on the normalized matrix Calculate the probability matrix P , and then weights are assigned according to the degree of difference between each indicator and the mark value. The formula is as follows: ； ； ； ； ； in, For the i The first evaluation object j The proportion of the indicator in this indicator, For the j The information entropy of the indicator, is the information utility value of the jth indicator; S35, calculate the i Comprehensive evaluation index of an evaluation object ,according to The evaluation results are sorted by size, and the formula is as follows: 。

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