Volatile organic compound absorbent efficient screening method based on quantum computational chemistry

Abstract

The invention discloses an efficient volatile organic compound (VOCs) absorbent screening method based on quantum computational chemistry, and belongs to the field of volatile organic compound waste gas treatment. Comprising the following steps: aiming at a target volatile organic compound, calculating solvation free energy of the target volatile organic compound in a to-be-selected solvent by utilizing quantum calculation chemical software, predicting a Henry coefficient, and screening out a solvent with high absorption capacity; calculating the selectivity of the binding energy evaluation solvent to the volatile organic compounds; a dynamic absorption experiment and a desorption experiment are used for investigating the actual absorption capacity. Compared with a traditional absorbent screening method, the method has the advantages that the time and workload for screening are greatly reduced, and the loss of experimental consumables is reduced. The method has the advantages of being wide in screening range and high in accuracy by combining theory and reality, the practicability and universality of the method greatly improve the screening efficiency, the cost is reduced, and the method plays a guiding role in the related fields of absorption and treatment of volatile organic compounds.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of volatile organic compounds (VOCs) waste gas absorption treatment, and particularly relates to a volatile organic compound absorber high-efficiency screening method based on quantum chemical calculation. BACKGROUND

[0002] With the rapid development of industrialization, volatile organic compounds (VOCs) are increasingly widely used in fine chemical industry, new materials, new energy and other fields. Most VOCs have strong volatility and are extremely easy to escape into the atmosphere during production and use, which not only destroys the ozone layer and aggravates photochemical pollution, but also causes serious harm to human health, and has become an important factor restricting the sustainable development of economy and society. The commonly used VOCs recovery technologies include solvent absorption method, condensation method, membrane separation method, adsorption method, etc., among which the solvent absorption method occupies the mainstream position in industry because it is suitable for the recovery of high-concentration VOCs. However, the core bottleneck of this technology is the selection of absorbent. Although traditional organic solvents (such as white oil and dioctyl phthalate) have low cost, they have problems such as low solubility, poor selectivity and high volatility. While green solvents such as ionic liquids and deep eutectic solvents have the advantages of low volatility and strong designability, they are limited by high viscosity and high cost, and it is difficult to realize large-scale industrial application. In addition, VOCs are of various types and have large structural differences, and efficient and low-consumption absorbents need to be designed for different target volatile organic compounds, but the existing screening methods lack universality and precision, which restricts the optimization and application of absorption technology.

[0003] In recent years, the rapid development of quantum chemical calculation method provides a new way for the study of intermolecular interaction. Through advanced quantum chemical calculation software, the interaction mechanism between solvent molecules and VOCs can be accurately analyzed, and the affinity can be predicted. However, it is difficult to completely simulate the complex conditions (such as temperature, pressure, impurity interference, etc.) in the actual industrial environment by relying solely on theoretical calculation, resulting in deviations between the calculation results and experimental data. The existing technology CN109616160A discloses an absorbent screening method based on COSMO-UNIFAC thermodynamic model, which predicts the absorption performance by calculating the interaction parameters between groups. This method relies on the activity coefficient under infinite dilution conditions, and only considers the interaction between group groups, ignoring the overall solvation effect of the dissolution system, and has not been experimentally verified, so it is difficult to accurately reflect the absorption effect under actual industrial conditions. The existing technology CN117298814A proposes an absorbent screening method based on quantum chemical calculation, but the B3LYP / 6-311+G(d,p) calculation method used has limited accuracy, and the description of intermolecular interaction is insufficient, lacking quantitative analysis indicators.

[0004] Therefore, in view of the above problems, it is urgent to develop a VOCs absorbent screening method that takes into account theoretical accuracy and experimental verification. SUMMARY

[0005] The present application overcomes the deficiencies of the prior art and provides a volatile organic compound absorbent high-efficiency screening method based on quantum chemical calculation.

[0006] To achieve the above-mentioned purpose, the technical scheme adopted by the present application is as follows: a volatile organic compound absorbent high-efficiency screening method based on quantum chemical calculation, comprising:

[0007] S1, for a target volatile organic compound, select several functional group organic solvents that meet the boiling point, flash point, saturated vapor pressure and viscosity characteristics;

[0008] S2, through quantum chemical calculation software, combined with density functional theory, molecular structure optimization and frequency analysis are performed on the functional group organic solvents in S1; the optimized molecular structure is imported into the SMD solvation model to calculate the solvation free energy and Henry coefficient; the binding energy is calculated; and several functional group organic solvents with certain selectivity and solubility for the target volatile organic compound are screened out;

[0009] S3, for the functional group organic solvents screened in S2, dynamic absorption and desorption experiments are performed, and according to the actual absorption capacity, regeneration effect and cycle stability of different functional group organic solvents for the target volatile organic compound, a functional group organic solvent suitable for the target volatile organic compound is screened out.

[0010] In a preferred embodiment of the present application, in step S1, the functional group organic solvents have the characteristics of high boiling point, high flash point, low saturated vapor pressure and low viscosity. Among them, the boiling point is greater than or equal to 150 DEG C, the flash point is greater than 60 DEG C, the saturated vapor pressure is less than or equal to 150 Pa (30 DEG C), and the viscosity is less than or equal to 20 mPa·s (30 DEG C).

[0011] The functional group organic solvents include aliphatic hydrocarbons, aromatic hydrocarbons, halogenated hydrocarbons, alcohols, phenols, ethers, glycol ethers, propylene glycol ethers, ketones, acids, esters, acetals, nitrogen-containing compounds and sulfur-containing compounds.

[0012] In a preferred embodiment of the present application, in step S2, the quantum chemical calculation software is Gaussian 16 software, the density functional theory selects M06-2X in Minnesota functional, is equipped with 6-311G++ (d, p) base group, and adopts em=gd3 command dispersion correction.

[0013] In a preferred embodiment of the present application, in step S2, the structure optimization and frequency analysis include:

[0014] Constructing the initial geometric configuration of the target volatile organic matter and functional group organic solvent; selecting a calculation method based on density functional theory, and setting the calculation parameters for dispersion correction; submitting the Gaussian 16 software for structure optimization and frequency vibration analysis to ensure that the number of virtual frequencies of the optimized structure is 0.

[0015] In a preferred embodiment of the present application, in step S2, the specific method for calculating the solvation free energy, binding energy and Henry coefficient is:

[0016] In the Gaussian 16 software, using density functional theory, inputting the molecular parameters, and combining the corrected binding energy obtained by the group overlap error ( ) ;

[0017] The solvation free energy ( ) is calculated by combining the SMD solvation model;

[0018] Based on the static headspace gas phase measurement method, the liquid phase volatile organic matter concentration and the gas phase volatile organic matter concentration are measured, and the distribution coefficient is obtained, and the Henry coefficient is derived according to the distribution coefficient ; the calculation formula is: ; ;

[0019] Correlate the free energy, density, solvent molecular weight, and Henry coefficient, and the calculation formula is: ; ; ;

[0020] Among them, is the liquid phase volatile organic matter concentration, with the unit of ; is the gas phase volatile organic matter concentration, with the unit of ; is the distribution coefficient, dimensionless; is the Henry coefficient, with the unit of ; is the ideal gas constant, with the value of 8.314 ; is the temperature, with the unit of ; is the density of the solvent component, ; is the molecular weight of the solvent, ; is the solvation free energy, with the unit of .

[0021] In a preferred embodiment of the present application, in step S2, the intermolecular interaction between the volatile organic compounds and the functional group organic solvents is visually analyzed by using the wave function software Multiwfn, including AIM topological analysis and critical point electron density calculation, to verify the existence of weak interaction.

[0022] The type and intensity of the intermolecular weak interaction between the volatile organic compounds and the functional group organic solvents are identified on the isosurface of RDG=0.5 by using the Multiwfn software for reduced density gradient analysis.

[0023] In a preferred embodiment of the present application, in step S2, the Dmol3 module of Materials Studio 2017 is used to calculate the sigma-profile, representing the trend of the electrostatic distribution on the molecular surface.

[0024] In a preferred embodiment of the present application, in step S3, the dynamic absorption experiment includes:

[0025] The volatile organic compounds are generated by simulating the air flow by using a micro-injection pump method, and the temperature, concentration, flow rate and liquid-gas ratio of the volatile organic compound gas are set, the functional group organic solvent and the volatile organic compound gas are countercurrently contacted in the packed column, and the absorption efficiency of the functional group organic solvent on the volatile organic compound is calculated;

[0026] The absorption efficiency is obtained by measuring the inlet and outlet concentrations by using gas chromatography;

[0027] The packing of the packed column is theta ring packing, the height is 70 cm, the temperature in the column is 30 DEG C, and the pressure in the column is 1 bar.

[0028] In a preferred embodiment of the present application, in step S3, the desorption experiment includes:

[0029] The desorption temperature, pressure and desorption time are set, and the functional group organic solvent absorbed with the volatile organic compound is desorbed by using a rotary evaporator; the lean liquid after desorption is subjected to a dynamic absorption experiment, the cycle number is 8 times, and the absorption and desorption cycle performance of the functional group organic solvent is evaluated.

[0030] In a preferred embodiment of the present application, the functional group organic solvent is used for absorbing the volatile organic compound gas discharged by fine chemical, new material, new energy, microelectronic, packaging printing, industrial coating, coal chemical and other industrial enterprises and laboratories.

[0031] The present application solves the defects in the background art, and has the following beneficial effects:

[0032] (1) Compared with the traditional absorbent screening method, the screening time and workload are greatly reduced, and the material loss required by the experiment is reduced. The present application has the characteristics of wide screening range, high accuracy of combination of theory and practice, greatly improved screening efficiency, reduced cost, guiding role for VOCs absorption management related fields.

[0033] (2) Based on the density functional theory and SMD solvent model, the binding energy of VOCs and solvent molecules and the solvation free energy of VOCs in the solvent are calculated by quantum chemical software, without a large number of blind absorption experiments, but the target VOCs molecules to be absorbed and managed and the existing organic solvent molecules with actual use possibility are input into the quantum chemical software to screen out solvents with high solubility of VOCs molecules and solvents with strong selectivity and strong affinity for VOCs, so as to realize accurate and efficient absorption screening.

[0034] (3) According to the present application, if the calculated solvation free energy data is large enough to form a certain database, for the absorption and management of various VOCs, the appropriate absorbent can be quickly screened out, and the effect of one labor for all life is achieved, and the organic solvents with different characteristic structures can be screened out, and the influence of molecular structure on VOCs absorption is found, which has strong pertinence.

[0035] (4) The present application combines the verification of absorption experiment with reliable quantum chemical theory, and the screening of absorbent has obtained an optimal solution in theory and practical application, which not only has reliable theoretical support, but also can screen out more organic solvents suitable for practical application according to the actual absorption experiment. BRIEF DESCRIPTION OF DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the drawings needed in the embodiment or prior art description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can be obtained by those skilled in the art without creative labor;

[0037] Figure 1 It is a flow chart of a volatile organic compound absorbent efficient screening method based on quantum chemical calculation;

[0038] Figure 2 It is the bond critical point of benzene-dibutyl phthalate system and the corresponding bond radius;

[0039] Figure 3 It is the sigma-profile analysis diagram of benzene-dibutyl phthalate system;

[0040] Figure 4 RDG scatter plot of DBP-Phthalic acid system;

[0041] Figure 5 RDG = 0.5 filled color value surface plot of DBP-Phthalic acid system;

[0042] Figure 6 Absorption experimental device diagram of the present application;

[0043] Figure 7 Desorption experimental device diagram of the present application;

[0044] In the figure: 1, nitrogen cylinder; 2, micro-injection pump; 3, buffer bottle; 4, rotor flow meter; 5, packed column; 6, peristaltic pump; 7, gas chromatograph; 8, information detection; 9, low-temperature cooling water; 10, rotary evaporator; 11, circulating water vacuum pump. DETAILED DESCRIPTION

[0045] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application.

[0046] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application, but the present application can also be practiced without the other ways different from those described herein, therefore, the protection scope of the present application is not limited by the specific embodiments disclosed below.

[0047] In the following embodiments, the materials and reagents used are all from commercial purchase, without special instructions.

[0048] Embodiment 1:

[0049] The present application provides a volatile organic compound absorbent high-efficiency screening method based on quantum chemical calculation:

[0050] (1) First, determine benzene as the target VOCs, and select solvents meeting the initial selection solvent standard. Calculate the solvation free energy of benzene and the selected functional group organic solvents, and calculate the theoretical Henry coefficient, as shown in Table 1.

[0051] (2) Calculate the binding energy between benzene and each functional group organic solvent molecule, as shown in Table 2.

[0052] (3) Perform AIM topological analysis and critical point electron density calculation using Multiwfn software, as shown in Table 3, Figure 2

[0053] ​(4) The σ-profile analysis chart was calculated by using the Dmol3 module of the Materials Studio 2017 software to reflect the trend of the static distribution of the molecular surface, and the results are shown in Figure 3 .

[0054] (5) The reduced density gradient analysis (RDG) was performed by using the Multiwfn software, and the results are shown in Figure 4 and Figure 5 .

[0055] Example 2

[0056] The application provides a volatile organic compound absorber high-efficiency screening method based on quantum chemical calculation:

[0057] (1) Carbon disulfide is determined as the target VOCs, and functional group organic solvents meeting the initial selection solvent standard are selected. The solvation free energy of carbon disulfide and the selected functional group organic solvents is calculated, and the theoretical Henry coefficient is calculated, and the results are shown in Table 4.

[0058] (2) The binding energy between carbon disulfide and each functional group organic solvent molecule is calculated, and the results are shown in Table 5.

[0059] Example 3

[0060] The application provides a volatile organic compound absorber high-efficiency screening method based on quantum chemical calculation:

[0061] (1) Taking benzene as the target VOCs, the first five solvents with the smallest Henry coefficient calculated by the solvation free energy and the strongest absorption and dissolution ability at 30 DEG C are benzene-dibutyl phthalate (H = 12.60 kPa, AG sol = -16.68 kJ / mol), benzene-cyclobutane sulfone (H = 13.08 kPa, AG sol = -19.18 kJ / mol), benzene-tetraethylene glycol dimethyl ether (H = 14.16 kPa, AG sol = -16.87 kJ / mol), benzene-dibutyl adipate (H = 16.68 kPa, AG sol = -15.97 kJ / mol), and benzene-triethylene glycol butyl ether (H = 18.12 kPa, AG sol = -16.37 kJ / mol).

[0062] (2) Taking benzene as the target VOCs, the binding energy of benzene and the selected solvents is calculated, and the first five solvents with the strongest affinity and selectivity for benzene in the selected solvents are benzene-dibutyl phthalate (DE bind = -32.82 kJ / mol), benzene-ethylene glycol butyl ether acetate (DE bind= -32.39 kJ / mol), benzene-propylene carbonate (DE = -31.77 kJ / mol), benzene-cyclobutanone (DE = -30.89 kJ / mol), benzene-ethyl acetoacetate (DE = -29.51 kJ / mol). bind = -31.77 kJ / mol), benzene-cyclobutanone (DE = -30.89 kJ / mol), benzene-ethyl acetoacetate (DE = -29.51 kJ / mol). bind = -31.77 kJ / mol), benzene-cyclobutanone (DE = -30.89 kJ / mol), benzene-ethyl acetoacetate (DE = -29.51 kJ / mol). bind = -31.77 kJ / mol), benzene-cyclobutanone (DE = -30.89 kJ / mol), benzene-ethyl acetoacetate (DE = -29.51 kJ / mol).

[0063] Example 4:

[0064] The application provides a volatile organic compound absorbent high-efficiency screening method based on quantum chemical calculation:

[0065] AIM topological analysis is performed on the benzene-dibutyl phthalate system to find (3, -1) type critical points often present between two atom pairs. Six critical points of this type are calculated between benzene and dibutyl phthalate molecules, the electron density value is between 0 and 0.05, and the Laplace value of the electron density is greater than 0, so that there is a weak interaction in the system.

[0066] Example 5:

[0067] The application provides a volatile organic compound absorbent high-efficiency screening method based on quantum chemical calculation:

[0068] Sigma-profile analysis of the benzene-dibutyl phthalate system shows that the molecular surface electrostatic potential of dibutyl phthalate presents three region distributions: a hydrogen bond acceptor (HBA) region (sigma>0.0082e / A 2 ), a nonpolar region (-0.0082e / A 2 <0.0082e / A 2 ), and a weak hydrogen bond donor (HBD) region (sigma<-0.0082e / A 2 ). (C-H…O) type hydrogen bonds are formed between molecules, and the intermolecular force is mainly van der Waals attraction.

[0069] Example 6:

[0070] The application provides a volatile organic compound absorbent high-efficiency screening method based on quantum chemical calculation:

[0071] RDG is analyzed by using Multiwfn software, on the RDG=0.5 isosurface, the benzene-dibutyl phthalate system is mainly a weak interaction of van der Waals force, and there is also a steric hindrance effect in the molecular ring interior.

[0072] Example 7:

[0073] This invention provides a highly efficient screening method for volatile organic compound absorbents based on quantum computational chemistry:

[0074] (1) Taking carbon disulfide as the target VOCs, the five solvents with the lowest Henry's coefficient and the strongest absorption and dissolution capacity calculated using the solvation free energy at 30℃ are carbon disulfide-tetraethylene glycol dimethyl ether (H=19.68kPa, ΔG sol =-15.87kJ / mol), carbon disulfide-propylene carbonate (H=19.98kPa, ΔG sol =-18.21kJ / mol), carbon disulfide-sulfolane (H=21.62kPa, ΔG sol =-17.69kJ / mol), carbon disulfide-triethylene glycol butyl ether (H=27.61kPa, ΔG sol =-16.59kJ / mol), carbon disulfide-dibutyl adipate (H=27.85kPa, ΔG sol =-14.54kJ / mol).

[0075] (2) Using carbon disulfide as the target VOCs, the binding energy of benzene with the selected solvents was calculated. The top five solvents with the strongest affinity and selectivity for benzene among the selected solvents were carbon disulfide-propylene carbonate (ΔE). bind =-30.21kJ / mol), carbon disulfide-sulfolane (ΔE) bind =-29.97kJ / mol), carbon disulfide-dibutyl phthalate (ΔE) bind =-29.79kJ / mol), carbon disulfide-ethylene glycol butyl ether acetate (ΔE bind =-28.65kJ / mol), carbon disulfide-ethyl acetoacetate (ΔE) bind =-27.89kJ / mol).

[0076] Example 8:

[0077] Using benzene as the target VOC, a dynamic absorption experiment was conducted in a packed tower using solvents selected through quantum computational chemistry. For example... Figure 6 As shown, a nitrogen cylinder 1 provides the carrier gas, and a micro-injection pump 2 injects liquid benzene into a buffer bottle 3 to form a mixed gas. The mixed gas, after its flow rate is regulated by a rotor flow meter 4, enters the bottom of the packed tower 5, where it comes into countercurrent contact with the organic solvent circulating downwards, driven by a peristaltic pump 6, on the surface of the θ-ring packing. The absorbed tail gas is then analyzed by a gas chromatograph 7, and the data is processed and displayed by an information detection unit 8. The concentration of benzene is 10000 mg / m³. 3 The gas flow rate is 4 L / min and the liquid-to-gas ratio is 3 L / m³. 3, the absorption temperature is 30℃, the atmospheric pressure is 1 bar, and the packing tower height is 70 cm.

[0078] The absorption efficiencies of dibutyl phthalate, sulfolane, tetraethylene glycol dimethyl ether, dibutyl adipate, triethylene glycol butyl ether, ethyl acetoacetate, ethylene glycol butyl ether acetate, and propylene carbonate are 96.9%, 95.3%, 97.4%, 96.5%, 95.2%, 93.6%, 92.8%, and 93.1%, respectively. Among them, tetraethylene glycol dimethyl ether has the best absorption effect on benzene and is the most efficient benzene absorbent.

[0079] Example 9:

[0080] The tetraethylene glycol dimethyl ether solvent with the highest benzene absorption efficiency after the dynamic absorption experiment is used for desorption cycle experiment. As shown in Figure 7 , the saturated benzene-absorbed tetraethylene glycol dimethyl ether solvent is pre-cooled by low-temperature cooling water 9, enters the rotary evaporator 10 for vacuum distillation regeneration, and the system vacuum degree is maintained by the circulating water vacuum pump 11. The desorption temperature is 95℃, the pressure is 10 kPa, and the desorption time is 48 h. The lean liquid after desorption is re-used for dynamic absorption experiment to evaluate its absorption and desorption cycle performance. After 8 cycles, the tetraethylene glycol dimethyl ether solvent still has an absorption efficiency of 93.5% on benzene, showing good absorption and desorption cycle performance.

[0081] Example 10:

[0082] Carbon disulfide is used as the target VOCs, and the solvents selected by quantum chemical calculation are used for packing tower dynamic absorption experiment. As shown in Figure 6 , nitrogen cylinder 1 provides carrier gas, and liquid carbon disulfide is injected into buffer bottle 3 by micro-injection pump 2 to form a mixed gas; the mixed gas is adjusted by flow meter 4 and then enters the bottom of packing tower 5, where it is in countercurrent contact with the organic solvent flowing from top to bottom driven by peristaltic pump 6; the tail gas after absorption enters gas chromatograph 7 for detection, and the absorption efficiency is displayed after information detection 8 data processing. The concentration of carbon disulfide is 10000 mg / m 3 , the gas flow rate is 4 L / min, the liquid-gas ratio is 3 L / m 3 , the absorption temperature is 30℃, the atmospheric pressure is 1 bar, and the packing tower height is 70 cm.

[0083] The absorption efficiency of tetraethylene glycol dimethyl ether, propylene carbonate, sulfolane, triethylene glycol butyl ether, dibutyl adipate, dibutyl phthalate, ethylene glycol butyl ether acetate, ethyl acetoacetate, and carbon disulfide is 94.4%, 95.1%, 93.2%, 92.4%, 92.7%, 91.8%, 90.6%, and 91.2%, respectively. Among them, propylene carbonate has the best absorption effect on carbon disulfide and is the most efficient absorbent for carbon disulfide.

[0084] Example 11:

[0085] With carbon disulfide as the target VOCs, the propylene carbonate with the highest carbon disulfide absorption efficiency after the dynamic absorption experiment was subjected to a desorption cycle experiment. As shown in Figure 7 the figure, the propylene carbonate solvent saturated with carbon disulfide was pre-cooled by low-temperature cooling water 9 and then entered a rotary evaporator 10 for vacuum distillation regeneration, and the system vacuum degree was maintained by a circulating water vacuum pump 11. The desorption temperature was 95°C, the pressure was 10 kPa, and the desorption time was 48 h. The lean liquid after desorption was subjected to a dynamic absorption experiment again to evaluate the absorption and desorption cycle performance. After 8 cycles, the propylene carbonate still had an absorption efficiency of 94.1% on carbon disulfide, and had good absorption and desorption cycle performance.

[0086]

[0087]

[0088]

[0089]

[0090]

[0091] The above theory and experimental results show that the VOCs absorbent high-efficiency screening method combining quantum computational chemistry theory screening and absorption experiment verification has good adaptability and reliability. Among them, the high-efficiency absorbents suitable for recovering benzene are tetraethylene glycol dimethyl ether, dibutyl phthalate, and dibutyl adipate, and the high-efficiency absorbents suitable for recovering carbon disulfide are propylene carbonate, tetraethylene glycol dimethyl ether, and sulfolane. Therefore, for VOCs with different properties, this method can also screen high-performance solvents from many candidate solvents as the selected absorbent for VOCs.

[0092] Based on the ideal embodiments of the present application, the above description, relevant personnel can make various changes and modifications without deviating from the technical idea of the present application. The technical scope of the present application is not limited to the contents of the specification, and the technical scope must be determined according to the scope of the claims.

Claims

1. A method for efficient screening of volatile organic compounds (VOCs) absorbers based on quantum computational chemistry, characterized in that, The method comprises the following steps: S1, selecting several functional group organic solvents with certain boiling point, flash point, saturated vapor pressure and viscosity for the target volatile organic compounds; S2, performing molecular structure optimization and frequency analysis on the functional group organic solvents in S1 by quantum chemical software combined with density functional theory; introducing the optimized molecular structure into the SMD solvation model to calculate the solvation free energy and Henry coefficient; calculating the binding energy; and screening several functional group organic solvents with certain selectivity and solubility for the target volatile organic compounds; S3, performing dynamic absorption and desorption experiments on the functional group organic solvents screened in S2, and screening a functional group organic solvent suitable for the target volatile organic compounds according to the actual absorption capacity, regeneration effect and cycle stability of the functional group organic solvents for the target volatile organic compounds.

2. The screening method according to claim 1, characterized in that: In step S1, the functional group organic solvents have the characteristics of high boiling point, high flash point, low saturated vapor pressure and low viscosity. The functional group organic solvents include aliphatic hydrocarbons, aromatic hydrocarbons, halogenated hydrocarbons, alcohols, phenols, ethers, glycol ethers, propylene glycol ethers, ketones, acids, esters, acetals, nitrogen-containing compounds and sulfur-containing compounds.

3. The screening method according to claim 1, characterized in that: In step S2, the quantum chemical software is Gaussian 16 software, the density functional theory selects M06-2X in Minnesota functional, is matched with 6-311G++ (d, p) basis set, and dispersion correction is adopted by using the em=gd3 command.

4. The screening method of claim 1, wherein: In step S2, the structure optimization and frequency analysis include: building the initial geometric configuration of the target volatile organic compounds and the functional group organic solvents; selecting a calculation method based on the density functional theory, and performing dispersion correction and calculation parameter setting; submitting the Gaussian 16 software to perform structure optimization and frequency vibration analysis, and ensuring that the number of virtual frequencies of the optimized structure is 0.

5. The screening method of claim 1, wherein: In step S2, the specific method for calculating the solvation free energy, binding energy and Henry coefficient is: in the Gaussian 16 software, using the density functional theory, inputting the molecular parameters, and obtaining the corrected binding energy by combining the machine overlap error; calculating the solvation free energy by combining the SMD solvation model; Based on static headspace gas phase measurement method, the concentration of liquid phase volatile organic compounds is measured and the concentration of gas phase volatile organic compounds , and the distribution coefficient is obtained According to the distribution coefficient , the Henry coefficient is derived ; The free energy, density, solvent molecular weight, and Henry coefficient are correlated, and the calculation formula is: ; ; ; wherein, is the liquid phase volatile organic concentration in mg / L; ; is the gas phase volatile organic concentration in mg / L; ; is the partition coefficient, dimensionless; is the Henry's law coefficient in mg / L / atm; ; is the ideal gas constant with a value of 8.314 ; is the temperature in degrees Kelvin; ; is the density of the solvent component in g / mL; ; is the molecular weight of the solvent in g / mol; ; is the free energy of solvation in cal / mol; and .

6. The screening method according to claim 1, wherein, In step S2, the wave function software Multiwfn is used to visually analyze the intermolecular interaction between the volatile organic compounds and the functional group organic solvents, including AIM topological analysis and critical point electron density calculation, to verify the existence of weak interaction; using the Multiwfn software to perform reduced density gradient analysis, and identifying the type and strength of the intermolecular weak interaction between the volatile organic compounds and the functional group organic solvents on the RDG=0.5 isosurface.

7. The screening method according to claim 1, wherein In step S2, the Dmol3 module of Materials Studio2017 is used to calculate the sigma-profile to characterize the trend of molecular surface electrostatic distribution.

8. The screening method of claim 1, wherein: In step S3, the dynamic absorption experiment includes: The absorption efficiency of the functional group organic solvent to volatile organic compounds is calculated by simulating the generation of volatile organic compounds through a micro-injection pump method of mixing air flow, setting the temperature, concentration, flow rate and liquid-gas ratio of the volatile organic compound gas, and countercurrently contacting the functional group organic solvent and the volatile organic compound gas in a packed column. The absorption efficiency is obtained by measuring the inlet and outlet concentrations by gas chromatography. The packing of the packed column is θ ring packing, the height is 70 cm, the temperature in the column is 30 DEG C, and the pressure in the column is 1 bar.

9. The screening method of claim 1, wherein: In step S3, the desorption experiment includes: The desorption temperature, pressure and desorption time are set, the functional group organic solvent absorbing volatile organic compounds is desorbed by using a rotary evaporator, and the lean liquid after desorption is subjected to a dynamic absorption experiment to evaluate the absorption and desorption cycle performance of the functional group organic solvent.

10. The screening method of claim 1, wherein: The functional group organic solvent is used for absorbing volatile organic compound gas discharged by fine chemical, new material, new energy, microelectronic, packaging printing, industrial coating, coal chemical and other industrial enterprises and laboratories.

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