A method for predicting the pollutant adsorption capacity of carbon-based materials using software

Abstract

The application discloses a method for predicting the adsorption capacity of pollutants by carbon-based functional groups by using software, detects the types and contents of functional groups of biochar, constructs a biochar model according to the types and contents of the functional groups, simultaneously constructs a planar graphite model without functional groups and a pollutant molecular structure model, constructs a solid-liquid interface model, adds water molecules and organic pollutant molecules into a simulation box, optimizes the structure of the model and performs molecular dynamics simulation, obtains an equilibrium configuration, analyzes the adsorption of organic pollutants on the surface of biochar and graphite according to the trajectory file of the equilibrium configuration, and quantitatively obtains the adsorption amount of the functional groups on the pollutants in the adsorption process.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of environmental chemistry and functional new materials, and particularly relates to a method for predicting the adsorption capacity of pollutants by functional groups of carbon-based materials by using software. BACKGROUND

[0002] Organic pollutants enter the environment in large quantities during human industrial and agricultural production processes, and their toxic, carcinogenic and teratogenic effects have attracted widespread social attention. Carbon-based materials generally have a large specific surface area, strong surface hydrophobicity, good thermal and mechanical stability, strong electron-donating ability, and recycling performance, and have strong adsorption performance on organic pollutants, and can affect the reaction activity of organic pollutants. The interaction between the two largely determines the behavior and migration of organic pollutants. It has been a hot topic in environmental geology research for many years. The interaction between organic pollutants and these carbon-based materials is very complex, in addition to the apparent non-ideal behavior process, there are also problems such as multiple mechanism coexistence and complex environmental influence factors, which makes it difficult to accurately identify the interaction between carbon-based materials and organic pollutants.

[0003] In view of this problem, a large number of scholars have constructed a planar model based on the surface element composition of carbon-based materials, combined with the morphological distribution of organic pollutants and adsorption experiments, and explored the interaction between carbon-based materials and organic pollutants. It is found that the aromatic ring in the carbon-based material can provide π electrons for the adsorption of aromatic organic pollutants, the H donor group forms a hydrogen bond with the organic pollutant, and the pore structure adsorbs the organic pollutant through the pore filling effect. The simple planar model simulates the surface micro-area of the carbon-based material, which also includes the effect of functional groups, but the quantitative relationship between organic pollutants and functional groups is still lacking. In addition, when discussing the interaction mechanism, only the surface interaction mechanism is considered, which leads to misunderstanding of the identification of the interaction mechanism, and it is impossible to quantitatively identify the contribution of various adsorption mechanisms. Therefore, the lack of quantitative description between the functional groups of carbon-based materials and organic pollutants restricts the accurate prediction and control of the behavior and risk of organic pollutants.

[0004] In actual operation experiments, the functional group structure in carbon-based materials can be understood by characterization methods, but it is challenging to distinguish the adsorption capacity of functional groups to pollutants. Through macroscopic experiments and classical adsorption model analysis, the interaction between carbon-based materials and organic pollutants can be described from a macroscopic level, but the adsorption capacity of functional groups in carbon-based materials to organic pollutants cannot be quantitatively described, so there is a large deviation and inevitable misunderstanding in understanding the environmental behavior of organic pollutants. The combination of theoretical calculation (molecular dynamics) and experimental research provides a powerful research means for understanding the environmental behavior and mechanism of organic pollutants, and can play an important role. Among them, molecular dynamics (MD) simulation has the advantages of high efficiency and stability, can directly observe the adsorption behavior and statistically analyze the adsorption mechanism, and is widely concerned and applied. SUMMARY

[0005] The present application provides a method for predicting the adsorption capacity of functional groups in carbon-based materials to pollutants by software, which can quantitatively describe the adsorption capacity of functional groups in carbon-based materials to pollutants through computational simulation, and has significant significance for the preparation of porous materials and the explanation of the adsorption behavior of organic pollutants in the environment in the future.

[0006] In order to achieve the above-mentioned purpose, the technical scheme of the present application is as follows.

[0007] A method for predicting the adsorption capacity of functional groups in carbon-based materials to pollutants by software, comprising the following steps:

[0008] (1) The prepared biochar is subjected to element analysis, Fourier infrared and XPS test, and the XPSpeak41 software is used for peak separation processing to obtain the types and contents of functional groups of the biochar;

[0009] (2) According to the measured types and contents of functional groups, the Sketch tool in the Materials Studio 2017R2 software is used to construct a biochar model, and a two-dimensional graphite model without functional groups is also constructed;

[0010] (3) Select organic pollutants, use the Sketch tool in Materials Studio 2017R2 software to build the molecular structure model of the pollutant, use the Amorphous Cell Construction tool and the Build Layers tool to build the solid-liquid interface model, and add water molecules and organic pollutant molecules to the simulation box, use the Forcite module to optimize the structure of the built model, then perform molecular dynamics simulation on the optimized model to obtain the equilibrium configuration, use the Analysis tool in the Forcite module to analyze the adsorption of organic pollutants on the surface of the biochar model and the surface of graphite according to the trajectory file obtained from the equilibrium configuration, and analyze the adsorption of organic pollutants on the surface of biochar and graphite through the relative concentration distribution curve parameters, so as to quantitatively determine the adsorption capacity of functional groups to pollutants in the adsorption process, and the specific formula is as follows:

[0011] The adsorption amount of the functional group = the theoretical maximum adsorption amount of the biochar x the relative concentration distribution proportion difference x (3.75-4.15)

[0012] The theoretical maximum adsorption amount of the biochar is the amount of pollutants absorbed by the biochar; the relative concentration distribution proportion difference = the number of pollutant molecules adsorbed by the biochar model proportion - the number of pollutant molecules adsorbed by the graphite model proportion.

[0013] The preparation method of the biochar in step (1) is as follows: the chicken feather is calcined in a tube furnace, the tube furnace is heated at a rate of 10℃ / min, heated to 220℃ for 4h, then heated to 425℃ at the same heating rate for 2h, and then cooled to room temperature after the program is completed, the mixture is directly placed in a 60℃ oven for drying, the dried sample is heated to 800℃ at the same heating rate (10℃ / min) for 1h, and then cooled to room temperature after the program is completed, the whole burning process is completed in N2 atmosphere, the modified biochar is washed with deionized water until it is neutral, and then placed in a 60℃ oven for drying for standby; the graphite is purchased from Aladdin reagent network.

[0014] The pollutant in step (3) is bisphenol A, chloramphenicol or sulfamethoxazole, etc.

[0015] The size of the simulation box set in step (3) is The optimal simulation box size is The number of pollutant molecules is determined according to the concentration of the pollutant, the number of pollutant molecules = actual concentration x 0.6, and the method is suitable for quantifying pollutants with a concentration of 10-100mg / L.

[0016] The parameters for structure optimization of the constructed model in step (3) by using Forcite module are as follows: force field: COMPASS II, van der Waals interaction is calculated by Atom Based method, Coulomb interaction is calculated by Ewald method, and the system is optimized for 10000 steps by selecting Smart Minimizer method.

[0017] The parameters for molecular dynamics simulation in step (3) are as follows: NVT ensemble is selected, the temperature control method is Nose, the temperature is 298K, the time step is 1fs, the total simulation time is 2000ps, and the result is outputted in 5ps as a frame.

[0018] The present application can quantitatively describe the adsorption capacity of the functional groups of biochar to pollutants by molecular dynamics simulation of biochar and graphite and parameter analysis of the result file, which has significant meaning for accurately evaluating the environmental behavior and effect of organic pollutants. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 The two-dimensional plane model of biochar and graphite;

[0020] Figure 2 The actual adsorption amount of pollutants by biochar and graphite;

[0021] Figure 3 The relative concentration distribution diagram of biochar and graphite after molecular dynamics simulation with bisphenol A;

[0022] Figure 4 The relative concentration distribution diagram of biochar and graphite after molecular dynamics simulation with chloramphenicol molecules;

[0023] Figure 5 The relative concentration distribution diagram of biochar and graphite after molecular dynamics simulation with sulfamethoxazole molecules;

[0024] Figure 6 The radial distribution function diagram of biochar and graphite after molecular dynamics simulation with pollutant molecules. DETAILED DESCRIPTION

[0025] In order to better understand the present application, the technical solutions of the present application will be further described in detail below in combination with specific embodiments.

[0026] The porous biochar selected in the embodiment is carbonized from chicken feather, and bisphenol A, chloramphenicol and sulfamethoxazole are purchased from Aladdin.

[0027] Example 1

[0028] A method for predicting the adsorption capacity of functional groups of carbon-based materials to pollutants by using software, comprising the following steps:

[0029] (1) The prepared porous biochar is tested by XPS, and the functional group types and contents of the biochar are obtained by peak processing with XPSpeak41 software;

[0030] (2) According to the measured functional group types and contents, a biochar model is constructed using the Sketch tool in Materials Studio 2017R2 software, and a two-dimensional graphite model without functional groups is also constructed. The difference between biochar and graphite lies in that biochar contains functional groups, while graphite does not, as shown in Figure 1 Figure 1 The left is the model of biochar, Figure 1 and the right is the model of graphite;

[0031] (3) Select an organic pollutant, construct the molecular structure of the pollutant using the Sketch tool in Materials Studio 2017R2 software, construct the solid-liquid interface model using the Amorphous Cell Construction tool and Build Layers tool, and add appropriate water molecules and organic pollutant molecules to the simulation box. The size of the simulation box is set to The number of water molecules is 6000, and the number of pollutant molecules is determined according to the concentration of the pollutant, i.e. pollutant molecule number = actual concentration x 0.6. The structure of the constructed model is optimized using the Forcite module. The parameters for optimizing the structure of the constructed model using the Forcite module are as follows: force field: COMPASS II, van der Waals interaction is calculated using the Atom Based method, Coulomb interaction is calculated using the Ewald method, and the SmartMinimizer method is selected to optimize the system for 10000 steps. Then, molecular dynamics simulation is performed on the optimized model. The parameters for molecular dynamics simulation are as follows: NVT ensemble is selected, Nose method is used for temperature control, temperature is 298K, time step is 1fs, and total simulation time is 2000ps. The results are output every 5ps, and the equilibrium configuration is obtained. The adsorption of organic pollutants on the surface of biochar model and graphite is analyzed using the Analysis tool in the Forcite module, and the adsorption of organic pollutants on the surface of biochar and graphite is analyzed in detail through the relative concentration distribution curve parameters, so as to quantitatively determine the adsorption capacity of functional groups to pollutants in the adsorption process. The specific formula is as follows:

[0032] Functional group adsorption capacity = biochar theoretical maximum adsorption capacity x relative concentration distribution proportion difference x (3.75-4.15)

[0033] ​Wherein, the theoretical maximum adsorption capacity of biochar is the amount of biochar absorbing all pollutants; the relative concentration distribution ratio difference = the proportion of the number of pollutant molecules adsorbed by the biochar model (the number of adsorbed pollutant molecules / the total number of pollutant molecules) - the proportion of the number of pollutant molecules adsorbed by the graphite model (the number of adsorbed pollutant molecules / the total number of pollutant molecules).

[0034] Example 2

[0035] The preparation method of the biochar is to calcine the chicken feather in a tube furnace. The tube furnace temperature rising program is to rise to 220℃ at 10℃ / min, and then to rise to 425℃ at the same temperature rising rate for 2h. After the program is completed, it is naturally cooled, and then the mixture is directly placed in a 60℃ oven for drying. The dried sample is heated to 800℃ at the same temperature rising rate (10℃ / min) for 1h. After the program is completed and cooled to room temperature, the whole burning process is completed in N2 atmosphere. The burned biochar is washed to neutral with deionized water and placed in a 60℃ oven for drying for standby.

[0036] Example 3

[0037] Bisphenol A is selected as a model organic pollutant, and the product of example 2 is selected as biochar. 20mg of biochar and graphite are respectively added into 100mL bisphenol A solution with a concentration of 50mg / L, and oscillated in a constant temperature oscillator. The supernatant is extracted at 5min, 10min, 20min, 40min, 1h, 3h, 5h, 8h, 12h, 24h, 48h and 72h, and then filtered through a 0.45μm filter membrane. The remaining concentration of the organic pollutant in the solution is determined by high performance liquid chromatography, and the actual adsorption capacity and the theoretical maximum adsorption capacity of biochar and graphite are calculated by formula (1) and (2). It should be noted that when calculating the theoretical maximum adsorption capacity, C t =0;

[0038]

[0039]

[0040] In the formula, C0is the initial concentration of the organic pollutant, mg / L; C e is the concentration at reaction equilibrium, mg / L; C t is the concentration at time t, mg / L; V is the volume of the organic pollutant solution, L; m represents the mass of the added biochar, g; Q e is the adsorption capacity of the biochar to the pollutant at equilibrium, mg / g; Q t is the adsorption capacity of the biochar to the pollutant at time t, mg / g.

[0041] AsFigure 2 As shown, the actual adsorption amount of the biochar obtained by the above specific experiment is 246.21 mg / g, the actual adsorption amount of the graphite to bisphenol A is 60.72 mg / g, and the adsorption amount of the functional group to the pollutant is 246.21-60.72 = 185.49 mg / g.

[0042] The maximum theoretical adsorption amount calculated by formula (2) is The calculated Q max = 250 mg / g.

[0043] According to the modeling method of Example 1, the size of the simulation box set in step (3) is The number of water molecules is 6000, and the number of pollutant molecules is determined according to the concentration of the pollutant, that is, the number of pollutant molecules = actual concentration x 0.6 = 50 x 0.6 = 30, and the specific formula of the adsorption capacity of the functional group to the pollutant in the adsorption process is used to calculate the predicted value:

[0044] The adsorption amount of the functional group = the theoretical maximum adsorption amount of the biochar x the relative concentration distribution difference x (3.75-4.15)

[0045] Among them, the theoretical maximum adsorption amount of the biochar is the amount of the pollutant absorbed by the biochar; the relative concentration distribution difference = the number of pollutant molecules absorbed by the biochar model / total pollutant molecules - the number of pollutant molecules absorbed by the graphite model / total pollutant molecules.

[0046] The simulation results of the biochar and graphite are shown in the relative concentration distribution graph Figure 3 As shown, the dashed line represents the bisphenol A molecule, and it can be seen that there are two peak values, the number of bisphenol A molecules absorbed by the biochar model is about 22 by adding the peak values, and the number of bisphenol A molecules absorbed by the graphite model is about 16 by adding the peak values, and the relative concentration distribution ratio is obtained by comparing the two with the total number of pollutants, that is, the relative concentration distribution ratio = the number of pollutant molecules absorbed by the biochar model / total pollutant molecules - the number of pollutant molecules absorbed by the graphite model / total pollutant molecules, and the relative concentration distribution difference is obtained by subtracting the relative concentration ratio of the bisphenol A molecules absorbed by the graphite biochar model from the relative concentration ratio of the bisphenol A molecules absorbed by the biochar model, that is, the relative concentration distribution difference = the number of pollutant molecules absorbed by the biochar model / total pollutant molecules - the number of pollutant molecules absorbed by the graphite model / total pollutant molecules, that is, 22 / 30-16 / 30 = 6 / 30, and the predicted value of the adsorption amount of the functional group of the carbon-based material to the pollutant is calculated by the formula: the adsorption amount of the functional group = the theoretical maximum adsorption amount of the biochar x the relative concentration distribution difference x (3.75-4.15), which is 187.5-207.5 mg / g.

[0047] The actual value and the predicted value are not much different, within the error range, which shows that the method of Example 1 is feasible.

[0048] Example 4

[0049] Chloramphenicol was selected as a model organic pollutant, and the product of Example 2 was selected as the biochar. 20 mg of biochar and graphite were weighed and added to 100 mL of chloramphenicol solution with a concentration of 50 mg / L, respectively, and oscillated in a constant temperature oscillator. The supernatant was drawn at 5 min, 10 min, 20 min, 40 min, 1 h, 3 h, 5 h, 8 h, 12 h, 24 h, 48 h, and 72 h, respectively, and filtered through a 0.45 μm filter. The remaining concentration of the organic pollutant in the solution was determined by high performance liquid chromatography. The actual adsorption capacity and the theoretical maximum adsorption capacity of biochar and graphite were calculated according to Formulas (1) and (2) in Example 3. It should be noted that when calculating the theoretical maximum adsorption capacity, C t = 0.

[0050] As shown in Figure 2 , the actual adsorption capacity of biochar for chloramphenicol obtained by the above specific experiment is 216.31 mg / g, and the actual adsorption capacity of graphite for chloramphenicol is 50.89 mg / g. The adsorption capacity of functional groups for pollutants is 216.31-50.89 = 165.42 mg / g.

[0051] The maximum theoretical adsorption capacity calculated by Formula (2) is The calculated Q max = 250 mg / g.

[0052] According to the method of Example 1, the size of the simulation box set in step (3) is 6000 water molecules, and the number of pollutant molecules is determined according to the concentration of the pollutant. The number of pollutant molecules = actual concentration x 0.6 = 50 x 0.6 = 30, and the calculation of the predicted value is carried out according to the specific formula of the adsorption capacity of functional groups for pollutants in the adsorption process:

[0053] The adsorption capacity of functional groups = the theoretical maximum adsorption capacity of biochar x relative concentration distribution ratio difference x (3.75-4.15)

[0054] The theoretical maximum adsorption capacity of biochar is the amount of pollutants absorbed by biochar; the relative concentration distribution ratio difference = the number of pollutant molecules absorbed by the biochar model / the number of pollutant molecules absorbed by the graphite model.

[0055] The relative concentration distribution diagram obtained by the simulation results of biochar and graphite is as follows: Figure 4As shown in the figure, the dotted line represents the chloramphenicol molecule, and it can be seen that there are two peaks, the number of chloramphenicol molecules adsorbed by the biochar model is about 18 by adding the peaks, and the number of chloramphenicol molecules adsorbed by the graphite model is about 13 by adding the peaks, and the relative concentration distribution ratio is compared with the total pollutant number, that is, the relative concentration distribution ratio of chloramphenicol molecules adsorbed by the biochar model minus the relative concentration distribution ratio of chloramphenicol molecules adsorbed by the graphite biochar model can obtain the relative concentration distribution difference, that is, the relative concentration distribution ratio difference = the number of pollutant molecules adsorbed by the biochar model (18 / 30) - the number of pollutant molecules adsorbed by the graphite model (13 / 30), that is, 18 / 30-13 / 30 = 5 / 30, by the formula: the adsorption amount of functional groups = the theoretical maximum adsorption amount of biochar × the relative concentration distribution ratio difference × (3.75-4.15), it is calculated that the adsorption amount of carbon-based material functional groups to pollutants is 156.25-172.92 mg / g.

[0056] The actual value is within the range of the predicted value, indicating that the method of example 1 is feasible.

[0057] Example 5

[0058] Select sulfamethoxazole as a model organic pollutant, and select the product of example 2 as biochar. 20 mg of biochar and graphite are weighed and added to 100 mL of sulfamethoxazole solution with a concentration of 50 mg / L, respectively, in a constant temperature oscillator. The supernatant is extracted at 5 min, 10 min, 20 min, 40 min, 1 h, 3 h, 5 h, 8 h, 12 h, 24 h, 48 h, and 72 h, respectively, and filtered through a 0.45 μm filter. The remaining concentration of the remaining organic pollutants in the solution is determined by high performance liquid chromatography. The actual adsorption amount and the theoretical maximum adsorption amount of biochar and graphite are calculated according to formulas (1) and (2) in example 3. It should be noted that when calculating the theoretical maximum adsorption amount, C t = 0.

[0059] As Figure 2 shown, the actual adsorption amount of biochar to sulfamethoxazole obtained by the above specific experiment is 206.52 mg / g, the actual adsorption amount of graphite to sulfamethoxazole is 42.52 mg / g, and the adsorption amount of functional groups to pollutants is 206.52-42.52 = 164 mg / g.

[0060] The maximum theoretical adsorption amount is calculated by formula (2) as The Q max = 250 mg / g.

[0061] Modeling is carried out according to the method of example 1, and the size of the simulation box set in step (3) is The number of water molecules is 6000, and the number of pollutant molecules is determined according to the concentration of the pollutant, that is, the number of pollutant molecules = actual concentration x 0.6 = 50 x 0.6 = 30, and the calculation of the predicted value is carried out according to the specific formula of the adsorption capacity of the functional group to the pollutant in the adsorption process finally obtained in Example 1:

[0062] The adsorption amount of the functional group = the theoretical maximum adsorption amount of the biochar x the relative concentration distribution proportion difference x (3.75-4.15)

[0063] The theoretical maximum adsorption amount of the biochar is the amount of the pollutant adsorbed by the biochar; the relative concentration distribution proportion difference = the proportion of the number of pollutant molecules adsorbed by the biochar model to the proportion of the number of pollutant molecules adsorbed by the graphite model.

[0064] The relative concentration distribution diagram obtained by the simulation of the biochar and the graphite is shown in Figure 5 The dotted line represents the sulfamethoxazole molecule, and it can be seen that there are two peak values, the number of sulfamethoxazole molecules adsorbed by the biochar model is about 16 by adding the peak values, and the number of sulfamethoxazole molecules adsorbed by the graphite model is about 11 by adding the peak values, and the relative concentration distribution proportion is obtained by comparing the two with the total number of pollutants, that is, the relative concentration distribution proportion difference = the proportion of the number of pollutant molecules adsorbed by the biochar model (16 / 30) to the proportion of the number of pollutant molecules adsorbed by the graphite model (11 / 30), that is, 16 / 30-11 / 30 = 5 / 30, and the adsorption amount of the pollutant by the functional group of the carbon-based material is calculated according to the formula: the adsorption amount of the functional group = the theoretical maximum adsorption amount of the biochar x the relative concentration distribution proportion difference x (3.75-4.15), which is 156.25-172.92 mg / g.

[0065] The actual value is within the range of the predicted value, which indicates that the method of Example 1 is feasible.

[0066] Example 6

[0067] The modeling is carried out according to the method of Example 1, and the size of the simulation box set in step (3) is The number of water molecules is 6000, and the number of pollutant molecules is determined according to the concentration of the pollutant, that is, the number of pollutant molecules = actual concentration x 0.6 = 50 x 0.6 = 30, and the molecular dynamics simulation is carried out according to the parameters in step (3), and the radial distribution function is analyzed according to the final result file, Figure 6The radial distribution function diagram of the molecular dynamics simulation of the biochar and graphite and the pollutant molecules, the peak value of the radial distribution function of the three pollutants on the biochar and graphite model is: bisphenol A>chloramphenicol>sulfamethoxazole, which indicates that the adsorption amount of the three pollutants on the biochar and graphite model is: bisphenol A>chloramphenicol>sulfamethoxazole.

[0068] The results are consistent with the actual experimental values and the trend of the estimated values, and also prove that the method of example 1 is feasible.

[0069] Due to the limitation of software, the method of the application is only suitable for quantifying pollutants with a concentration of 10-100 mg / L, and the method of the above examples is verified, which can prove that it is feasible to predict the adsorption capacity of the functional groups of the carbon-based material to the pollutants by using the method of example 1.

[0070] The above examples are preferred embodiments of the application, but the embodiments of the application are not limited by the above examples, and any changes, modifications, substitutions, simplifications made without departing from the spirit and principles of the application are equivalent replacement methods, and are all included in the protection scope of the application.

Claims

1. A method for predicting the pollutant adsorption capacity of a carbon substrate functional group using software, characterized in that, The method comprises the following steps: (1) The biochar is subjected to element analysis, Fourier infrared and XPS test, peak separation treatment is conducted by using XPSpeak41 software, and types and contents of functional groups of the biochar are obtained; (2) According to the types and contents of functional groups measured, a biochar model is constructed by using a Sketch tool in Materials Studio 2017R2 software, and a two-dimensional graphite model without functional groups is also constructed; (3) A molecular structure model of the pollutant is constructed by using the Sketch tool in Materials Studio 2017R2 software, a solid-liquid interface model is constructed by using an Amorphous Cell Construction tool and a Build Layers tool, simulated water molecules and organic pollutant molecules are added to a simulation box, structure optimization is conducted on the constructed model by using a Forcite module, molecular dynamics simulation is conducted on the optimized model, an equilibrium configuration is obtained, the adsorption of the organic pollutant on the surface of the biochar model and the graphite surface is analyzed by using an Analysis tool in the Forcite module according to a trajectory file of the equilibrium configuration, the adsorption of the organic pollutant on the surface of the biochar and the graphite surface is analyzed by using a relative concentration distribution curve, and the adsorption capacity of the functional group to the pollutant in the adsorption process is quantified, and the specific formula is as follows: The adsorption amount of the functional group = the theoretical maximum adsorption amount of the biochar x relative concentration distribution proportion difference x (3.75-4.15) Wherein, the theoretical maximum adsorption amount of the biochar is the amount of the pollutant absorbed by the biochar; the relative concentration distribution proportion difference = the number of pollutant molecules adsorbed by the biochar model / percentage - the number of pollutant molecules adsorbed by the graphite model / percentage.

2. The method of predicting the ability of a carbon substrate functional group to adsorb a contaminant using software of claim 1, wherein, The preparation method of the biochar in step (1) comprises the following specific steps: under a nitrogen atmosphere, chicken feathers are heated to 220 DEG C at a heating rate of 10 DEG C / min, and then heated to 425 DEG C at the same heating rate for 2 hours, and then naturally cooled, and then mixed with KOH and water at a mass ratio of 1:2:4, and then the mixture is dried at 60 DEG C, and then the sample after drying is heated to 800 DEG C at a heating rate of 10 DEG C / min under a nitrogen atmosphere for 1 hour, and then cooled to room temperature, and then washed with deionized water until neutral, and then dried at 60 DEG C to obtain the biochar.

3. The method of predicting the ability of a carbon substrate functional group to adsorb a contaminant using software of claim 1, wherein, The pollutant in step (3) is bisphenol A, chloramphenicol or sulfamethoxazole.

4. The method of predicting the ability of a carbon substrate functional group to adsorb a contaminant using software of claim 1, wherein, The size of the simulation box set in step (3) is The number of water molecules is set to 6000, and the number of pollutant molecules = actual concentration x 0.6, with the actual concentration being 10-100 mg / L.

5. The method of predicting the ability of a carbon substrate functional group to adsorb a contaminant using software of claim 1, wherein, In step (3), the parameters for structure optimization of the constructed model by using the Forcite module are as follows: force field: COMPASS II, van der Waals interaction is calculated by using an Atom Based method, Coulomb interaction is calculated by using an Ewald method, and the system is optimized for 10000 steps by using a Smart Minimizer method.

6. The method for predicting the adsorption capacity of functional groups of a carbon-based material to pollutants by using software according to claim 1, wherein The parameters of step (3) are as follows: the NVT ensemble is selected, the temperature is controlled by the Nose method, the temperature is 298 K, the time step is 1 fs, the total simulation time is 2000 ps, and the results are output every 5 ps.

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