Simulation calculation method for catalytic degradation of SF6
By constructing a molecular model of nitrogen-doped carbon materials and a metal-doped catalyst, the density functional and transition state theory is used to solve the problem of insufficient microscopic mechanism of the catalyst, and a low-cost and efficient SF6 degradation effect is achieved.
Patent Information
- Application Number
- CN202510518775.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-24
- Publication Date
- 2025-08-08
AI Technical Summary
The microscopic mechanism research of existing catalysts in the SF6 degradation process is insufficient, and the catalyst development is blind. Traditional degradation methods have problems such as high temperature requirements, low efficiency, and poor product selectivity.
Density functional theory and transition state theory are used to construct a molecular model of nitrogen-doped carbon materials, select metal atoms for doping, build a gas-solid adsorption model and reaction path, calculate the catalytic performance of the catalyst, and evaluate the catalytic effect of different doping structures.
Explain the mechanism of action of the catalyst from a microscopic level, reduce the reaction energy demand, improve the degradation rate and product selectivity, and provide guidance for suitable catalysts, which is relatively low.
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Abstract
Description
Technical Field
[0001] The present invention belongs to the field of molecular simulation calculation, and in particular relates to a simulation calculation method for catalytic degradation of SF6. Background Art
[0002] Sulfur hexafluoride (SF6) is a synthetic, stable gas. Due to its excellent insulation and arc-extinguishing properties, it is widely used in the power industry. Global SF6 emissions are enormous, equivalent to 125 million tons of carbon dioxide annually, and are growing at a rate of 10% per year. SF6 is a greenhouse gas regulated under the Kyoto Protocol, with a greenhouse gas potential 23,900 times that of CO2, an atmospheric lifetime of 3,200 years, and resistance to natural degradation. Therefore, reducing SF6 emissions is of paramount importance to the environment and society.
[0003] SF6 emissions can be reduced through three approaches across the production, use, recovery, and disposal of SF6: recycling and reusing SF6 waste gas, replacing it with new gases, and degradation. Recycling and reusing SF6 waste gas is direct and effective. Traditional degradation methods require high levels of external energy and demanding reaction conditions, resulting in low degradation efficiency, complex equipment, and high degradation costs. Finding a suitable catalyst for the degradation process can reduce the activation energy required, improving degradation rates and product selectivity. Domestic and international researchers have conducted extensive experimental research on SF6 catalytic degradation, focusing on SF6 decomposition products, decomposition pathways, and gas-solid surface adsorption characteristics. Most studies remain at the experimental level, with relatively few addressing the catalytic mechanisms at the microscopic level. Currently, mainstream SF6 degradation methods include thermal (catalytic) degradation, photocatalytic degradation, and NTP (low-temperature plasma) degradation. Targeting these three degradation methods, domestic and international researchers have developed a variety of catalysts, including metals and metal oxides, phosphates, and supported catalysts, and have developed and optimized a variety of degradation schemes with remarkable results. However, overall, the pyrolysis method requires a high temperature environment above 400°C, placing stringent demands on the degradation equipment. Photolysis, while milder in reaction conditions, has lower degradation efficiency and requires higher photochemical properties of the catalyst. While the plasma method can be performed at low temperatures and achieve high conversion rates at low SF6 concentrations, it suffers from poor product selectivity and complex tail gas treatment procedures. Catalyst development is largely based on verification experiments, without in-depth exploration of the microscopic mechanisms of catalytic action, leading to a certain degree of blindness in catalyst selection and preparation.
[0004] Nitrogen-doped carbon materials are novel materials created by chemically linking or incorporating nitrogen atoms into the carbon skeleton. Because nitrogen and carbon atoms are of similar size, the carbon skeleton structure is minimally disrupted during nitrogen substitution, maintaining the stability of the carbon material. Furthermore, because nitrogen atoms are more electronegative than carbon atoms, the doped carbon materials exhibit superior electronic conductivity. The introduction of nitrogen gives nitrogen-doped carbon materials a unique structure, offering numerous advantages over traditional catalysts. While improving their ability to activate reactant or product molecules, the introduction of nitrogen also effectively enhances the dispersion and stability of active species, modulating their redox properties and ultimately improving catalytic performance. Nitrogen-doped carbon materials, due to their unique structure and properties, have been widely developed in the field of catalysis. However, research on the application of nitrogen-doped carbon materials to SF6 is virtually non-existent. Summary of the Invention
[0005] The present invention mainly addresses the problems of insufficient exploration of the microscopic mechanism of catalyst action, the inability of existing catalysts to fully meet the SF6 degradation requirements, and the certain blindness in catalyst development. The present invention provides a simulation calculation method for catalytic degradation of SF6. The method of the present invention is based on density functional theory and transition state theory, and examines the material's catalytic SF6 degradation ability at a microscopic level. It can explain the catalyst's mechanism of action at a microscopic level, and the calculation is simple and the cost is low.
[0006] To achieve the above objectives, the following technical solutions are specifically included:
[0007] A simulation calculation method for catalytic degradation of SF6 includes the following steps:
[0008] (1) Constructing a molecular structure model of nitrogen-doped carbon materials;
[0009] (2) selecting sites on the molecular structure model of the nitrogen-doped carbon material for metal atom doping, performing structural optimization, and determining the molecular structure model of the metal-doped catalyst;
[0010] (3) selecting the adsorption sites of gaseous SF6 on the molecular structure model of the metal-doped catalyst and the molecular structure model of the nitrogen-doped carbon material, respectively, and constructing a gas-solid adsorption model, and then performing structural optimization to obtain a gas-solid adsorption model of SF6 adsorbed by the metal-doped catalyst and a gas-solid adsorption model of SF6 adsorbed by the nitrogen-doped carbon material; and then calculating to obtain the property information of the gas-solid adsorption model of SF6 adsorbed by the metal-doped catalyst and the gas-solid adsorption model of SF6 adsorbed by the nitrogen-doped carbon material, and determining the nitrogen-doped carbon material model and the metal-doped catalyst model for catalytic degradation of SF6 according to the property information;
[0011] (4) First, the reaction path of SF6 degradation is constructed to determine the reactants and products; adsorption sites are selected on the nitrogen-doped carbon material model and the metal-doped catalyst model to adsorb the reactants and products, the structures of the adsorbed reactants and products are optimized, and then the transition state of the reaction is determined. Finally, the reaction heat and energy barrier of the reactants to generate products through the transition state reaction on the nitrogen-doped carbon material model and the metal-doped catalyst model are calculated respectively, and the catalytic performance of the nitrogen-doped carbon material and the metal-doped catalyst is evaluated based on the reaction heat and the energy barrier.
[0012] The calculation method of the present invention involves molecular model establishment and molecular dynamics calculation, based on density functional theory and transition state theory, specifically through Materials Studio software, including building a molecular model of nitrogen-doped carbon material, selecting metal atoms to dope and modify the nitrogen-doped carbon material to obtain a molecular structure model of a metal-doped catalyst, building a gas-solid adsorption model of SF6 molecules, finding the transition state of SF6 defluorination reaction, and building an SF6 defluorination reaction path. Among them, the molecular structure model of the nitrogen-doped carbon material is first constructed, and then the metal-doped catalyst model is constructed. By calculating the binding energy and charge transfer amount of the molecular structure model of the metal-doped catalyst, it can be determined which doping structure is more stable and more conducive to electron transmission, so as to evaluate which doping structure is a suitable metal-doped catalyst structure; then, the adsorption sites of gaseous SF6 are selected on the molecular structure model of the metal-doped catalyst and the molecular structure model of the nitrogen-doped carbon material, and a gas-solid adsorption model is constructed. By calculating the adsorption energy, The ability of the gas-solid adsorption model to interact with SF6 molecules is judged by using property information such as electron transfer, differential charge density, state density, interatomic bond length or bond angle, and the structure with stronger interaction with SF6 molecules is selected as the model for subsequent calculation of nitrogen-doped carbon materials and metal-doped catalysts for catalytic degradation of SF6; finally, the reaction path, reactants, products and transition states of SF6 degradation are determined, and the reaction heat and energy barrier of the reactants to generate products through the transition state reaction on the nitrogen-doped carbon material model and the metal-doped catalyst model are calculated respectively. The catalytic performance of the nitrogen-doped carbon material and the metal-doped catalyst is evaluated based on the reaction heat and the energy barrier. Therefore, based on density functional theory and transition state theory, the present invention constructs structural models of catalysts before and after metal doping and the reaction path of catalytic degradation of SF6 on the catalyst from a microscopic level, and calculates the change in reaction energy of catalytic degradation of SF6 by the catalyst before and after metal doping. According to the difference in reaction energy of catalytic degradation of SF6 by different catalysts, the energy of catalytic degradation of SF6 by the catalyst before and after metal doping is evaluated. Based on this process, it can be determined which doping structure is more suitable and the difference in catalytic effect of the catalyst before and after metal doping can be analyzed to determine which catalyst and catalytic path are more suitable for catalytic degradation of SF6. This has a guiding role in finding suitable catalysts and microscopic catalytic reaction paths in actual research, and is of great significance for researching and exploring catalytic materials for SF6 degradation.
[0013] Preferably, in step (1), the nitrogen-doped carbon material in the molecular structure model of the nitrogen-doped carbon material is a two-dimensional nanostructure.
[0014] Preferably, in step (1), the nitrogen species in the molecular structure model of the nitrogen-doped carbon material includes at least one of graphitic nitrogen, pyridinic nitrogen, pyrrolic nitrogen or pyridinic nitrogen oxide.
[0015] Preferably, in step (1), in the molecular structure model of the nitrogen-doped carbon material, the lattice parameter in the Z direction is
[0016] Preferably, the method further includes calculating the electronic structure information of the molecular structure model of the metal-doped catalyst, wherein the electronic structure information includes binding energy and charge transfer amount. In step (2), the binding energy is -1eV to -8eV, and the charge transfer amount is 0.1e to 0.4e. Based on the electronic structure information of the molecular structure model of the metal-doped catalyst, it is possible to evaluate at which site of the catalyst the metal is doped, where the structure of the catalyst is more stable and more conducive to electron transmission, so as to determine which metal-doped catalyst molecular structure is more suitable as the catalyst model for subsequent calculation of catalytic degradation of SF6.
[0017] Preferably, in step (2), the metal atoms include at least one of copper atoms and zinc atoms.
[0018] Preferably, in step (2), the molecular structure model of the metal-doped catalyst includes at least one of the following two metal atom doping structures: (a) metal atoms are doped at the divacancy sites formed by four pyridinic nitrogen atoms; and (b) metal atoms are doped at the top sites of graphitic nitrogen atoms. The inventors of the present invention have confirmed that the use of the above three metal-doped catalyst structures can be more conducive to obtaining a metal-doped catalyst molecular structure with better stability and electron transport capability.
[0019] In step (3), the property information includes at least one of adsorption energy, electron transfer, differential charge density, density of states, interatomic bond length or bond angle.
[0020] Preferably, in step (3), in the gas-solid adsorption model of SF6 adsorbed by the metal-doped catalyst, the SF6 molecules have at least one of the following three molecular orientations: M1, where one F atom in the SF6 molecule is closest to the catalyst surface; M2, where two F atoms in the SF6 molecule are closest to the catalyst surface; and M3, where three F atoms in the SF6 molecule are closest to the catalyst surface. The inventors of the present invention have confirmed that the above three SF6 molecular orientations can be used to further enhance the interaction strength between the SF6 molecules and the catalyst material.
[0021] Preferably, in step (3), the calculation specifically includes using density functional theory calculation, and the density functional theory calculation also includes using generalized gradient approximation to approximate the exchange correlation energy as a functional of the electron density.
[0022] Preferably, in step (3), the calculation specifically includes calculation parameter setting, and the calculation parameter setting further includes the following steps: using the Grimme method in DFT-D for dispersion correction; selecting the DNP basis set for electron wave function expansion; using density functional semi-core pseudopotential for kernel processing; setting the cutoff radius of the effective action of the atomic orbital to The convergence accuracy of SCF is 1.0×10 -5 The direct inversion DIIS value in the SCF iterative subspace is set to 6; the thermal tail effect Smearing value is set to 0.005Ha; the Brillouin zone k-point sampling is set to 3×3×1; the energy convergence criterion is set to 2.0×10 -5 Ha, the maximum force and maximum displacement are
[0023] Preferably, in step (4), the calculation specifically includes using density functional theory calculation, and the density functional theory calculation also includes using generalized gradient approximation to approximate the exchange correlation energy as a functional of the electron density.
[0024] Preferably, in step (4), the calculation specifically includes calculation parameter setting, and the calculation parameter setting further includes the following steps: using the Grimme method in DFT-D for dispersion correction; selecting the DNP basis set for electron wave function expansion; using density functional semi-core pseudopotential for kernel processing; setting the cutoff radius of the effective action of the atomic orbital to The convergence accuracy of SCF is 1.0×10 -5 The direct inversion DIIS value in the SCF iterative subspace is set to 6; the thermal tail effect Smearing value is set to 0.005Ha; the Brillouin zone k-point sampling is set to 3×3×1; the energy convergence criterion is set to 2.0×10 -5 Ha, the maximum force and maximum displacement are
[0025] Preferably, in steps (2), (3) and (4), the structure optimization includes using density functional theory calculations, and the density functional theory calculations also include using generalized gradient approximation to approximate the exchange correlation energy as a functional of the electron density.
[0026] Preferably, in steps (2), (3) and (4), the structure optimization is performed by Materials Studio computational simulation software, specifically including calculation parameter setting, wherein the calculation parameter setting further comprises the following steps: using the Grimme method in DFT-D for dispersion correction; selecting the DNP basis set for electron wave function expansion; using density functional semi-core pseudopotential for kernel processing; setting the cutoff radius of the effective action of the atomic orbital to The convergence accuracy of SCF is 1.0×10-5 The direct inversion DIIS value in the SCF iterative subspace is set to 6; the thermal tail effect Smearing value is set to 0.005Ha; the Brillouin zone k-point sampling is set to 3×3×1; the energy convergence criterion is set to 2.0×10 -5 Ha, the maximum force and maximum displacement are
[0027] Compared with the prior art, the present invention has the following beneficial effects: the simulation calculation method of the present invention is based on density functional theory and transition state theory, including building a molecular model of nitrogen-doped carbon materials, selecting metal atoms to dope and modify nitrogen-doped carbon materials, constructing a gas-solid adsorption model of SF6 molecules, finding the transition state of SF6 defluorination reaction, and constructing the SF6 defluorination reaction path; from a microscopic level, the effect of the catalyst on catalytic SF6 degradation is calculated, and the mechanism of action of the catalyst is explained. The calculation is simple and the cost is low, which is of great significance for the research and exploration of catalytic materials for SF6 degradation. BRIEF DESCRIPTION OF THE DRAWINGS
[0028] Figure 1 This is a simulation calculation flow chart of Example 1.
[0029] Figure 2 The intrinsic material structure model constructed in Example 1 and the catalyst molecular structure model doped with copper atoms.
[0030] Figure 3 This is the adsorption result of SF6 molecules on the copper atom-doped catalyst surface in Example 1.
[0031] Figure 4 This is the structural model of SF6 molecules adsorbed on the copper atom-doped catalyst surface before optimization in Example 1.
[0032] Figure 5 This is the structural model of the reactants and products of the defluorination of SF6 molecules to generate SF5 molecules and F atoms in Example 1.
[0033] Figure 6 This is the defluorination reaction path of SF6 molecules on the copper atom-doped catalyst surface in Example 1.
[0034] Figure 7 This is the defluorination reaction path of SF6 molecules on the surface of the intrinsic material in Example 1.
[0035] Figure 8 The figure is a flow chart of the simulation calculation method for catalytic degradation of SF6 according to the present invention. DETAILED DESCRIPTION
[0036] To better illustrate the objectives, technical solutions, and advantages of the present invention, the present invention will be further described below with reference to specific examples. The experimental methods used in the examples and / or comparative examples are conventional methods unless otherwise specified; the materials and reagents used are commercially available unless otherwise specified.
[0037] Example 1
[0038] In this embodiment, based on density functional theory and transition state theory, relying on the computational simulation software Materials Studio, an intrinsic material simulation model of nitrogen-doped carbon materials was built. Then, doping sites were selected on the surface of the intrinsic material, and Cu atoms were used for doping modification to obtain a copper atom-doped catalyst. Then, the adsorption experiment of SF6 molecules was carried out on the surface of the intrinsic material and the copper atom-doped catalyst, respectively. After the structure was built, the structure was optimized, and the results were analyzed and compared from the perspectives of adsorption energy, charge transfer amount, bond length change, and state density. In order to further explore the catalytic degradation effect of the selected materials on SF6 molecules, this study constructed the subsequent defluorination reaction path of low-fluorine sulfides on the surfaces of the two materials, conducted a transition state search, and analyzed the energy changes during the reaction process.
[0039] In the present embodiment, the Dmol3 module of Materials Studio software is mainly relied on for modeling and calculation. Dmol3 is a quantum mechanics calculation program based on density functional theory, which can simulate the processes and properties of organic and inorganic molecules, molecular crystals, covalent solids, metallic solids and material surfaces, and is a more commonly used calculation module after comprehensive calculation cost and accuracy factors. In density functional theory, it is necessary to approximate the exchange correlation energy to the functional of electron density, where the two simplest approximation methods are domain density approximation (LDA) and generalized gradient approximation (GGA). The LDA functional is applicable to systems with slow charge density changes and higher charge density; GGA introduces a density gradient in the process of approximating exchange correlation energy, overcomes the limitations of LDA based on the uniform electron gas model, improves calculation accuracy, and improves the calculation accuracy of transition state energy barrier while reducing the error of chemical bond dissociation energy.
[0040] This paper studies gas-solid interactions and subsequent reaction path construction including transition state search. Chemical adsorption may occur in this process, accompanied by electron transfer and changes in molecular structure. Therefore, it is more suitable to use the GGA functional containing density gradient. The specific calculation parameters are set as follows: the Grimme method in DFT-D is used for dispersion correction; the DNP basis set is selected for electronic wave function expansion; the density functional semi-core pseudopotential (DSSP) is used for core processing; the cutoff radius of the effective atomic orbital action is set to The convergence accuracy of SCF is 1.0×10 -5The direct inversion DIIS value in the SCF iterative subspace is set to 6; the thermal tail effect Smearing value is set to 0.005Ha; the Brillouin zone k-point sampling is set to 3×3×1; the energy convergence criterion is set to 2.0×10 -5 Ha, the maximum force and maximum displacement are The simulation calculations used in this embodiment all adopt the above parameters, wherein the simulation calculations include the construction of the molecular structure model, the structural optimization of the molecular structure model, the calculation of the property information of the molecular structure model, and the calculation of the reaction heat and energy barrier of the transition state and reaction path.
[0041] The specific process is as follows:
[0042] (1) Constructing the molecular structure model of intrinsic material (CN):
[0043] The nitrogen species in nitrogen-doped carbon materials are mainly divided into four types, namely graphitic nitrogen, pyridinic nitrogen, pyrrolic nitrogen and pyridinic nitrogen oxide. According to the relative changes in the content of nitrogen species, a molecular structure model of nitrogen-doped two-dimensional nanocarbon materials is constructed, and the structure is optimized to obtain an intrinsic material molecular structure model. The intrinsic material molecular structure model constructed in this embodiment is obtained by doping nitrogen atoms in a 5×5×1 single-layer graphene. The doping form of nitrogen atoms mainly considers two forms: graphitic nitrogen and pyridinic nitrogen. These two forms of nitrogen atoms interact strongly with the reactants. In addition, this embodiment also constructs nitrogen atom defect sites by adjusting the doping sites and number of pyridinic nitrogen atoms to provide sites for subsequent metal atom doping and active sites for adsorption. In order to avoid the interaction of periodic structures, this embodiment studies the setting of the Z direction (perpendicular to the XY plane) lattice parameters on the material molecular structure model to This ensures that the nitrogen-doped carbon material has a Z direction greater than The molecular structure model constructed in this embodiment is as follows Figure 2 As shown in the illustration (a).
[0044] (2) Select copper atoms to dope the intrinsic material, construct a catalyst molecular structure model and perform structural optimization:
[0045] The interaction between nitrogen species and active components such as metal components or metal oxides can be used to improve catalytic performance. In this embodiment, Cu atoms are selected to select sites on the surface of the constructed two-dimensional nano-intrinsic material model for doping, and the structure is optimized based on DFT to obtain a catalyst doped with copper atoms. Among them, when transition metal atoms are doped into the surface of the CN material, a certain amount of energy is released or absorbed. This energy is called binding energy. When energy is released during the doping process, it means that the metal atoms and the CN material tend to form a stable doping structure. The more energy released, the more stable the structure formed, and the stronger the interaction between the metal atoms and the CN material; when energy is absorbed during the doping process, it means that the doping structure formed by the metal atoms and the CN material is unstable, and the repulsion between the two is strong. The more energy absorbed, the more unstable the structure formed. While absorbing or releasing energy, a certain amount of charge transfer and redistribution will occur between the transition metal atoms and the CN material. By analyzing the overall electronic structure after doping, the stability of the structure and the ability of the material to transmit electrons can be further judged.
[0046] Structural optimization of nitrogen-doped carbon materials doped with copper atoms is primarily aimed at achieving a stable doping structure. It also provides physical and chemical information about the structure, such as its energy and electronic structure, under given energy and force convergence criteria. Analysis of this physical and chemical information allows for molecular structure screening and, by comparison with the physical and chemical information of the catalyst structure after SF6 molecules have been adsorbed, analysis of the strength of the adsorption process.
[0047] The molecular structure model of the catalyst doped with copper atoms in this embodiment is represented by Cu-CN-R1, wherein Cu represents copper atoms, CN represents the intrinsic material of nitrogen-doped carbon materials, and R1 represents the serial number of the doping site. For example, in Cu-CN-1, Cu represents copper atoms, CN represents the intrinsic material, and 1 represents doping site 1. This embodiment performs copper atom doping on nitrogen atom defect sites, and provides two catalyst molecular structure models Cu-CN-1 and Cu-CN-2 obtained after doping, which respectively represent copper atoms doped at the divacancy site composed of four pyridine N atoms and copper atoms doped at the top position of graphite N. The structural schematic diagram is shown in FIG. Figure 2As shown in (b) and (c), the binding energy and charge transfer amount obtained by the doping scheme are calculated and shown in Table 1 below. From the optimized structure, it can be preliminarily seen that the Cu atoms doped at site 1 are tightly bonded together in the form of coordination with four pyridine N atoms, and the Cu atoms doped at the graphitic nitrogen are adsorbed on the material surface in a free form, wherein the Cu atoms are significantly offset relative to the top position of the graphitic nitrogen. By comparing the binding energy and charge transfer amount of the two doping schemes, an in-depth analysis shows that the binding energy of both doping schemes is negative, indicating that they tend to form a stable doping structure; the charge transfer amount is positive, the metal atoms become electron donors, and the CN material is an electron acceptor. In terms of doping sites, the binding energy of the metal atoms doped to site 1 is much smaller than that of the doping site 2, and the amount of electrons lost is much greater than that of site 2, indicating that the metal atoms doped at site 1 interact more strongly with the substrate material, and the doping structure formed is more stable. Therefore, compared with the molecular structure model Cu-CN-2, the Cu-CN-1 molecular structure is more stable.
[0048] Table 1
[0049]
[0050]
[0051] (3) Construct a gas-solid adsorption model of SF6 adsorption catalyst and perform structural optimization calculation based on DFT:
[0052] A key aspect of a catalyst's catalytic effect is its ability to lower the reaction energy barrier of a chemical reaction, thereby reducing the energy required for the reaction and promoting its progress. When gas molecules adsorb onto the surface of a solid catalyst material, two different adsorption scenarios occur, depending on the degree of interaction: physical adsorption and chemical adsorption. The adsorption energy and the amount of charge transferred from the SF6 gas molecules during the adsorption process can be used to initially determine which adsorption process is occurring. Physical adsorption has a relatively low adsorption energy, and the amount of charge transferred during the adsorption process is also small. In contrast, chemical adsorption has a relatively high adsorption energy, and the amount of charge transferred during the adsorption process is also large.
[0053] During the actual reaction of catalytic SF6 degradation, a large number of SF6 molecules randomly contact the catalyst surface. Considering the highly symmetrical octahedral structure of SF6 molecules, this paper selects three representative SF6 molecular orientations for subsequent simulated adsorption processes. This paper designates the SF6 molecular orientation with one F atom closest to the material surface as M1, the orientation with two F atoms closest to the material surface as M2, and the orientation with three F atoms closest to the material surface as M3.
[0054] Adsorption sites were selected on the surface of the catalyst molecular structure model constructed above, and various MN-X-CN (M represents the molecular orientation of SF6, and to distinguish and sort different molecular orientations, the corresponding sequence number R2 is added after M, X represents the Cu atom, and CN represents nitrogen-doped carbon material) gas-solid adsorption models were constructed. Density functional calculations and structural optimization were performed. By calculating the adsorption energy, electron transfer, differential charge density, and state density of each gas-solid adsorption model, observing and measuring the changes in interatomic bond lengths and bond angles, and comparing the calculation results of different adsorption models, the catalytic mechanism and catalyst degradation activity were analyzed.
[0055] This example provides 6 gas-solid adsorption models, and the optimized structures are as follows: Figure 3 As shown, Figure 4 This is the structure constructed before optimization. After density functional calculation, the state information of different gas-solid adsorption models was obtained, including the adsorption energy, charge transfer amount and bond length information in Table 2. Compared with the structure before optimization, it can be found that the three gas-solid adsorption models M1-Cu-CN-1, M2-Cu-CN-1 and M3-Cu-CN-1 did not have any bond breaking, while the three gas-solid adsorption models M1-Cu-CN-2, M2-Cu-CN-2 and M3-Cu-CN-2 all broke two SF bonds to generate free SF4 molecules. The two F atoms that were released formed bonds with the Cu atoms doped on the surface of the CN material. In addition, the surface of the Cu-CN-2 material underwent obvious deformation after the adsorption of SF6 molecules, which preliminarily indicates that the interaction between SF6 molecules and the material surface is strong. Further analysis of the changes in adsorption energy, charge transfer amount and bond length calculated by structural optimization shows that the six adsorption configurations all release energy during the adsorption process, and the SF6 molecules all obtain electrons from the material surface. In terms of the absolute value of adsorption energy, the adsorption energies of M1-Cu-CN-1, M2-Cu-CN-1 and M3-Cu-CN-1 are much smaller than those of M1-Cu-CN-2, M2-Cu-CN-2 and M3-Cu-CN-2, among which the energy released by the adsorption configuration of M1-Cu-CN-2 is the largest at 3.676eV. From the absolute value of the charge transfer amount, the number of electrons obtained by the SF6 molecule at site 1 is smaller than that at site 2, among which the number of electrons obtained by the SF6 molecule with the M2-Cu-CN-2 configuration is the largest at 0.853e. From the perspective of bond length change, the SF bonds of the six configurations of SF6 molecules are different relative to the initial bond length. All of them have increased to varying degrees. Among them, the bond length of the SF6 molecule at site 2 increases more than that of the SF6 molecule at site 1. By comparing the state information before and after adsorption, the strength of the interaction between the SF6 molecule and the material surface is analyzed. The stronger the interaction, the greater the potential of this material model to catalyze the decomposition of SF6, and thus this model is selected for subsequent transition state searches. The adsorption energy, charge transfer amount, and bond length changes of each adsorption configuration are shown in Table 2:
[0056] Table 2
[0057]
[0058] (4) In order to further explore the catalytic ability of the material, based on density functional theory (DFT) and transition-state theory (TST), the transition state (TS) in the defluorination process was found, and the defluorination reaction paths SF6 on the surface of the intrinsic material and the surface of the copper atom-doped catalyst were constructed in turn. x →SF x-1 +F(x=6, 5, 4, 3, 2 or 1).
[0059] Among them, the decomposition of SF6 will first defluorinate to generate a series of low-fluorine sulfides in sequence. Therefore, this embodiment first constructs the defluorination reaction path, and then searches for the transition state after the construction. For example, with respect to the SF6→SF5+F defluorination reaction path, first, an adsorption site is selected on the surface of the material to adsorb SF6 as a reactant (for example, an adsorption site located directly above the nitrogen atom defect site), and then SF5 and F atoms are adsorbed on the same material surface as products. The structures of the reactants and products are optimized respectively. The optimized structures of the reactants and products are as follows: Figure 5 As shown, the distance from the reactant SF6 molecules to the material surface is approximately The system energy reached the standard set during structural optimization, approaching the steady-state structure of physical adsorption. The product indicates that the SF6 molecule breaks its bond on the material surface, and the generated SF5 is in a critical state of detachment from the material surface. The detached F atoms then form bonds with Cu atoms and adsorb on the material surface, which is consistent with the reaction pathway constructed in this example. Finally, a transition state search was performed, and the energy changes during the defluorination process were compared. The reaction heat and energy barrier were calculated to explore the catalytic effects of the intrinsic material and the copper-doped catalyst.
[0060] On the surface of the copper atom-doped catalyst, the defluorination of SF6 is gradually carried out to generate S atoms. The overall reaction is exothermic, with a total reaction heat of -72.262 kcal / mol. The specific reaction heat and energy barrier values of each step in the defluorination reaction path are shown in Table 3. After the transition state found in this example, the defluorination reaction path of SF6 molecules on the surface of the copper atom-doped catalyst material is as follows: Figure 6 shown.
[0061] On the surface of the intrinsic material, the gradual defluorination of SF6 to the formation of S atoms is an endothermic reaction with a total reaction heat of 165.048 kcal / mol. The specific reaction heat and energy barrier values of each step in the defluorination reaction path are shown in Table 4. After the transition state found in this example, the defluorination reaction path of SF6 molecules on the surface of the intrinsic material is as follows: Figure 7 shown.
[0062] Table 3
[0063]
[0064] Table 4
[0065]
[0066] From Table 3-4 and Figure 6-7 It can be seen that compared with the surface of the intrinsic material, the defluorination of SF6 molecules to S atoms changes from an endothermic reaction to an exothermic reaction, and the effect of copper atom-doped catalyst in reducing the energy barrier is more significant. That is, after the nitrogen-doped carbon material is modified by Cu atom doping, the catalytic activity of defluorination of SF6 molecules to S can be significantly improved.
[0067] The present invention adopts a theoretical simulation calculation method to calculate the effect of a new material on catalyzing the degradation of SF6 molecules at a microscopic level, which is of great significance for the research and exploration of catalytic materials for SF6 degradation.
[0068] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the essence and scope of the technical solutions of the present invention.
Claims
1. A simulation calculation method for catalytic degradation of SF6, characterized in that: The steps include: (1) Constructing a molecular structure model of nitrogen-doped carbon materials; (2) selecting sites on the molecular structure model of the nitrogen-doped carbon material for metal atom doping, performing structural optimization, and determining the molecular structure model of the metal-doped catalyst; (3) selecting the adsorption sites of gaseous SF6 on the molecular structure model of the metal-doped catalyst and the molecular structure model of the nitrogen-doped carbon material, respectively, and constructing a gas-solid adsorption model, and then performing structural optimization to obtain a gas-solid adsorption model of SF6 adsorbed by the metal-doped catalyst and a gas-solid adsorption model of SF6 adsorbed by the nitrogen-doped carbon material; and then calculating to obtain the property information of the gas-solid adsorption model of SF6 adsorbed by the metal-doped catalyst and the gas-solid adsorption model of SF6 adsorbed by the nitrogen-doped carbon material, and determining the nitrogen-doped carbon material model and the metal-doped catalyst model for catalytic degradation of SF6 according to the property information; (4) First, the reaction path of SF6 degradation is constructed to determine the reactants and products; adsorption sites are selected on the nitrogen-doped carbon material model and the metal-doped catalyst model to adsorb the reactants and products, the structures of the adsorbed reactants and products are optimized, and then the transition state of the reaction is determined. Finally, the reaction heat and energy barrier of the reactants to generate products through the transition state reaction on the nitrogen-doped carbon material model and the metal-doped catalyst model are calculated respectively, and the catalytic performance of the nitrogen-doped carbon material and the metal-doped catalyst is evaluated based on the reaction heat and the energy barrier.
2. The simulation calculation method for catalytic degradation of SF6 according to claim 1, characterized in that: In step (1), the nitrogen-doped carbon material in the molecular structure model of the nitrogen-doped carbon material is a two-dimensional nanostructure; in the molecular structure model of the nitrogen-doped carbon material, the lattice parameter in the Z direction is 3. The simulation calculation method for catalytic degradation of SF6 according to claim 1, characterized in that: In step (1), the nitrogen species in the molecular structure model of the nitrogen-doped carbon material includes at least one of graphitic nitrogen, pyridinic nitrogen, pyrrolic nitrogen or pyridinic nitrogen oxide.
4. The simulation calculation method for catalytic degradation of SF6 according to claim 1, characterized in that: Step (2) also includes calculating the electronic structure information of the molecular structure model of the metal-doped catalyst, wherein the electronic structure information includes binding energy and charge transfer amount, the binding energy is -1eV to -8eV, and the charge transfer amount is 0.1e to 0.4e.
5. The simulation calculation method for catalytic degradation of SF6 according to claim 1, characterized in that: Include at least one of the following AC: A. In step (2), the metal atom comprises at least one of a copper atom and a zinc atom; B. In step (2), the molecular structure model of the metal-doped catalyst includes at least one of the following two metal atom doping structures: (a) metal atoms are doped at the divacancy sites formed by four pyridinic nitrogen atoms; (b) metal atoms are doped at the top sites of graphite nitrogen atoms; C. In step (3), the property information includes at least one of adsorption energy, electron transfer, differential charge density, density of states, interatomic bond length or bond angle.
6. The simulation calculation method for catalytic degradation of SF6 according to claim 1, characterized in that: In step (3), in the gas-solid adsorption model of SF6 adsorbed by the metal-doped catalyst, the SF6 molecules include at least one of the following three molecular orientations: M1, one F atom in the SF6 molecule is closest to the catalyst surface; M2, two F atoms in the SF6 molecule are closest to the catalyst surface; M3, three F atoms in the SF6 molecule are closest to the catalyst surface.
7. The simulation calculation method for catalytic degradation of SF6 according to claim 1, characterized in that: In step (3), the calculation specifically includes using density functional theory calculation, and the density functional theory calculation also includes using generalized gradient approximation to approximate the exchange correlation energy as a functional of electron density.
8. The simulation calculation method for catalytic degradation of SF6 according to claim 1, characterized in that: In step (3), the calculation specifically includes calculation parameter setting, and the calculation parameter setting also includes the following steps: using the Grimme method in DFT-D for dispersion correction; selecting the DNP basis set for electron wave function expansion; using density functional semi-core pseudopotential for kernel processing; setting the cutoff radius of the effective action of the atomic orbital to The convergence accuracy of SCF is 1.0×10 -5 The direct inversion DIIS value in the SCF iterative subspace is set to 6; the thermal tail effect Smearing value is set to 0.005Ha; the Brillouin zone k-point sampling is set to 3×3×1; the energy convergence criterion is set to 2.0×10 -5 Ha, the maximum force and maximum displacement are 9. The simulation calculation method for catalytic degradation of SF6 according to claim 1, characterized in that: In step (4), the calculation specifically includes using density functional theory calculation, and the density functional theory calculation also includes using generalized gradient approximation to approximate the exchange correlation energy as a functional of electron density.
10. The simulation calculation method for catalytic degradation of SF6 according to claim 1, characterized in that: In step (4), the calculation specifically includes calculation parameter setting, and the calculation parameter setting also includes the following steps: using the Grimme method in DFT-D to perform dispersion correction; selecting the DNP basis set to perform electron wave function expansion; using density functional semi-core pseudopotential to perform kernel processing; setting the cutoff radius of the effective action of the atomic orbital to The convergence accuracy of SCF is 1.0×10 -5 The direct inversion DIIS value in the SCF iterative subspace is set to 6; the thermal tail effect Smearing value is set to 0.005Ha; the Brillouin zone k-point sampling is set to 3×3×1; the energy convergence criterion is set to 2.0×10 -5 Ha, the maximum force and maximum displacement are