A doped iron-based catalyst based on density functional theory and a method for researching the same
By studying rare earth-doped iron-based catalysts using density functional theory, the problem of imperfect research methods was solved, catalyst performance was optimized, and efficient and environmentally friendly catalyst design was achieved, saving resources and time.
Patent Information
- Application Number
- CN202311049327.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2023-08-18
- Publication Date
- 2025-12-30
- Estimated Expiration
- 2043-08-18
AI Technical Summary
The existing research methods for rare earth metal-doped iron-based catalysts are incomplete, and the adsorption performance of the doped catalyst surface on reactant gas molecules is unclear.
The rare earth-doped iron-based catalyst was studied using density functional theory (DFT). The catalyst structure was optimized by spin polarization DFT calculation and Materials Studio software. The electronic structure and reaction mechanism of the catalyst were analyzed by combining PDOS plots to optimize the catalyst performance.
This provides an efficient and environmentally friendly method for catalyst research, saving time and resources, predicting catalyst performance, reducing computation time, avoiding chemical pollution, and making it suitable for widespread application.
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Figure CN117095769B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to a doped iron-based catalyst based on density functional theory and its research method, belonging to the fields of materials science, catalysis science and computational chemistry. Background Technology
[0002] From the 20th century to the present, with the rapid development of industry, the use of fossil fuels has been increasing, leading to a rise in nitrogen oxides (NOx). x SO2 is one of the major air pollutants. V2O5-WO3 / TiO2 (VW / T) catalysts at 300–400℃ have been extensively studied as industrial SCR denitrification catalysts. Higher activation temperatures lead to excessive N2O generation, making SO2 more easily oxidized to SO3. Furthermore, the toxicity of vanadium increases the post-treatment cost of deactivated catalysts. Therefore, there is an urgent need to develop low-temperature, high-efficiency denitrification catalysts. In recent years, iron-based catalysts have been favored by many researchers due to their advantages such as wide availability, no pollution, low cost, and high structural selectivity.
[0003] Iron-based catalysts are excellent denitration catalysts and have attracted increasing attention from researchers in recent years. γ-Fe₂O₃ exhibits good denitration performance in the temperature range of 200–290℃, with an efficiency reaching up to 90% at 250℃. However, when the temperature exceeds 300℃, γ-Fe₂O₃ transforms into α-Fe₂O₃, leading to a decrease in efficiency. Previous experiments have shown that doping with transition metals or rare earth metals can alter the physicochemical properties of the catalyst surface and improve its denitration activity. China possesses the world's largest rare earth mineral resources, particularly in Jiangxi and Inner Mongolia. The advantage of rare earth elements lies in their localized f-orbital electrons, which provide magnetism to rare earth compounds. A characteristic of the electronic structure of rare earth elements is that their outermost electron orbital is 4f. 1+n 5d 0～1 6s 2 Under normal conditions, the 5d orbitals of most rare earth elements (except La) are empty, and these empty orbitals can serve as "electron transfer stations" for catalysis. Therefore, rare earth elements, with their good redox properties, suitable surface acidity, and excellent oxygen storage and release capabilities, have attracted attention in the modification and preparation of NH3-SCR catalysts. Optimizing the concentration, location, and structure of rare earth metal doping has a significant impact on catalyst performance, but accurately controlling these parameters remains a challenge. Furthermore, the adsorption performance of reactant gas molecules on the surface of the doped catalyst is still unclear.
[0004] Therefore, there is an urgent need in this field for a research method for doped iron-based catalysts. Summary of the Invention
[0005] The problem to be solved by the present invention is that the research methods for rare earth metal doped iron-based catalysts in the prior art are not perfect.
[0006] Density functional theory (DFT) has proven to be one of the most effective methods for studying gas adsorption and reaction mechanisms. It can both confirm experimental findings at the microscopic level and predict results that experimental methods cannot achieve. Therefore, this invention uses DFT to conveniently compare rare-earth-doped iron-based catalysts before and after their formation, providing in-depth understanding of the catalyst's electronic structure, reaction mechanism, and surface properties, and offering valuable information for catalyst optimization and design.
[0007] To address the aforementioned problems, the present invention provides a doped iron-based catalyst based on density functional theory and its research method.
[0008] In a first aspect, the present invention provides a method for studying doped iron-based catalysts based on density functional theory, comprising the following steps:
[0009] Step 1: Based on the existing model, perform supercell construction to obtain the original γ-Fe2O3 crystal structure;
[0010] Step 2: Spin polarization DFT calculations were performed using the Perdew-Burke-Ernzerhof (PBE) function and the Projector Augmented Wave (PAW) method. The original γ-Fe2O3 was optimized by selecting a K-point with a cutoff energy of 400 eV and a value of 5×5×5 to obtain the optimized γ-Fe2O3 crystal structure.
[0011] Step 3: The optimized γ-Fe2O3 crystal structure in Step 2 is cross-sectioned into a supercell, and further optimized using the Constraints function of the Modify option in MaterialsStudio to obtain a model of the γ-Fe2O3(001) surface.
[0012] Step 4: Replace one Fe atom in the γ-Fe2O3(001) surface structure described in Step 3 with the rare earth element Pr, and then optimize the above parameter settings;
[0013] Step 5: Based on the results of Step 4, introduce NH3 molecule adsorption into the model obtained in Step 4, and further optimize the structure to calculate the gas adsorption energy E of the doped catalyst. abs ;
[0014] Step 6: Perform post-processing analysis on the results obtained in Step 5 to obtain the PDOS graph.
[0015] Preferably, the original γ-Fe₂O₃ crystal structure in step 1 is calculated to be 10.667 × Fe₂O₃, which is Fe 21.33 O 32 .
[0016] Preferably, in the supercell of step 3, a 2×2 model is set up and Vacuum layer, the space below is left empty when setting the unit cell. In the vacuum layer, five atomic layers are finally selected. During optimization, the bottom two atomic layers are fixed while the other atoms are relaxed.
[0017] Preferably, in step 4, one Fe atom on the surface is replaced with a Pr atom, and optimization is performed again. The optimization settings are based on the settings in step 3, with the addition of DFT+U calculation, and the U value of the f orbital of Pr is set to 4.5.
[0018] In a second aspect, the present invention provides a doped iron-based catalyst obtained by the above-described method.
[0019] Compared with the prior art, the present invention has the following beneficial effects:
[0020] 1. The method of this invention overcomes the shortcomings of the traditional "trial and error" method for catalyst preparation, saves time and resources, and determines the initial crystal structure based on density functional theory, and analyzes the performance through theoretical calculations.
[0021] 2. This invention does not involve the implementation and experimentation of chemical products throughout the entire process, and will not generate chemical pollution. It conforms to the concept of environmental protection and green development, and is low in cost, easy to operate, easy to implement, and suitable for application and promotion.
[0022] 3. This invention can predict the performance of the catalyst in advance through calculation results before the experiment, and select suitable samples in advance, thus saving experimental time.
[0023] 4. By setting the calculation parameters reasonably, the calculation time is reduced, and the waste of computer time is avoided. Attached Figure Description
[0024] Figure 1 This is a model diagram after Pr doping;
[0025] Figure 2 The diagram shows the adsorption configuration of NH3 molecules on the γ-Fe2O3(001) surface;
[0026] Figure 3 The adsorption configuration of NH3 molecules on the Pr-doped γ-Fe2O3(001) surface is shown.
[0027] Figure 4 The PDOS results of NH3 molecules adsorbed on the γ-Fe2O3(001) surface are shown in the figure.
[0028] Figure 5 The image shows the PDOS results of NH3 molecules adsorbed on the Pr-doped γ-Fe2O3(001) surface. Detailed Implementation
[0029] To make the present invention more apparent and understandable, preferred embodiments are described in detail below with reference to the accompanying drawings:
[0030] Step 1: The initial crystal structure was determined through literature analysis: γ-Fe₂O₃, CIF file code 9006317, space group number 213. The lattice constant of γ-Fe₂O₃ is...
[0031] Step 2: Through convergence experiments, a cutoff energy of 400 eV and a K-point of 5×5×5 were selected for bulk optimization. Spin polarization DFT calculations were performed using the Perdew-Burke-Ernzerhof (PBE) function and the Projector Augmented Wave (PAW) method. The INCAR file was obtained using VASPKIT function 101, the KPOINTS file using function 102, and the POTCAR file using function 103. The POSCAR file was obtained in step 1. After optimization, the total energy and force changes for each ion interaction were less than 10. -5 eV and 10 -3 eV A -1 This demonstrates that the calculation is reliable and that the optimized crystal structure was obtained.
[0032] Step 3: Since the 001 surface of γ-Fe2O3 exhibits the strongest reactivity, it is selected as the reaction surface. The optimized γ-Fe2O3 crystal structure is cross-sectioned using Materials Studio software, with a 2×2 slab model and 15 [unclear text - possibly related to crystal structure or parameters]. The vacuum layer was selected. Five atomic layers were chosen, with the bottom two layers fixed to relax the other atoms. Since the supercell model is too large to be easily computed, Monkhorst-pack 1×1×1 points were selected to compute the structure after the supercell, resulting in an optimized γ-Fe2O3(001) surface model.
[0033] Step 4: Since the γ-Fe₂O₃(001) surface has four octahedral Fe cations as the main active sites participating in the SCR process, the rare earth element Pr is used to replace one Fe atom in the surface structure before optimizing the above parameter settings. Because transition metal-doped iron-based catalysts are strongly electron-correlated systems, Hubbard U should be considered in the DFT calculations. Therefore, the U value of Fe's d orbital is 4.0, and the U value of Pr's f orbital is 4.5. Final optimization calculations are then performed, as follows... Figure 1 As shown.
[0034] Step 5, first place NH3 gas molecules into The single-cell structure was optimized, and then NH3 molecules were placed into the optimized structure from steps 3 and 4 for adsorption simulation tests. The optimized structure yielded the desired result. Figure 3 , 4 As shown. The formula (1) for calculating the adsorption energy is:
[0035] E abs = E gas+surface – (E abs + E surface (1)
[0036] Among them, E gas+surface E represents the energy of the gas adsorption configuration and the relaxation surface. gas E represents the energy of a single gas before adsorption. surface This represents the energy after the surface has relaxed.
[0037] Step 6: Based on Step 5, perform PDOS calculations on the optimized structure. Add parameters such as LORBIT and NEDOS to the INCAR settings, and increase the number of K-points by setting the ISMEAR value to -5. Use function 115 of the VASPKIT post-processing tool to analyze the PDOS results of NH3 gas molecules adsorbed on the γ-Fe2O3(001) surface before and after doping. Figure 4 , 5 .
[0038] The above embodiments are merely preferred embodiments of the present invention and are not intended to limit the present invention in any form or substance. It should be noted that those skilled in the art can make several improvements and additions without departing from the present invention, and these improvements and additions should also be considered within the scope of protection of the present invention.
Claims
1. A method for studying doped iron-based catalysts based on density functional theory, characterized in that, Comprising the following steps: Step 1: Supercell on the basis of the existing model, get the original γ-Fe2O3 crystal structure; Step 2: Using Perdew-Burke-Ernzerhof (PBE) function and projector augmented wave (PAW) method for spin polarization DFT calculation and selecting the cutoff energy of 400eV and 5×5×5 K points to optimize the original γ-Fe2O3, get the optimized γ-Fe2O3 crystal structure; Step 3: Cutting surface supercell on the optimized γ-Fe2O3 crystal structure in step 2, and using the Constraints function of Modify option of Materials Studio for further optimization, get the model of γ-Fe2O3(001) surface; Step 4: Replacing one Fe atom of the γ-Fe2O3(001) surface structure in step 3 with rare earth element Pr and optimizing again with the above parameter settings; Step 5: Through the results of step 4, introducing NH3 molecule adsorption into the model obtained in step 4, and further optimizing the structure to calculate the gas adsorption energy Eabs of the doped catalyst; Step 6: Data post-processing analysis of the results obtained in step 5, get PDOS diagram.
2. The density functional theory-based doped iron-based catalyst investigation method according to claim 1, wherein, The original γ-Fe2θ crystal structure of step 1 is actually calculated model 10.667 x Fe2θ, which is Fe 21.33 O 32 .
3. The density functional theory-based doped iron-based catalyst investigation method according to claim 1, wherein, In the supercell of step 3, set 2×2 model and 15Å vacuum layer, set the unit cell with 2Å vacuum layer at the bottom, and finally select five layers of atoms, and optimize the lowermost two layers of atoms while relaxing the other atoms.
4. The density functional theory-based doped iron-based catalyst investigation method according to claim 1, wherein, In step 4, replace one Fe atom on the surface with Pr atom, and optimize again, and increase DFT+U calculation based on the settings in step 3, and set the U value of Pr f orbit as 4.5.
Citation Information
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