A method for coating Pt clusters of different sizes with FeN-doped fullerenes to improve their ORR catalytic performance

Abstract

This invention relates to the field of oxygen reduction catalysis technology, and provides a method for improving the ORR catalytic performance of FeN-doped fullerenes coated with Pt clusters of different sizes. The method first constructs FeN4C... 180 A model was constructed and coated with varying numbers of Pt clusters. Density functional theory (DFT) calculations were then used to optimize the model to investigate the ORR catalytic performance of different fullerene-modified structures. Specific steps included: FeN-doped fullerene model construction and optimization; coating with Pt clusters of different sizes; calculation of the stability of the coating structure; calculation of the free energy of the ORR process; and analysis of the intrinsic causes of catalytic performance. Theoretical simulations investigated the influence of Pt cluster size on ORR catalytic performance, providing a new modification strategy for improving the ORR catalytic performance of fullerenes while reducing the amount of precious metals used. The theoretically predicted structures can provide targeted guidance for experimental synthesis, reducing experimental testing costs and the number of operations.

Description

Technical Field

[0001] This invention relates to the field of oxygen catalytic reduction technology, specifically to a method for improving the ORR catalytic performance of FeN-doped fullerenes by coating them with Pt clusters of different sizes. The ORR performance of fullerenes is improved by coating them with different numbers of Pt atom clusters. Background Technology

[0002] Against the backdrop of the ongoing energy revolution, hydrogen energy is considered a crucial starting point for building a global new energy system. Among numerous hydrogen conversion and utilization devices, proton exchange membrane fuel cells (PEMFCs) are considered to have the greatest potential for civilian applications due to their many advantages, especially their low-temperature availability. At the PEMFC cathode, the oxygen reduction reaction (ORR) occurs slowly, inhibiting its conversion efficiency. Currently, platinum (Pt)-based catalysts exhibit the highest ORR activity and were used as commercial catalysts in the early stages of PEMFC promotion. Given that platinum is a rare and expensive precious metal, the development of novel catalysts is crucial; therefore, the design goal is to reduce the amount of platinum used in the catalyst while achieving Pt-like catalytic performance.

[0003] Fullerenes inherently have low electrocatalytic activity, but due to their unique rigid spherical molecular structure, all sp... 2 Hybridized carbon atoms and their unique electron affinity have led to the widespread use of composite materials as electrocatalysts. Furthermore, exploratory research has been conducted on some modified fullerene materials, such as the synthesis of heterofullerene derivatives where carbon atoms are substituted by other heteroelements, which have been reported as potential ORR catalysts. Meanwhile, single-atom catalysts (SACs) are rapidly becoming a research frontier in the field of electrocatalysis. The synergistic effect between metal nanoparticles or metal clusters has been demonstrated to achieve new heights in electrochemical activity. In 2022, Feng et al. successfully synthesized a Ru nanoparticle-encapsulated oxygen-like fullerene carbon cage, decorated with single-atom RuNx species and anchored on a nitrogen-doped carbon substrate. This cage exhibited excellent HER electrocatalytic performance in both acid and base conditions, and this synthetic method can be extended to the transition metal Pt.

[0004] First-principles calculations are a new method for studying materials properties that has rapidly emerged alongside experimental and theoretical research methods, developing rapidly with the advancement of computer technology. They allow for the study and simulation of material properties at the atomic level, particularly elucidating the microscopic principles underlying material properties. Numerous examples of first-principles calculations have demonstrated that this method can be used to conduct in-depth and systematic studies of the catalytic mechanisms of catalysts, guiding their design, synthesis, and application. Furthermore, first-principles calculations do not require actual experiments, only computer molecular simulations, resulting in low investment, low cost, short calculation cycles, high efficiency, accurate results, and simple data interpretation, making them universally applicable. While there are existing international reports on the use of first-principles calculations to characterize the ORR catalytic performance of fullerenes, there are currently no research cases using this method to conduct detailed measurements and characterizations of FeN-doped fullerenes coated with Pt atom clusters of different sizes. Summary of the Invention

[0005] This invention addresses the drawbacks of platinum (Pt)-based catalysts, which are commercially viable ORR catalysts but suffer from high cost and easy deactivation. It provides a method to reduce the amount of platinum used in the catalyst and improve its ORR catalytic performance. This method is based on density functional theory calculations in quantum chemistry, calculating the binding energy of FeN-doped fullerene-coated Pt clusters of different sizes and the ORR 4e⁻. - The ORR catalytic performance of FeN-doped fullerene-coated Pt clusters of different sizes was characterized by the path free energy, electronic density of states, and charge difference density, and the intrinsic reasons for the improved catalytic activity were analyzed.

[0006] This invention provides a method for coating Pt clusters of different sizes with FeN-doped fullerenes to improve their ORR catalytic performance, and constructing FeN4-doped C 180 Model and FeN4C with different numbers of Pt clusters 180 Several doped models were tested, and their stability was assessed by optimizing them using first-principles density functional theory. The ORR (Objective Response Rate) was then calculated. - Based on the reaction pathway free energy diagram, the Pt cluster-doped FeN4C with the best ORR catalytic performance was selected. 180 The intrinsic reasons for its catalytic activity were analyzed by calculating the electronic state density and charge difference density.

[0007] Further, the specific steps are as follows:

[0008] Step 1: Using Device Studio software, modify the C++ code. 180 The model was doped with FeN4 to construct FeN4C 180 Model;

[0009] Step 1.1, in C 180 In the model, the top and bottom four C atoms of a carbon ring containing six C atoms are replaced with N atoms;

[0010] Step 1.2: Delete one of the two C atoms on the left and right, and replace the remaining C atom with an Fe atom to construct FeN4C. 180 Unit cell.

[0011] Step 2, FeN4C 180 The model undergoes structural optimization to obtain the doped model with the lowest energy.

[0012] Step 2.1: Set the structure optimization parameters, including the plane wave cutoff energy, K-point selection, preset criteria for electronic self-consistent iteration and ion relaxation convergence. The convergence criteria for electronic self-consistent iteration and ion relaxation are set to convergence to an energy level of 10. -5 eV and atomic forces converge to The DFT-D3 method (D represents dispersion) was used to analyze FeN4C. 180 The interatomic interactions in the model were corrected using Grimme's van der Waals (vdW).

[0013] Step 3, in the optimized FeN4C 180 The model is used to wrap different numbers of Pt clusters to obtain Pt x @FeN4C 180 In the model, x = 5 - 13;

[0014] Step 3.1: Use Abcluster software to search for the global minimum of Pt clusters, using the Sutton-Chen potential as the force field, and search for Pt clusters with 5-13 atoms;

[0015] Step 3.2: Wrap the searched Pt cluster with the global minimum value onto the optimized FeN4C. 180 After that, Pt was obtained. x @FeN4C 180 Model.

[0016] Step 4, for Pt x @FeN4C 180 The model undergoes structural optimization to obtain the doped model with the lowest energy.

[0017] Step 4.1.1: Set the structure optimization parameters, including the plane wave cutoff energy, K-point selection, preset criteria for electronic self-consistent iteration and ion relaxation convergence. The convergence criteria for electronic self-consistent iteration and ion relaxation are set to convergence to an energy of 10. -5 eV and atomic forces converge to The DFT-D3 method (D represents dispersion) was used to analyze FeN4C.180 The interatomic interactions in the model were corrected using Grimme's van der Waals (vdW).

[0018] Step 5: Perform self-consistent calculations on the optimized models, and calculate Pt. x @FeN4C 180 The difference between the energy of the structure and the energy of the model before integration, i.e., E(pt) x @FeN4C 180 )-E(pt x )-E(FeN4C 180 ), obtain the binding energy Eb, and determine Pt x @FeN4C 180 Whether the model can exist stably; a stable structure can only be formed when the binding energy of the material is less than zero, and the more negative the binding energy, the more stable the structure.

[0019] Step 6, in Pt x @FeN4C 180 Based on the premise that the model can exist stably, determine Pt. x @FeN4C 180 Model in ORR4e - Catalytic performance under the mechanism;

[0020] Step 6.1, after optimization, Pt x @FeN4C 180 In the model, an adsorption model for ORR intermediate species *O, *OH, and *OOH on the active Fe site is constructed;

[0021] Step 6.2: Optimize the structure of the *O, *OH, and OOH models, with the parameter settings the same as in Step 2;

[0022] Step 6.3: After completing the structural optimization, perform static self-consistent calculations to obtain the energies of the *O, *OH, and *OOH models;

[0023] Step 6.4, Calculate ORR 4e - The free energy change ΔG and the thermodynamic overpotential ηη at equilibrium potential for each path in the path;

[0024] Step 6.5: Draw the ORR reaction path free energy diagram and compare the ORR thermodynamic overpotential ηη of each model;

[0025] Step 6.6: Determine the catalytic performance of each model in ORR based on the comparison results, and determine Pt. 10 @FeN4C 180 The catalytic effect is the best.

[0026] Step 7: Calculate Ptx @FeN4C 180 The density of states and differential charge density plots were used to infer the strength of binding between each model and the intermediate species in ORR, thus revealing the intrinsic reasons for the changes in ORR catalytic performance.

[0027] In the above scheme, ORR 4e - The mechanism is as follows:

[0028] O2+H + +e - →*OOH (Formula 1)

[0029] *OOH+H + +e - →*O+H2O (Formula 2)

[0030] *O+H + +e - -→*OH (Equation 3)

[0031] *OH+H + +e - →H2O (Equation 4)

[0032] The method for calculating thermodynamic overpotential is as follows:

[0033]

[0034] Where e represents the elementary charge, and ΔG1, ΔG2, ΔG3, and ΔG4 are ORR 4e - The Gibbs free energy of the reaction in Equations 1 to 4 of the mechanism is at an equilibrium potential of 1.23V.

[0035] Because the present invention employs the above-mentioned technical means, it has the following beneficial effects:

[0036] This invention eliminates the need for actual experiments, overcoming the complexity of existing experimental techniques regarding ORR equipment and related operations. By employing a density functional theory (DFT)-based method, this invention successfully improves the ORR catalytic performance of FeN-doped fullerenes by coating FeN-doped fullerenes with Pt atom clusters of different sizes, thereby reducing the amount of Pt used. Specifically, the Pt atom clusters coated with 10 Pt atom clusters... 10 @FeN4C 180 The ORR catalytic effect is the best. Attached Figure Description

[0037] Figure 1 The FeN4C constructed in the computational simulation of this invention 180 Model diagram;

[0038] Figure 2This is a diagram of a Pt cluster structure with 5-8 atoms according to the present invention;

[0039] Figure 3 The Pt of this invention x @FeN4C 180 Structure diagram of (x=5-13);

[0040] Figure 4 The Pt of this invention x @FeN4C 180 Binding energy diagram of (x=5-13)

[0041] Figure 5 This is the ORR reaction pathway free energy diagram of the present invention;

[0042] Figure 6 The FeN4C of this invention 180 The electronic density of states (DOS) plot;

[0043] Figure 7 The Pt of this invention 10 @FeN4C 180 The electronic density of states (DOS) plot;

[0044] Figure 8 The FeN4C of this invention 180 The differential charge density plot;

[0045] Figure 9 The Pt of this invention 10 @FeN4C 180 The differential charge density plot. Detailed Implementation

[0046] The embodiments of the present invention will be described in detail below. Although the present invention will be described and illustrated in conjunction with some specific embodiments, it should be noted that the present invention is not limited to these embodiments. On the contrary, any modifications or equivalent substitutions made to the present invention should be covered within the scope of the claims of the present invention.

[0047] Furthermore, to better illustrate the present invention, numerous specific details are set forth in the following detailed embodiments. Those skilled in the art will understand that the present invention can be practiced without these specific details.

[0048] The following example illustrates the application of this method, including the following steps:

[0049] Step 1. Using Device Studio software, in C... 180In the model, a carbon ring containing six C atoms has its top and bottom four C atoms replaced with N atoms, one of the two C atoms on the left and right is deleted, and the remaining C atom is replaced with an Fe atom. The Fe atom is set to... - The N-bond length is Establish FeN4C 180 Unit cell, such as Figure 1 As shown, its unit cell parameters are

[0050] Step 2. Add FeN4C 180 The model underwent structural optimization to obtain the lowest-energy doped model; the plane wave cutoff energy was set to 450 eV, the K-point was chosen as a 1×1×1 Gama point, and the convergence criteria for electronic self-consistent iteration and ion relaxation were set to convergence to an energy of 10 eV. -5 eV and atomic forces converge to The DFT-D3 method (D represents dispersion) was used, and Grimme's van der Waals (vdW) correction was performed.

[0051] Step 3. Use Ablcuster software to search for the global minimum of Pt clusters. Use the Sutton-Chen potential as the force field and search for Pt clusters with 5-13 atoms. The cluster model with the global minimum found is as follows: Figure 2 As shown.

[0052] Step 4. Wrap the searched Pt cluster with the global minimum value onto the optimized FeN4C. 180 Then, the Device Studio software was used to optimize the structure of each model to obtain the doped model with the lowest energy; the parameter settings were the same as in step 2.

[0053] Step 5. Calculate Pt separately using static self-consistency. x @FeN4C 180 FeN4C 180 Pt x Energy, binding energy E b The calculation method is E b =E(Pt) x @FeN4C 180 )-E(FeN4C 180 )-E(Pt x ), where E(Pt) x @FeN4C 180 ) represents Pt x Doping into FeN4C 180 The energy after that, E(FeN4C) 180 ) is FeN4C 180 Energy, E(Pt) x ) is Ptx The binding energy of a material. A stable structure can only be formed when the binding energy is less than zero, and the more negative the binding energy, the more stable the structure. The obtained binding energy is as follows: Figure 3 As shown, the binding energies are all negative, indicating that the Pt cluster is doped with FeN4C. 180 It is feasible in practice, and it can be preliminarily determined that the larger the cluster, the more stable the binding.

[0054] Step 6. After optimization, Pt x @FeN4C 180 In the model, *O, *OH, and *OOH models are constructed on Fe atoms. The structures of these models are then optimized using the same parameter settings as in step 2. After optimization, static self-consistency is performed to obtain the energies of the *O, *OH, and *OOH models, and the ORR (4e⁻¹) is calculated. - Plot the ORR reaction path free energy diagram using the path free energy changes ΔG and thermodynamic overpotential η for each path. Figure 4 As shown, it is concluded that in Pt x @FeN4C 180 The ORR catalytic effect of both is superior to that of FeN4C. 180 And Pt 10 @FeN4C 180 The catalytic effect is the best.

[0055] Step 7. Calculate FeN4C separately. 180 and Pt10@FeN4C 180 The density of states diagram after O adsorption, as shown below. Figure 6 As shown in Figure 7, it can be seen that after coating the Pt atom cluster, the overlap of the density of states orbitals of Fe and O atoms at the adsorption sites increases, and the interaction between the two atoms is enhanced; the calculation of FeN4C 180 and Pt 10 @FeN4C 180 Differential charge density plot, such as Figure 8 and Figure 9 As shown, it can be seen that after fullerenes are coated with Pt clusters, the number of Fe atoms loses more electrons, indicating that the Pt clusters act as "electron acceptors," accepting electrons donated by the exposed Fe atoms. 10 @FeN4C 180 The loss of Fe electrons enhances the desorption of *OH, thereby improving the ORR catalytic performance, which confirms the results obtained.

[0056] After screening, Pt was ultimately selected as the model with the best ORR catalytic activity. 10 @FeN4C 180 .

[0057] The free energy G is calculated as follows: ΔG = ΔE + ΔZPE - TΔS, where ΔE, ΔZPE, and ΔS are the reaction energies calculated using static self-consistency, ΔE is the change in zero-point energy during the reaction, ΔZPE is the change in entropy during the reaction, and T is the temperature (298.15 K). The ΔS values ​​for the *O, *OH, and *OOH models are very small and can be ignored. The ΔS values ​​for H2O and H2 can be obtained by searching a database.

[0058] The method for calculating differential charge density is: Δρ=ΔρPt x @FeN4C 180 -ΔρFeN4C 180 -ΔρPt x , where ΔρPt x @FeN4C 180 ΔρFeN4C 180 ,ΔρPt x For Pt x @FeN4C 180 The change in charge density, ρFeN4C 180 The change in charge density, Pt x The change in charge density.

[0059] This invention provides a method for improving the ORR catalytic performance of FeN-doped fullerenes coated with Pt clusters of different sizes. The core of this method lies in utilizing density functional theory (DFT) to construct and optimize FeN4C... 180 A model was developed, and Pt clusters of different sizes were coated onto it to improve the ORR catalytic performance of fullerenes. Specifically, this method includes the following key steps:

[0060] 1. Model Building and Optimization: FeN4C was built using Device Studio software. 180 The model was developed and its structure optimized to obtain a stable doping model.

[0061] 2. Pt cluster coating: In optimized FeN4C 180 The model contains Pt clusters of different sizes, forming Ptx@FeN4C 180 The model was then redesigned and its structure optimized again.

[0062] 3. Stability calculation: Calculate Pt x @FeN4C 180 The binding energy is used to assess its stability. A binding energy less than zero indicates a stable structure, and the more negative the binding energy, the more stable the structure.

[0063] 4. ORR process free energy calculation: Calculate ORR 4e -The free energy of the pathway is used to determine the catalytic performance of different ORR models by comparing their thermodynamic overpotentials (η). The lower the η, the better the ORR catalytic effect.

[0064] 5. Intrinsic Cause Analysis: By calculating the density of states (DPS) and differential charge density (DCD) plots, the intrinsic causes of changes in catalytic performance are analyzed. The DPS plot analyzes the strength of the binding between the model and the ORR intermediate species, while the DCD plot analyzes the charge gain and loss.

[0065] The advantage of this invention is that it eliminates the need for actual experiments; the effect of different Pt cluster sizes on ORR catalytic performance can be studied through theoretical simulation, providing a new calculation method for improving the ORR catalytic performance of fullerenes.

[0066] In summary, this invention has studied the effect of coating FeN-doped fullerenes with Pt clusters of different sizes on ORR catalytic performance through theoretical simulation, providing a new calculation method for improving the ORR catalytic performance of fullerenes.

[0067] The above description discloses only one preferred embodiment of the present invention, and should not be construed as limiting the scope of the present invention. Those skilled in the art will understand that all or part of the processes of the above embodiments can be implemented, and equivalent changes made in accordance with the claims of the present invention are still within the scope of the invention.

Claims

1. A method for improving the ORR catalytic performance of FeN-doped fullerenes coated with Pt clusters of different sizes, characterized in that: The specific steps are as follows: Step 1: Using Device Studio software, modify the C++ code. 180 The model was doped with FeN4 to construct FeN4C 180 Model; Step 2, FeN4C 180 The model undergoes structural optimization to obtain a stable doping model; Step 3, in the optimized FeN4C 180 The model is filled with Pt clusters of different sizes to obtain Pt x @FeN4C 180 Model; Step 4, for Pt x @FeN4C 180 The model undergoes structural optimization to obtain a stable doping model; Step 5: Perform self-consistent calculations on the optimized models, and calculate Pt. x @FeN4C 180 The difference between the energy of the structure and the energy of the model before integration, i.e., E(Pt) x @FeN4C 180 ) - E(Pt x ) - E(FeN4C 180 ), to obtain the binding energy E b Determine Pt x @FeN4C 180 Can the model exist stably? Step 6, in Pt x @FeN4C 180 Based on the premise that the model can exist stably, calculate its ORR 4e. - Reaction pathway free energy diagram to determine Pt x @FeN4C 180 The catalytic performance of the model; Step 7: Calculate Pt x @FeN4C 180 The density of states and differential charge density plots were used to infer the strength of binding between each model and the intermediate species in ORR, thus revealing the intrinsic reasons for the changes in ORR catalytic performance.

2. The method for improving the ORR catalytic performance of FeN-doped fullerenes coated with Pt clusters of different sizes according to claim 1, characterized in that: Step 1.1: In a carbon ring containing six C atoms in the C180 model, replace the top and bottom four C atoms with N atoms; Step 1.2: Delete one of the two C atoms on the left and right, and replace the remaining C atom with an Fe atom to construct FeN4C. 180 Unit cell.

3. The method for improving the ORR catalytic performance of FeN-doped fullerenes coated with Pt clusters of different sizes according to claim 1, characterized in that: The structure optimization parameters are set, including preset criteria for plane wave cutoff energy, K-point selection, electronic self-consistent iteration, and ion relaxation convergence. The convergence criteria for electronic self-consistent iteration and ion relaxation are set to convergence to an energy of 10. -5 eV and atomic force converged to 0.02 eV / Å; the DFT-D3 method was used to analyze FeN4C 180 The interatomic interactions in the model were corrected using Grimme's van der Waals.

4. The method for improving the ORR catalytic performance of FeN-doped fullerenes coated with Pt clusters of different sizes according to claim 1, characterized in that: Step 3.1: Use Abcluster software to search for the global minimum of Pt clusters, using the Sutton-Chen potential as the force field, and search for Pt clusters with 5-13 atoms; Step 3.2: Wrap the searched Pt cluster with the global minimum value onto the optimized FeN4C. 180 After that, Pt was obtained. x @FeN4C 180 The model has x values ​​ranging from 5 to 13.

5. The method for improving the ORR catalytic performance of FeN-doped fullerenes coated with Pt clusters of different sizes according to claim 1, characterized in that: The structure optimization parameters are set, including preset criteria for plane wave cutoff energy, K-point selection, electronic self-consistent iteration, and ion relaxation convergence. The convergence criteria for electronic self-consistent iteration and ion relaxation are set to convergence to an energy of 10. -5 The atomic force converged to 0.02 eV / Å; the Pt was analyzed using the DFT-D3 method. x @FeN4C 180 The interatomic interactions in the model were corrected using Grimme's van der Waals.

6. The method for improving the ORR catalytic performance of FeN-doped fullerenes coated with Pt clusters of different sizes according to claim 1, characterized in that: Step 6.1, after optimization, Pt x @FeN4C 180 In the model, an adsorption model for ORR intermediate species *O, *OH, and *OOH on the active Fe site is constructed; Step 6.2: Optimize the structure of the *O, *OH, and OOH models, with the parameter settings the same as in Step 2; Step 6.3: After completing the structural optimization, perform static self-consistent calculations to obtain the energy of different catalyst *O, *OH, and *OOH models; Step 6.4, Calculate ORR 4e - The free energy change ΔG and the thermodynamic overpotential η at equilibrium potential for each path in the path; Step 6.5: Draw the ORR reaction path free energy diagram and compare the ORR thermodynamic overpotential η of each model; Step 6.6: Determine the catalytic performance of each model in ORR based on the comparison results, and determine Pt. 10 @FeN4C 180 The catalytic effect is the best.

7. The method for improving the ORR catalytic performance of FeN-doped fullerenes coated with Pt clusters of different sizes according to claim 1, characterized in that, ORR 4e - The mechanism is as follows: O2+ H + + e - → *OOH (Formula 1) *OOH + H + + e - → *O + H2O (Equation 2) *O + H + + e - → *OH (Formula 3) *OH + H + + e - → H2O (Equation 4) The method for calculating thermodynamic overpotential is as follows: ] in Represents the elementary charge. ORR 4e - The Gibbs free energy of the reaction in Equations 1 to 4 of the mechanism is at an equilibrium potential of 1.23V.

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