Design method, structure and device of mixed cluster structure based on first principle

Abstract

The application discloses a design method, a structure and a device of a mixed cluster based on a first principle. 13 The icosahedral Cu cluster is taken as a matrix, a plurality of isomers are constructed by replacing Cu atoms with Rh atoms, first principle calculation is performed by using a Materials Studio software, the most stable structure is screened out, and parameters such as average binding energy, mixing energy, second-order energy difference and energy gap are calculated to evaluate the thermodynamic stability and chemical stability of the cluster. The calculation result shows that the Rh2Cu 11 and Rh3Cu 10 cluster has significant negative mixing energy, higher second-order energy difference and moderate energy gap, and has a good balance between thermodynamic stability and catalytic activity, and can be used as an ideal candidate material for catalysis and adsorption applications. The application provides theoretical guidance for component design and performance prediction of Rh-Cu cluster materials.

Description

Technical Field

[0001] This invention relates to the field of quantitative material design, and more particularly to a design method, structure, and apparatus for hybrid cluster structures based on first principles. Background Technology

[0002] Hybrid clusters are nanoparticles formed by two or more different metal atoms through metallic bonds. They possess multiple metallic properties and exhibit various size, quantum size, and synergistic effects, making them widely applicable in catalysis, sensing, and other fields. Performance, especially stability, is a key factor in evaluating their application value. Current research methods fall into two categories: experimental testing and theoretical calculation. Both have limitations and shortcomings, making it difficult to meet the precise research needs of clusters of specific sizes and hindering their industrialization.

[0003] Rh is a rare and precious metal with excellent adsorption and catalytic performance; Cu is low in cost, has good stability and abundant reserves, and can form mixed clusters with Rh through synergistic effects such as electron transfer, which can improve its stability.

[0004] In existing technologies, density functional theory (DFT) methods have been used to analyze the gas stability of Rh–Cu mixed clusters. For example, the paper "DFT study of the interaction between carbon monoxide and Rh–Cu bimetallic nanoclusters" discloses a theoretical method for studying the stability of Rh–Cu mixed clusters. This existing technique first constructs Rh–Cu mixtures with different composition ratios. x Cu 4-x A mixed cluster model (x=0-4) was developed, forming five different alloy configurations by varying the number of Rh and Cu atoms: x=0 (pure Cu4 cluster), x=1 (Rh1Cu3 cluster), x=2 (Rh2Cu2 cluster), x=3 (Rh3Cu1 cluster), and x=4 (pure Rh4 cluster). Density functional theory (DFT) was then used to optimize the geometric structure of each cluster model. Through multiple energy iterations, the spatial positions of atoms were gradually adjusted until the stable structure with the lowest energy was obtained. This stable structure represents the thermodynamically stable state of the cluster, thus determining the optimal atomic arrangement for Rh-Cu mixed clusters with different ratios. This provides a reliable basic model for subsequent studies on the adsorption performance and catalytic activity of the clusters. The existing technical models are not rational or scientific enough, and the stability analysis is limited to thermodynamic stability without considering chemical stability. The analysis is too singular and not comprehensive enough to fully reflect the actual stability performance of clusters. The key to improving the systematicness and practicality of cluster research is to rationally select the matrix structure and take into account multi-dimensional stability analysis. Summary of the Invention

[0005] To address the aforementioned problems, this invention employs the icosahedron, which possesses unique structural stability and electronic properties, as the matrix. Leveraging the inherent advantages of icosahedral clusters, a new Rh... m Cu n (m+n=13) Hybrid Cluster Structure and Rh Based on First Principles m Cu n (m+n=13) Design method for hybrid cluster structures. This invention comprehensively and accurately reflects the actual stability performance of clusters through multi-dimensional stability analysis, making up for the core deficiencies of existing technologies, further improving the systematicness and practicality of the research, and providing more reliable support for the development of Rh-Cu hybrid clusters.

[0006] m+n=13 is Rh m Cu n The critical size of mixed clusters is characterized by unique structure and electronic properties, and stability performance that differs from other sizes. However, they are difficult to prepare and characterize, and existing methods cannot accurately determine their stability performance, resulting in unclear correlation between structure and performance, which limits their application in catalysis, sensing and other fields.

[0007] To achieve the objectives of this invention, the technical solution adopted is as follows: The first aspect of this invention provides an Rh based on first principles. m Cu n A design method for a (m+n=13) hybrid cluster structure, characterized in that the hybrid cluster structure is composed of m Rh atoms and n Cu atoms, and has an icosahedral framework structure, where 1≤m≤12 and n=13-m. The method includes the following steps: Step S1: Using an icosahedron Cu 13 Using clusters as the matrix, one or more Cu atoms are replaced with Rh atoms at different substitution sites, where the number of Rh atoms m satisfies 1 ≤ m ≤ 12, resulting in multiple Rh atoms. m Cu n (m+n=13) isomers of mixed clusters; Step S2: Using first-principles calculation software, calculate the Rh obtained in step S1. m Cu n Structural optimization calculations were performed on the (m+n=13) mixed cluster isomers to obtain structurally stable Rh. m Cu n (m+n=13) Mixed cluster structure; Step S3: Using first-principles calculation software, calculate the Rh obtained in step S2. m Cu n First-principles thermodynamic and chemical property calculations were performed on the (m+n=13) mixed cluster structure.

[0008] In some embodiments, the first-principles calculation software is based on the density functional theory (DFT) framework and uses the PBE-DFT method for calculation.

[0009] In some embodiments, the first principle calculation software is Materials Studio.

[0010] In some embodiments, the method for performing structural optimization calculations on the cluster structure in step S2 is to perform structural optimization calculations on the Rh obtained in step S1. m Cu n Energy testing was performed on the (m+n=13) mixed cluster isomers to obtain the isomer with the lowest energy. Preferably, Materials Studio Dmol was used. 3 The module undergoes energy testing.

[0011] In some embodiments, the calculation of the thermodynamic and chemical properties includes the average binding energy (E0). b ), mixed energy (E) Mix ), second-order energy difference (∆2E) and bandgap (E) g The calculation formula is as follows:

[0012] In some embodiments, step S3 calculates the average binding energy (E) of the cluster. b ), mixed energy (E) Mix ), second-order energy difference (∆2E) and bandgap (E) g ), and analyze the average binding energy (E) of the clusters. b ), mixed energy (E) Mix ), second-order energy difference (∆2E) and bandgap (E) g The value of ) is used to determine Rh. m Cu n (m+n=13) Properties of mixed cluster materials.

[0013] The second aspect of the present invention provides an Rh based on first principles. m Cu n A (m+n=13) hybrid cluster structure, wherein the hybrid cluster structure is composed of m Rh atoms and n Cu atoms, has an icosahedral framework structure, where 1≤m≤12 and n=13-m, is characterized by being obtained by the following design method, the method comprising the following steps: Step S1: Using an icosahedron Cu 13 Using clusters as the matrix, one or more Cu atoms are replaced with Rh atoms at different substitution sites, where the number of Rh atoms m satisfies 1 ≤ m ≤ 12, resulting in multiple Rh atoms.m Cu n (m+n=13) isomers of mixed clusters; Step S2: Using first-principles calculation software, calculate the Rh obtained in step S1. m Cu n Structural optimization calculations were performed on the (m+n=13) mixed cluster isomers to obtain structurally stable Rh. m Cu n (m+n=13) Mixed cluster structure; Step S3: Using first-principles calculation software, calculate the Rh obtained in step S2. m Cu n First-principles thermodynamic and chemical property calculations were performed on the (m+n=13) mixed cluster structure.

[0014] In some embodiments, the first-principles calculation software is based on the density functional theory (DFT) framework and uses the PBE-DFT method for calculation.

[0015] In some embodiments, the first principle calculation software is Materials Studio.

[0016] In some embodiments, the method for performing structural optimization calculations on the cluster structure in step S2 is to perform structural optimization calculations on the Rh obtained in step S1. m Cu n Energy testing was performed on the (m+n=13) mixed cluster isomers to obtain the isomer with the lowest energy. Preferably, Materials Studio Dmol was used. 3 The module undergoes energy testing.

[0017] In some embodiments, the calculation of the thermodynamic and chemical properties includes the average binding energy (E0). b ), mixed energy (E) Mix ), second-order energy difference (∆2E) and bandgap (E) g ) calculation.

[0018] In some embodiments, step S3 calculates the average binding energy (E) of the cluster. b ), mixed energy (E) Mix ), second-order energy difference (∆2E) and bandgap (E) g ), and analyze the average binding energy (E) of the clusters. b ), mixed energy (E) Mix ), second-order energy difference (∆2E) and bandgap (E) g The value of ) is used to determine Rh. m Cu n (m+n=13) Properties of mixed cluster materials.

[0019] A third aspect of the present invention provides a method for determining Rh m Cu n A device for (m+n=13) mixing cluster material properties, comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the Rh described in the first aspect. m Cu n (m+n=13) Design method for hybrid cluster structures.

[0020] A fourth aspect of the present invention provides a computer-readable storage medium storing a computer program thereon, characterized in that, when the computer program is executed by a processor, it implements the Rh described in the first aspect. m Cu n (m+n=13) Design method for hybrid cluster structures.

[0021] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) This invention uses first-principles calculations to systematically study the effects of different contents of Rh and Cu on Rh. m Cu n The stability of the (m+n=13) cluster structure is affected, providing guidance and a basis for composition design for the development of Rh-Cu cluster materials with excellent catalytic and adsorption properties.

[0022] (2) Rh2Cu 11 and Rh3Cu 10 The clusters exhibit significant negative mixing energies and relatively high second-order energy differences. Furthermore, both clusters possess moderate band gaps, implying a good balance between thermodynamic stability and chemical reactivity. These properties make Rh₂Cu… 11 and Rh3Cu 10 These are ideal candidates for further research into their catalytic and adsorption properties. This invention provides a basis for the development of Rh... m Cu n (m+n=13) Cluster materials provide support. Attached Figure Description

[0023] The invention will now be described in more detail with reference to embodiments and the accompanying drawings. Figure 1 For Rh based on first principles m Cu n (m+n=13) Design method for hybrid cluster structures; Figure 2 For Rh m Cu n (m+n=13) Stable isomer structures in cluster structures; Figure 3 For Rh m Cu n (m+n=13) The average binding energy E of the cluster structure (A) b (B) Mixed energy E mix The second-order energy difference Δ2E between (C) and (C) Figure 4 For Rh m Cu n (m+n=13) Cluster structure band gap E g . Detailed Implementation

[0024] The invention will be described in more detail below with reference to the embodiments and the accompanying drawings, which will enable those skilled in the art to have a more complete understanding of the invention, but does not limit the invention in any way. Example

[0025] A first-principles-based Rh m Cu n A design method for a (m+n=13) hybrid cluster structure, wherein the hybrid cluster structure is composed of m Rh atoms and n Cu atoms, and has an icosahedral framework structure, where 1≤m≤12 and n=13-m, the method includes the following steps: Step S1: Using an icosahedral Cu13 cluster as a matrix, replace one or more Cu atoms with Rh atoms at different substitution sites, where the number of Rh atoms m satisfies 1 ≤ m ≤ 12, resulting in multiple RhCu atoms. 12 ,Rh2Cu 11 ,Rh3Cu 10 ,Rh4Cu9,Rh5Cu8,Rh6Cu7,Rh7Cu6,Rh8Cu5,Rh9Cu4,Rh 10 Cu3,Rh 11 Cu2,Rh 12 Isomers of Cu; Step S2: Using the first-principles calculation software Materials Studio, process the Rh obtained in step S1. m Cu n Structural optimization calculations were performed on the (m+n=13) hybrid cluster structure to obtain a structurally stable Rh. m Cu n (m+n=13) hybrid cluster structure; specifically, the structure optimization calculation is to optimize the Rh obtained in step S1. m Cu n Energy tests were performed on the (m+n=13) cluster structure to obtain the structure of the lowest-energy isomer, which is the structurally stable Rh. m Cu n(m+n=13) hybrid cluster structure. Materials Studio Dmol was used. 3 Module for Rh m Cu n Energy tests were performed on the (m+n=13) cluster structure. The structurally stable isomer structure was also tested. Figure 2 As shown.

[0026] The Materials Studio software, based on the density functional theory (DFT) framework, employs the PBE-DFT method, considering spin and electronic gradient corrections. The calculations utilize a dual numerical polarization (DNP 3.5) basis set, and weak intermolecular interactions are considered through DFT-D correction. A 20 Å cubic supercell is used to avoid periodic interactions. Strict convergence criteria are set for the energy measurements: an energy convergence threshold of 1 × 10⁻⁶. -5 Hartley, maximum force 0.002 Hartley / Å, maximum displacement 5×10 -3 The orbital cutoff radius is set to 4.6 angstroms.

[0027] Step S3: Using the first-principles calculation software Materials Studio, process the Rh obtained in step S2. m Cu n (m+n=13) First-principles thermodynamic and chemical property calculations were performed on the mixed cluster structure to determine its thermodynamic and chemical stability.

[0028] The parameters are set to be consistent with those in step S2, and the average binding energy (E) of the hybrid cluster structure is calculated. b ), mixed energy (E) Mix ), second-order energy difference (∆2E) and bandgap (E) g The average binding energy (E) of the hybrid cluster structure was calculated. b ), mixed energy (E) Mix The second-order energy difference (∆2E) represents the thermodynamic stability of the hybrid cluster structure, and the results are shown in the appendix. Figure 3 As shown.

[0029] For binding energy (E) b The hybrid cluster structure exhibits good stability with a binding energy between 2.3 and 3.2 eV. Because Rh atoms exhibit a higher binding energy than copper atoms, Rh... m Cu n The total binding energy of the cluster increases with the number of Rh atoms (m), indicating that the structural stability increases with the number of Rh atoms (or decreases with the number of Cu atoms n).

[0030] For mixed energy (E Mix Negative values ​​indicate a tendency for atomic mixing, while positive values ​​indicate segregation. All Rh... m Cu n The mixing energies of the cluster structures are all negative, indicating good mixing behavior. This is especially true for Rh₂Cu. 11 Rh3Cu 10 Rh4Cu9 exhibits a large negative E mix The values ​​indicate that these cluster structures have a strong tendency to mix and high stability.

[0031] For the second-order energy difference (∆2E), the Rh m Cu n The ∆2E value of the cluster fluctuates to some extent with the increase of the number of Rh atoms (m). Specifically, Rh3Cu... 10 The cluster has the largest ∆2E and the highest stability, while Rh2Cu 11 Clusters have the second highest ∆2E, indicating relatively high stability.

[0032] Bandgap (E) g E is an important indicator of the chemical stability of the hybrid cluster structure; a larger E g A more difficult electronic transition corresponds to higher chemical stability, while a smaller ET indicates a more difficult electronic transition, corresponding to higher chemical stability. g This indicates easier electronic transitions and higher chemical reactivity. Figure 4 The band gap of the hybrid cluster structure is shown as a function of the number of Rh atoms (m). Notably, Rh₂Cu 11 and Rh3Cu 10 E g The value is approximately 0.7 eV, indicating that both cluster structures maintain a perfect balance between chemical stability and appropriate reactivity.

[0033] In summary, Rh2Cu 11 and Rh3Cu 10 The clusters exhibit significant negative mixing energies and high second-order energy differences. Furthermore, both cluster structures possess moderate band gaps, implying a good balance between thermodynamic stability and chemical reactivity. These properties make Rh₂Cu… 11 and Rh3Cu 10 Becoming a better performing Rh m Cu n (m+n=13) hybrid cluster structure. Based on this performance, it is suitable for developing novel Rh... m Cu n The structure of the n(m+n=13) mixed cluster material is Rh2Cu 11 and Rh3Cu 10Cluster structure.

[0034] While the invention has been described herein with reference to specific embodiments, it should be understood that these embodiments are merely examples of the principles and applications of the invention. Therefore, it should be understood that many modifications can be made to the exemplary embodiments, and other arrangements can be designed without departing from the spirit and scope of the invention as defined by the appended claims. It should be understood that different dependent claims and features described herein can be combined in ways different from those described in the original claims. It is also understood that features described in conjunction with individual embodiments can be used in other described embodiments.

Claims

1. A design method for hybrid cluster structures based on first principles, characterized in that, The hybrid cluster structure is composed of m Rh atoms and n Cu atoms, and has an icosahedral framework structure, where 1≤m≤12 and n=13-m. The method includes the following steps: Step S1: Using an icosahedron Cu 13 Using clusters as the matrix, one or more Cu atoms are replaced with Rh atoms at different substitution sites, where the number of Rh atoms m satisfies 1 ≤ m ≤ 12, resulting in multiple Rh atoms. m Cu n (m+n=13) isomers of mixed clusters; Step S2: Using first-principles calculation software, calculate the Rh obtained in step S1. m Cu n Structural optimization calculations were performed on the (m+n=13) mixed cluster isomers to obtain structurally stable Rh. m Cu n (m+n=13) Mixed cluster structure; Step S3: Using first-principles calculation software, calculate the Rh obtained in step S2. m Cu n First-principles thermodynamic and chemical property calculations were performed on the (m+n=13) mixed cluster structure.

2. The method as described in claim 1, characterized in that, The first-principles calculation software is based on the density functional theory (DFT) framework and uses the PBE-DFT method for calculation.

3. The method as described in claim 1 or 2, characterized in that, The software used for the first principle calculation was MaterialsStudio.

4. The method as described in claim 1, characterized in that, The method for performing structural optimization calculations on the cluster structure in step S2 is to perform structural optimization calculations on the Rh obtained in step S1. m Cu n Energy tests were performed on the (m+n=13) mixed cluster isomers to obtain the isomer with the lowest energy.

5. The method as described in claim 4, characterized in that, Using Materials Studio Dmol 3 The module undergoes energy testing.

6. The method as described in claim 1, characterized in that, The calculations of the thermodynamic and chemical properties include the average binding energy (E). b ), mixed energy (E) Mix ), second-order energy difference (∆2E) and bandgap (E) g ) calculation.

7. A hybrid cluster structure based on first principles, characterized in that, Obtained by using the design method described in any one of claims 1-6.

8. The hybrid cluster structure as described in claim 7, characterized in that, The hybrid cluster structure is Rh2Cu 11 or Rh3Cu 10 Cluster structure.

9. A computing device based on a first-principles hybrid cluster structure, comprising a memory and a processor, characterized in that, The memory stores a computer program, and when the processor executes the computer program, it implements Rh as described in any one of claims 1 to 6. m Cu n (m+n=13) Design method for hybrid cluster structures.

10. A computer-readable storage medium storing a computer program thereon, characterized in that, When the computer program is executed by a processor, it implements Rh as described in any one of claims 1 to 6. m Cu n (m+n=13) Design method for hybrid cluster structures.

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