A high specific energy positive electrode material based on first-principle calculation

Abstract

This invention discloses a high-energy-density cathode material based on first-principles calculations, prepared using the following method: S1, determining the matrix phase and lattice constant of the Ni-Co-Mn ternary system; S2, introducing one or more heavy metal dopants into the matrix phase, constructing doping models under different doping concentrations using a homogeneous distribution model, forming multiple second-phase structure models under different doping elements and concentrations; S3, calculating the single-atom binding energy of each second-phase structure model and under different lattice constants, and evaluating the influence of different doping concentrations and doping elements on the structural stability of the material based on the magnitude of the single-atom binding energy. By introducing multiple heavy metal dopants and combining homogeneous distribution models, lattice constant optimization, and binding energy evaluation, the structural stability prediction and doping optimization of the Ni-Co-Mn ternary cathode material are achieved.

Description

Technical Field

[0001] This invention relates to the field of lithium-ion battery material design technology, specifically to a Ni-Co-Mn ternary cathode material based on first-principles calculations, and particularly to a design method that achieves precise control over the structural and thermal stability of the material by introducing heavy metal doping elements and combining homogeneous distribution modeling with first-principles energy calculations. Background Technology

[0002] Ni-Co-Mn ternary materials, as core materials for lithium-ion battery cathodes, are widely used in electric vehicles and energy storage systems due to their advantages of high specific capacity and low cost. However, the structural stability of ternary materials, especially high-nickel systems (such as NCM811), significantly restricts the improvement of battery performance. Taking the high-nickel ternary material NCM811 as an example, during charge and discharge, Ni²⁺, due to its similar ionic radius to Li⁺, easily migrates to lithium sites under high voltage, initiating cation mixing and causing the material to transform from a layered structure to a rock salt phase. This change causes lattice parameter contraction, narrowing the Li⁺ diffusion channels, increasing ion migration resistance, and thus accelerating capacity decay. Simultaneously, the active sites on the material surface undergo side reactions with the electrolyte, generating a thicker solid electrolyte interphase (SEI) film. This membrane not only consumes active lithium and reduces the battery's initial coulombic efficiency, but also exacerbates interfacial impedance with increasing cycle count, further affecting the battery's cycle life. Furthermore, materials in the charging state are prone to releasing lattice oxygen at high temperatures, triggering a violent exothermic reaction and posing a safety hazard of battery thermal runaway.

[0003] To address the aforementioned issues, existing technologies primarily improve material stability by coating the surface with inert coatings such as Al2O3 or ZrO2, or by doping with light metal ions such as Mg²⁺ or Al³⁺. However, surface coating increases interfacial impedance, leading to a decrease in battery rate performance; and light metal ions, due to their relatively similar electronegativity to Ni / Co / Mn, have limited influence on the regulation of the material's electronic structure. More importantly, both methods rely on experimental trial and error, lacking theoretical guidance for dopant selection, resulting in long development cycles, high costs, and difficulty in accurately analyzing the impact of dopant elements on lattice distortion and electronic structure at the atomic scale.

[0004] First-principles calculations, based on density functional theory, can simulate the interaction between dopant elements and the matrix material at the atomic level, accurately calculating key parameters such as lattice matching, bonding characteristics, and defect formation energy, providing theoretical support for material design. However, currently, for Ni-Co-Mn ternary materials, a quantitative model of the relationship between heavy metal doping (such as d-block elements like Cr, Fe, and Cu) and structural stability has not been established, and the selective doping mechanism at Ni / Co / Mn sites remains unclear, resulting in low efficiency of theoretical guidance for experiments. Therefore, a systematic design method based on first-principles calculations is needed to overcome the blindness of traditional trial-and-error methods and achieve precise control over the structural stability of ternary cathode materials. Summary of the Invention

[0005] This invention provides a high specific energy cathode material based on first-principles calculations. By theoretically calculating and screening heavy metal doping elements and concentrations, the crystal structure is optimized at the atomic scale, solving the problems of blind doping and inefficient stability control in existing technologies, and realizing the design of ternary cathode materials with high cycle life and high thermal stability.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A high-energy-density cathode material based on first-principles calculations includes the following steps: S1. Determine the optimal matrix phase structure and optimal lattice constant of the Ni-Co-Mn ternary system.

[0007] Methods for determining the optimal matrix phase structure and optimal lattice constant include: S11. For the preset crystal structure, it conforms to the general formula Li[Ni x Co y Mn 1-x-y The close-packed hexagonal crystal structure model of O2, where x and y are both values ​​greater than 0; S12. Set an arithmetic sequence containing multiple initial lattice constant values; S13. Using first-principles calculations, calculate the total structural energy and the energy of a single atom one by one under the unit cell model and using each initial lattice constant value in the arithmetic sequence. S14. Based on the initial lattice constant values ​​and corresponding single atom energy data obtained in step S13, a lattice constant-single atom energy curve is generated by fitting. S15. Based on the lattice constant-single atom energy curve, determine the lattice constant value corresponding to the lowest system energy, and determine it as the optimal lattice constant of the crystal structure. S16. For a variety of different preset crystal structures, repeat steps A1 to A5 to obtain the lowest single atom energy of each crystal structure under its optimal lattice constant. S17. By comparing the lowest single-atom energies obtained from the various different crystal structures, the crystal structure with the lowest single-atom energy is determined as the optimal structure of the matrix phase.

[0008] The initial value range for the lattice constant is 2.84-2.94 Å. If the calculation does not yield a parabola, such as a curve that decreases monotonically overall, the current scanning range is too small and has not yet covered the minimum energy point. The lattice constant range should be appropriately expanded to the right. If the curve increases monotonically overall, the value is too large, and the initial value should be adjusted to the left to cover the minimum value range.

[0009] S2. Introduce one or more heavy metal doping elements into the matrix phase. The heavy metal doping elements are selected from one or more of Fe, Ni, Cr, Zr, and Cu. Construct doping models under different doping concentrations using a homogeneous distribution model to form multiple second-phase structure models under different doping elements and different doping concentrations.

[0010] Specifically, an element other than the matrix element selected in step S1 is chosen as the dopant element, and the matrix element and the dopant element form the second phase. To improve the computational efficiency of doped structure construction, a homogeneous distribution model based on the Special Quasi-Random Structure (SQS) method is preferred. This method optimizes the atomic pair correlation function within a finite supercell to approximate an ideal random solid solution as closely as possible, thereby achieving a uniform distribution of heavy metal elements in the Ni-Co-Mn ternary phase. In specific implementation, the elemental occupancy probability of transition metal sites is defined using VASP software combined with the ATAT toolkit, directly controlling the doping concentration. Unlike the traditional supercell single-atom replacement method, this method does not specify fixed atomic positions but achieves homogenization through statistical distribution. For the non-integer number of atoms corresponding to the doping concentration (e.g., 0.16), probabilistic occupancy allocation is performed in multiple sets of equivalent arrangement configurations, and an energy-weighted average is applied to ensure that the model conforms to the preset concentration gradient at the atomic scale.

[0011] In step S2, the doping concentration is set to include a site fraction x = 0%, 1%, 2%, 3%, 4%, 5%, corresponding to the number of heavy metal atoms n introduced into the supercell. x =0, 0.16, 0.32, 0.48, 0.64, 0.8.

[0012] S3. Calculate the binding energy of individual atoms for each second-phase structure model under different lattice constants, and evaluate the influence of different doping concentrations and doping elements on the structural stability of the material based on the magnitude of the binding energy of individual atoms.

[0013] Specifically, before calculating the single-atom binding energy of the second-phase structure model in step S3, the optimal structure and optimal lattice constant of the second-phase structure model are first determined. The specific steps are as follows: Based on first principles, the total structural energy and single-atom energy of each second-phase structure model under different lattice constants are calculated. The lattice constant corresponding to the lowest total structural energy is determined through fitting, and the crystal structure with the lowest single-atom energy under that lattice constant is selected as the optimal second-phase structure model under that doping condition, i.e., under specific doping elements and doping concentrations. That is, for each combination of doping elements and doping concentrations, the total structural energy and single-atom energy of the second-phase structure model under each lattice constant are calculated. A fitting curve is obtained for the lattice constant and single-atom energy data; the fitting curve is an upward-opening parabola, and the optimal lattice constant corresponding to the energy minimum point is obtained. Wherein, the single-atom energy ( , , , The energy is obtained by constructing an isolated atom model with a sufficiently large vacuum layer; specifically, a single atom is placed at the center of a cubic vacuum box with a side length of not less than 15 Å, the interatomic interaction is turned off and spin polarization calculation is performed, and the total energy obtained is the single-atom reference energy of the element, which is used to eliminate the interference of the environmental potential field and as the energy benchmark for calculating the binding energy.

[0014] The formula for calculating the second binding energy is:

[0015] in, It is the binding energy of a single atom; The total structural energy of the second-phase structure model; and , , , These are the single-atom energies of Li, O, Co, Mn, and the dopant element X, respectively. n Li 、n O 、n Co 、n Mn 、n X These represent the atomic numbers of Li, O, Co, Mn, and dopant element X in the second phase structure, respectively, with values ​​greater than or equal to 0; X is the dopant heavy metal element, which can be selected from Fe, Ni, Cr, Zr, and Cu.

[0016] This indicates that the second phase is unstable and difficult to form. The larger the value, the less recommended it is to introduce the second phase, and vice versa. That is, the larger the absolute value of the binding energy of a unit atom, the more stable the structure; the greater the binding energy, the less stable the structure, and the less recommended it is to introduce the corresponding doping scheme.

[0017] The beneficial effects of this invention are: 1. This invention constructs a structure conforming to the general formula Li[Ni] x CoyMn 1-x-y A close-packed hexagonal crystal structure model of O2 was constructed, and multiple lattice constants were set in an arithmetic sequence. Combined with first-principles calculations, a lattice constant-energy fitting curve (E-V curve) was built to achieve high-precision screening of the optimal lattice constants and structure types in the crystal structure. This improves the accuracy of Ni-Co-Mn ternary cathode material structure design, avoids empirical errors, and ensures the acquisition of an initial matrix model with the lowest structural energy and highest stability.

[0018] 2. This invention replaces the traditional "single-point substitution supercell model" with a "homogeneous distribution model." Instead of replacing dopant atoms in fixed positions, it achieves an approximately uniform random distribution of dopant elements within the supercell by setting statistical occupancy probabilities. This avoids the accumulation of local stress fields caused by excessive concentration of dopant atoms, improves the convergence and stability of doped structure calculations, and more closely approximates the physical state of actual solid solution materials.

[0019] 3. By introducing the binding energy of a unit atom as an evaluation index, a quantitative model is established based on the principle of energy conservation. Combining first-principles calculations, the total structural energy and the atomic energies of the constituent elements are used to determine the probability of doping structure formation. When the binding energy is negative and has a large absolute value, it indicates a more stable structure and a superior doping scheme; when the binding energy is positive, the corresponding structure is unstable and not recommended. This method avoids traditional experimental trial-and-error screening and establishes a quantitative standard for predicting structural stability at the theoretical level.

[0020] 4. By systematically setting different doping concentrations (e.g., x = 0~5%) and multiple heavy metal elements (Fe, Ni, Cr, Zr, Cu) in the second-phase design, this method possesses a universal combinatorial screening structure and supports expansion into a high-throughput theoretical platform. Technical benefits: Significantly improves the development efficiency of novel doped systems, significantly reduces experimental resource investment and screening time, and is particularly suitable for pre-screening applications involving multi-element doping. Attached Figure Description

[0021] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0022] Figure 1 Crystal structure model and energy fitting curve; Figure 2 This is a schematic diagram of a homogeneous doping model constructed based on the SQS method. Figure 3 This is a schematic diagram of the Cr-Fe co-doped structure. Detailed Implementation

[0023] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0024] Example 1: This example provides a high-energy-density cathode material based on first-principles calculations, which can efficiently evaluate the impact of different doping schemes on the material's structural stability, providing theoretical guidance for practical material development. It was prepared using the following method: S1. Determine the optimal matrix phase, optimal lattice constant, and fundamental properties of the matrix structure. Fundamental properties include individual atom energy, binding energy, etc. Figure 1 As shown; First, the matrix structure of the Ni-Co-Mn ternary system is determined. The matrix structure adopts a hexagonal close-packed (HCP) crystal structure with the general formula Li[Ni] x Co y Mn 1-x-y O2, where x=y≈0.33. In this embodiment, an initial unit cell is constructed based on NCM111 (x≈y≈0.33), and then extended along the a and b axes to form a 2×2×1 supercell model for subsequent doping simulation.

[0025] Regarding the selection of crystal structure type, this embodiment calculates the energy of a single atom for different possible crystal structures (such as layered type and spinel type) under their optimal lattice constant, and selects the structure with the lowest energy as the optimal crystal structure.

[0026] A set of arithmetic lattice constants (a = 2.85–2.95 Å, step size 0.02 Å) was established. VASP software was used to perform structural optimization and energy calculations on each set of lattice constants, obtaining lattice constant-to-total energy data. A Python fitting tool was then used to perform curve fitting on this data. The fitting results showed that the system energy was lowest when a ≈ 2.91 Å, and the corresponding lattice constant was the optimal lattice constant. Then, the individual atom energies of different lattice structures at their optimal lattice constants were compared to obtain the crystal structure with the lowest individual atom energy, which was then taken as the optimal matrix phase structure.

[0027] There are many ways to determine the optimal structure and basic properties of the matrix phase using first-principles calculations. This embodiment provides one option: one method is to perform structure optimization and energy calculations using VASP software combined with the CASTEP module under the Linux operating system. Another method is to perform modeling and energy calculations using the Material Studio software environment. Because the first-principles calculation methods used are different, the specific implementation steps may also be different. This module does not require manual setting of possible lattice constants when determining the optimal lattice constant, but the ultimate goal remains the same: to obtain the basic properties to assist in the design of Ni-Co-Mn ternary materials, which can serve as the basis for lattice parameter optimization and doping evaluation.

[0028] S2. Construction and analysis of the doping model.

[0029] Based on the optimal matrix structure determined in step S1, Cr dopant is introduced, and second-phase models with different doping concentrations are constructed: Dopant element: Cr; Doping method: replacing Co atoms in the transition metal layer; Doping concentration is set to x = 0%, 1%, 2%, 3%, 4%, 5%, corresponding to the number of doped atoms n. Cr =0, 0.16, 0.32, 0.48, 0.64, 0.80; The doping method adopts a homogeneous distribution model, that is, to simulate the random and uniform distribution of doped atoms without introducing local stress concentration.

[0030] To avoid the impact of excessive proximity between dopant atoms on computational stability due to localized stress fields, all dopant atoms are arranged in the supercell to satisfy the minimum spacing condition, and the interactions between dopant atoms are not considered.

[0031] like Figure 2 As shown, the constructed 2×2×1 supercell was used to simulate structures with different doping concentrations.

[0032] To reduce computational workload, each doping model is further optimized. First, the optimal structure and optimal lattice constant of the second-phase structure model are determined. The specific steps are as follows: For each combination of doping elements and doping concentrations, the total structural energy and individual atom energy of the second-phase structure model under each lattice constant are calculated. The lattice constant and individual atom energy data are fitted with a curve. The fitted curve is an upward-opening parabola. The optimal lattice constant and the corresponding optimal structure corresponding to the energy minimum point are obtained.

[0033] S3. Perform structural stability analysis.

[0034] For each doping condition, the binding energy of a single atom in the optimal second-phase structure model is calculated:

[0035] in, It is the binding energy of a single atom; The total structural energy of the second-phase structure model; and , , , These are the single-atom energies of Li, O, Co, Mn, and the dopant element X, respectively. n Li 、n O 、n Co 、n Mn 、n X These represent the atomic numbers of Li, O, Co, Mn, and dopant element X in the second-phase structure, respectively, with values ​​greater than or equal to 0; X is a doped heavy metal element, which can be selected from Fe, Ni, Cr, Zr, and Cu.

[0036] In this embodiment, Cr was selected as the doping element, and the variation with concentration is shown in Table 1 below.

[0037] 0% -5.02 1% -5.09 2% -5.13 3% -5.11 4% -5.06 5% -4.98 It can be seen that as the Cr doping concentration increases, the binding energy first decreases and then increases, indicating that the structure is most stable at a concentration of 2%.

[0038] This embodiment uses first-principles calculations to obtain the structural energy and binding energy under different doping conditions, realizing a quantitative assessment of the structural stability of Ni-Co-Mn ternary materials. It has the following technical advantages: it can skip a large number of experimental trial and error processes, significantly improving the efficiency of material development; the trend of binding energy change is clear, and the influence of doping concentration on stability can be accurately determined; and the use of a homogeneous distribution model improves the versatility and physical reliability of the simulation.

[0039] Example 2: In this example, based on the optimal matrix structure of the Ni-Co-Mn ternary system established in Example 1, a variety of transition metals or metalloid elements (including Fe, Zr, and Al) are introduced as doping components to construct multiple sets of doped structure models. The structural stability of each doped system is quantitatively evaluated by first-principles calculations to verify the influence of different doping elements on the material binding energy and lattice stability.

[0040] Doping model construction: The matrix structure adopts the same 2×2×1 layered supercell model as in Example 1; the doping concentration is set to 2%, corresponding to a single doped atom replacing a Co atom in the supercell; the selected doping elements include single elements of Fe, Zr, and Al; the doping positions are consistent with the aforementioned Cr doping model, and are distributed at equal intervals to reduce local stress interference; the remaining modeling parameters (lattice constant search range, structure optimization settings, etc.) are consistent with those in Example 1.

[0041] Calculation process: VASP software is used for structure optimization and energy calculation; lattice constant is fitted using Python tools; the binding energy of a single atom is calculated based on the total energy of the structure and the energy of isolated atoms; and the structural stability is compared under different doping elements.

[0042] Binding energy calculation results and analysis: The effect of doping elements on the structural binding energy is shown in the following table (Table 2): Fe -5.11 improve The crystal lattice is uniform and there is no significant distortion. Zr -5.07 Stability slightly improved Lattice expansion, with significant local O displacement. Al -4.96 reduce Lattice contraction leads to increased local distortion. Cr (comparison) -5.13 Optimal The crystal lattice is the most stable, and the ions are evenly distributed. Table 2 shows that Cr doping remains the optimal solution for improving stability, with the lowest binding energy (-5.13 eV / atom) at a doping concentration of 2%. Fe doping exhibits good stability, with a binding energy slightly lower than Cr, and does not cause significant lattice distortion, demonstrating promising engineering application prospects. Although Zr doping has a high binding energy, it easily causes local lattice expansion, which may adversely affect electrochemical performance. Al doping leads to an increase in system binding energy and a decrease in structural stability, and is not recommended, especially in layered structures.

[0043] By comparing the simulation results of different doping elements, it can be seen that the doping effect of different elements is significantly different, which is related to their atomic radius, electronegativity and valence state; Cr and Fe doping can improve the binding energy and optimize the lattice stability while maintaining the original layered structure; this method can eliminate unfavorable doping schemes in advance and save the experimental development cycle.

[0044] Therefore, this embodiment further verifies that the doping screening method based on first-principles calculation proposed in this application has high versatility and foresight, and provides a reliable theoretical basis for subsequent multi-doping synergistic optimization (such as Cr+Fe co-doping).

[0045] Example 3: Analysis of the optimization effect of Cr-Fe co-doping on the structural stability of Ni-Co-Mn ternary materials.

[0046] To further explore the influence of multi-element synergistic doping on the crystal structure stability of Ni-Co-Mn ternary materials, this embodiment introduces two transition metal elements, Cr and Fe, on the basis of the optimal matrix structure determined in Example 1, to simulate the structural performance change trend under the synergistic doping effect and evaluate their role in structural binding energy and lattice integrity.

[0047] Model building: Matrix structure: The Ni-Co-Mn ternary hexagonal close-packed structure (2×2×1 supercell) of Example 1 is adopted.

[0048] Doping method: Cr and Fe atoms replace Co atoms respectively, with a doping ratio of 1:1. The total doping concentration is still controlled at 2%, that is, Cr accounts for 1% and Fe accounts for 1%.

[0049] Doping distribution: Cr and Fe were introduced into two Co atomic sites that were far apart to reduce the local stress caused by their interaction.

[0050] Structural diagram: as shown Figure 3 As shown, Cr and Fe are located at Co sites in different layers, forming a stable doping distribution.

[0051] The calculation process remains the same as in Example 1: VASP software is used to optimize the structure and calculate the total energy of the double-doped supercell; Python tools are used to fit the lattice constant-single atom energy curve to determine the optimal lattice constant.

[0052] The binding energy per unit atom is calculated based on the following formula:

[0053] Compare the binding energies of single-doped (Cr or Fe) and double-doped (Cr-Fe) structures at the same doping concentration.

[0054] Cr single doping 2%:0% -5.13 optimal Extremely low Fe single doping 0%:2% -5.11 excellent Low Cr-Fe co-doping 1%:1% -5.15 Optimal No obvious local stress area

[0055] The calculation results show that the Cr-Fe co-doping has a lower binding energy (-5.15 eV / atom) than any single doping scheme, indicating that its crystal structure is more stable. Co-doping eliminates the slight structural distortion caused by Fe doping, while retaining the high stability advantage brought by Cr. The stress is uniformly distributed in all directions of the lattice, with no local ion over-dense or over-sparse regions, and the electron cloud uniformity is also better than that of single doping.

[0056] The multi-element synergistic doping scheme has a superimposed synergistic effect in improving structural stability; the combination of Cr and Fe not only retains their respective ability to stabilize the structure, but also forms a more reasonable band structure in the electronic structure, thereby improving the overall performance of the material; the results show that the doping modeling and calculation process proposed in this invention is also applicable to complex synergistic designs and has universal applicability; it is applicable to high-performance ternary cathode materials, lithium battery systems with high thermal stability requirements and other fields.

[0057] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A high-energy-density cathode material based on first-principles calculations, characterized in that, It was prepared using the following method: S1. Determine the matrix phase and lattice constant of the Ni-Co-Mn ternary system; S2. Introduce one or more heavy metal doping elements into the matrix phase, and construct doping models under different doping concentrations using a homogeneous distribution model to form multiple second-phase structure models under different doping elements and different doping concentrations. S3. Calculate the binding energy of a single atom under different lattice constants for each second-phase structural model, and evaluate the influence of different doping concentrations and doping elements on the structural stability of the material based on the magnitude of the binding energy of a single atom.

2. The high specific energy cathode material based on first-principles calculations according to claim 1, characterized in that, The heavy metal doping element is selected from at least one of Fe, Ni, Cr, Zr, and Cu.

3. The high specific energy cathode material based on first-principles calculations according to claim 2, characterized in that, The formula for calculating the binding energy of a single atom in the second-phase structure model is as follows: ； in, It is the binding energy of a single atom; The total structural energy of the second-phase structure model; and , , , These are the single-atom energies of Li, O, Co, Mn, and the dopant element X, respectively. n Li 、 n O 、n Co 、n Mn 、n X These represent the atomic numbers of Li, O, Co, Mn, and dopant element X in the second phase structure, respectively.

4. The high specific energy cathode material based on first-principles calculations according to claim 1, characterized in that, The larger the absolute value of the binding energy of a single atom, the more stable the structure; the larger the binding energy is, the less stable the structure is, and it is not recommended to introduce the corresponding doping scheme.

5. The high specific energy cathode material based on first-principles calculations according to claim 1, characterized in that, The specific steps for determining the optimal structure and optimal lattice constant of the matrix phase in step S1 are as follows: Constructing a matrix phase conforming to the general formula Li[Ni] x Co y Mn 1-x-y The close-packed hexagonal crystal structure model of O2 is used. A set of lattice constants is set, and the total energy of the structure and the energy of a single atom under different lattice constants are calculated based on first principles. The lattice constant corresponding to the lowest total energy of the structure is selected as the optimal lattice constant. Then, the crystal structure with the lowest energy of a single atom under the optimal lattice constant is selected as the optimal structure of the matrix phase.

6. The high specific energy cathode material based on first-principles calculations according to claim 5, characterized in that, The multiple lattice constants set in step S1 are arranged in an arithmetic sequence.

7. The high specific energy cathode material based on first-principles calculations according to claim 5, characterized in that, In step S1, the relationship curve between the lattice constant and the energy data of a single atom is fitted. This relationship curve is a parabola with the opening facing upwards. The optimal lattice constant corresponds to the minimum point of this relationship curve.

8. The high specific energy cathode material based on first-principles calculations according to claim 1, characterized in that, Before calculating the single-atom binding energy of the second-phase structure model in step S3, the optimal structure and optimal lattice constant of the second-phase structure model must be determined. The specific steps are as follows: Based on first principles, the total structural energy and individual atom energy of each second-phase structure model under different lattice constants are calculated. The lattice constant corresponding to the lowest total structural energy is determined by fitting, and the crystal structure with the lowest individual atom energy under that lattice constant is selected as the optimal second-phase structure model under that doping condition.

9. The high specific energy cathode material based on first-principles calculations according to claim 1, characterized in that, In step S2, the doping concentration is set to include a site fraction x = 0%, 1%, 2%, 3%, 4%, 5%, corresponding to the number of heavy metal atoms n introduced into the matrix phase obtained in step S1. x =0, 0.16, 0.32, 0.48, 0.64, 0.8.

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