Method for analyzing properties of heterostructures

Abstract

The embodiment of the present disclosure relates to a performance analysis method of a heterostructure, and belongs to the technical field of performance analysis of materials. The method comprises the following steps: constructing an original virtual structure model corresponding to the heterostructure according to an original structure model and a target lattice constant, and determining a target layer spacing of the heterostructure based on the original virtual structure model; adjusting the original virtual structure model based on the target layer spacing to obtain a target virtual structure model, and determining a first performance parameter of the heterostructure in a physical performance dimension and a second performance parameter of the heterostructure in a chemical performance dimension according to the target virtual structure model; analyzing the physical performance of the heterostructure according to the first performance parameter of the heterostructure in the physical performance dimension, and analyzing the chemical performance of the heterostructure according to the second performance parameter of the heterostructure in the chemical performance dimension. The present disclosure improves the accuracy of the performance analysis result.

Description

Technical Field

[0001] This disclosure relates to the field of material performance analysis technology, and more specifically, to a method for performance analysis of heterostructures. Background Technology

[0002] Existing performance analysis methods can only be implemented from a single dimension (such as structural stability or electrical conductivity), which results in low accuracy of the performance analysis results.

[0003] It should be noted that the information in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0004] The purpose of this disclosure is to provide a performance analysis method for heterogeneous structures, thereby overcoming, at least to some extent, the problem of low accuracy of performance analysis results due to limitations and defects in related technologies.

[0005] According to one aspect of this disclosure, a method for performance analysis of heterostructures is provided, comprising:

[0006] In response to the assignment operation of the lattice constant on the interactive interface, the target lattice constant required to construct the target virtual structure model corresponding to the heterostructure is determined, and the original structure model corresponding to the heterostructure is called.

[0007] Based on the original structural model and the target lattice constant, an original virtual structural model corresponding to the heterostructure is constructed, and the target interlayer spacing of the heterostructure is determined based on the original virtual structural model.

[0008] The original virtual structure model is adjusted based on the target interlayer spacing to obtain the target virtual structure model, and the first performance parameter of the heterostructure in the physical performance dimension and the second performance parameter in the chemical performance dimension are determined based on the target virtual structure model.

[0009] The physical properties of the heterostructure are analyzed based on the first performance parameter in the physical property dimension, and the chemical properties of the heterostructure are analyzed based on the second performance parameter in the chemical property dimension.

[0010] In one exemplary embodiment of this disclosure, the heterostructure is an APA-graphene / silicene heterostructure; in the APA-graphene / silicene heterostructure, the APA-graphene structure is located on top of the silicene structure; the target lattice constant includes a first lattice constant corresponding to the APA-graphene structure and a second lattice constant corresponding to the silicene structure; the original structural model includes a first original structural model corresponding to the APA-graphene structure and a second original structural model corresponding to the silicene structure.

[0011] In one example embodiment of this disclosure, based on the original structural model and the target lattice constant, an original virtual structural model corresponding to the heterostructure is constructed, including:

[0012] The first original structural model corresponding to the APA-graphene structure is called, and the first original structural model is adjusted based on the first lattice constant to obtain the APA-graphene lattice.

[0013] The second primitive structure model corresponding to the silicene structure is invoked, and the second primitive structure model is adjusted based on the second lattice constant to obtain the silicene unit cell structure; wherein, the second primitive structure model is the unit cell structure of silicon crystal;

[0014] The silicene unit cell structure is redefined to obtain an orthorhombic silicene structure that matches the APA-graphene lattice. Based on the APA-graphene lattice and the orthorhombic silicene structure, an original virtual structure model corresponding to the heterostructure is generated.

[0015] In one example embodiment of this disclosure, determining the target interlayer spacing of the heterogeneous structure based on the original virtual structural model includes:

[0016] Static self-consistent calculations are performed on the original virtual structure model to determine the target plane wave cutoff energy and target K-grid density required for performance analysis of the heterostructure.

[0017] The target interlayer spacing between the APA-graphene lattice and the orthorhombic silicene structure in the heterostructure is determined based on the target plane wave cutoff energy and the target K-grid density.

[0018] In one example embodiment of this disclosure, determining a first performance parameter in the physical performance dimension and a second performance parameter in the chemical performance dimension of the heterostructure based on the target virtual structure model includes:

[0019] Obtain the pseudopotential parameters of the elements included in the APA-graphene structure and the silicene structure in the target virtual structure model, and generate a PBE functional pseudopotential file corresponding to the heterostructure based on the pseudopotential parameters of the elements.

[0020] The convergence criterion parameters, optimization step size parameters, and lattice optimization parameters required for performance analysis of the heterostructure are determined, and an input parameter file is generated based on the convergence criterion parameters, optimization step size parameters, lattice optimization parameters, and target plane wave cutoff energy.

[0021] Generate a K-point file corresponding to the heterostructure based on the target K-grid density, and generate a cell position file corresponding to the heterostructure based on the target virtual structure model;

[0022] Based on the PBE functional pseudopotential file, input parameter file, K-point file, and cell position file, a first performance parameter of the heterostructure in the physical property dimension is determined; wherein, the first performance parameter includes at least one of the phonon spectrum, molecular dynamics, elastic constant, and differential charge density of the heterostructure.

[0023] Based on the PBE functional pseudopotential file, input parameter file, K-point file, and cell position file, a second performance parameter of the heterostructure in the chemical performance dimension is determined; wherein, the second performance parameter includes at least one of the following: the band structure of the heterostructure, the adsorption energy of a single Li ion, the migration and diffusion barrier of Li ions in the heterostructure, the theoretical voltage capacity of the heterostructure, and the open-circuit voltage.

[0024] In one example embodiment of this disclosure, a second performance parameter of the heterostructure in the chemical property dimension is determined based on the PBE functional pseudopotential file, input parameter file, K-point file, and unit cell position file, including:

[0025] Based on the PBE functional pseudopotential file, input parameter file, K-point file, and cell position file, the energy band of the heterostructure and the adsorption energy of a single Li ion are determined.

[0026] The most stable adsorption site in the heterostructure is determined based on the adsorption energy of a single Li ion, and the migration and diffusion barrier of a single Li ion in the heterostructure is determined based on the most stable adsorption site.

[0027] The maximum number of Li ions that can be adsorbed in a single heterostructure can be determined based on the adsorption energy of a single Li ion, and the theoretical voltage capacity and open-circuit voltage of the heterostructure can be determined based on the maximum number of Li ions that can be adsorbed in a single heterostructure.

[0028] In one exemplary embodiment of this disclosure, determining the most stable adsorption site in the heterostructure based on the adsorption energy of a single Li ion includes:

[0029] By iterating through the adsorption energies of individual Li ions, the adsorption energy of the smallest individual Li ion is extracted from the adsorption energies of individual Li ions, and the adsorption site corresponding to the adsorption energy of the smallest individual Li ion is taken as the most stable adsorption site in the heterostructure.

[0030] In one exemplary embodiment of this disclosure, determining the maximum number of Li ions that can be adsorbed in a single heterostructure based on the adsorption energy of a single Li ion includes:

[0031] In a single heterostructure, the number of Li ions to be adsorbed is increased sequentially, and the adsorption energy of each additional Li ion at the corresponding adsorption site is calculated.

[0032] When the adsorption energy of any adsorption site is positive, the number of Li ions currently present in a single heterostructure is taken as the maximum number of Li ions that can be adsorbed in a single heterostructure.

[0033] In one example embodiment of this disclosure, the physical properties of the heterostructure are analyzed based on a first performance parameter in the physical performance dimension, including:

[0034] If the phonon spectrum of the heterostructure does not include explicit imaginary frequencies, then the heterostructure is determined to have good dynamic stability; and / or

[0035] If the oscillation range of the total molecular energy in the molecular dynamics of the heterostructure is less than a preset threshold, then the heterostructure is determined to have good thermodynamic stability; and / or

[0036] If the elastic constant of the heterostructure is less than a preset elastic threshold, then the heterostructure is determined to have good mechanical stability; and / or

[0037] If the differential charge density of the heterostructure is less than a preset density threshold, then the heterostructure is determined to have good charge transfer properties.

[0038] In one exemplary embodiment of this disclosure, the chemical properties of the heterostructure are analyzed based on a second performance parameter in the chemical properties dimension, including:

[0039] If the energy band of the heterostructure can cross the Fermi level, then the heterostructure is determined to have good electronic conductivity; and / or

[0040] If the adsorption energy of a single Li ion at a certain position in the heterostructure is less than a preset adsorption threshold, then it is determined that the position in the heterostructure has stable adsorption properties; and / or

[0041] If the diffusion barrier between the heterostructures is less than a preset barrier threshold, then the heterostructure is determined to have good ion migration performance; and / or

[0042] If the theoretical voltage capacity of the heterostructure is greater than a preset capacity threshold, then the heterostructure is determined to have good capacitive performance; and / or

[0043] If the open-circuit voltage of the heterostructure is greater than a preset voltage threshold, then the heterostructure is determined to have good driving performance.

[0044] This disclosure provides a method for performance analysis of heterostructures. In response to an assignment operation on the lattice constant on an interactive interface, the method determines the target lattice constant required to construct a target virtual structure model corresponding to the heterostructure and calls the original structure model corresponding to the heterostructure. Then, based on the original structure model and the target lattice constant, the method constructs the original virtual structure model corresponding to the heterostructure and determines the target interlayer spacing of the heterostructure based on the original virtual structure model. Furthermore, the method adjusts the original virtual structure model based on the target interlayer spacing to obtain the target virtual structure model. Based on the target virtual structure model, the method determines a first performance parameter in the physical performance dimension and a second performance parameter in the chemical performance dimension of the heterostructure. Finally, the method analyzes the physical performance of the heterostructure based on the first performance parameter in the physical performance dimension and analyzes the chemical performance of the heterostructure based on the second performance parameter in the chemical performance dimension. Since the performance of the heterostructure can be determined from two different dimensions—chemical and physical—the accuracy of the obtained performance analysis results is improved.

[0045] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0046] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0047] Figure 1 The flowchart illustrates a performance analysis method for a heterostructure according to an exemplary embodiment of the present disclosure.

[0048] Figure 2 An example diagram schematically illustrates a first original structural model according to an exemplary embodiment of the present disclosure.

[0049] Figure 3An example diagram schematically illustrates a second original structural model according to an exemplary embodiment of the present disclosure.

[0050] Figure 4 An example diagram schematically illustrates a primitive virtual structure model according to an exemplary embodiment of the present disclosure.

[0051] Figure 5 The diagram illustrates a scenario example of a calculation process for a target plane wave cutoff energy according to an exemplary embodiment of the present disclosure.

[0052] Figure 6 The diagram illustrates a scenario example of a K-grid density calculation process according to an exemplary embodiment of the present disclosure.

[0053] Figure 7 The diagram illustrates a scenario example of a calculation process for a target interlayer spacing according to an exemplary embodiment of the present disclosure.

[0054] Figure 8 The flowchart illustrates a method for calculating a first performance parameter and a second performance parameter according to an example embodiment of the present disclosure.

[0055] Figure 9 An example diagram of a phonon spectrum obtained according to an exemplary embodiment of the present disclosure is shown schematically.

[0056] Figure 10 An example diagram illustrating the temperature and energy obtained according to an exemplary embodiment of this disclosure is shown.

[0057] Figure 11 An example diagram illustrating a differential charge density obtained according to an exemplary embodiment of the present disclosure is shown.

[0058] Figure 12 An example diagram illustrating a band structure result obtained according to an exemplary embodiment of the present disclosure is shown.

[0059] Figure 13 The diagram schematically illustrates a specific example of an adsorption site of a single Li ion on a heterostructure according to an exemplary embodiment of the present disclosure.

[0060] Figure 14 This diagram schematically illustrates an example of the migration and diffusion barrier of a single Li ion in a heterostructure obtained according to an exemplary embodiment of the present disclosure.

[0061] Figure 15 This diagram schematically illustrates the variation of adsorption energy of Li adsorbed between layers in an APA / Si heterostructure according to an exemplary embodiment of the present disclosure.

[0062] Figure 16The diagram illustrates an example of the relationship between the theoretical voltage capacity and the OCV of an APA / Si heterostructure according to an exemplary embodiment of the present disclosure.

[0063] Figure 17 The diagram schematically illustrates a block diagram of a performance analysis apparatus for a heterogeneous structure according to an exemplary embodiment of the present disclosure.

[0064] Figure 18 The diagram schematically illustrates an example structure of an electronic device for implementing a performance analysis method for heterogeneous structures according to an exemplary embodiment of the present disclosure. Detailed Implementation

[0065] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this disclosure more comprehensive and complete, and to fully convey the concept of the example embodiments to those skilled in the art. The described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a full understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced with one or more of the specific details omitted, or other methods, components, apparatus, steps, etc., can be employed. In other instances, well-known technical solutions are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0066] Furthermore, the accompanying drawings are merely illustrative of this disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0067] Lithium-ion batteries (LiBs), as high-performance energy storage devices, have been commercially applied globally, particularly in portable electronic devices and electric vehicles. Research shows that stable anode materials play a crucial role in improving the energy density, safety, and cycle life of lithium-ion batteries. Traditional graphite anode materials have a relatively low theoretical specific capacity (approximately 372 mAh / g), which severely restricts their further development in the field of lithium-ion batteries.

[0068] Silicene, a two-dimensional material composed of Group IV elements, exhibits excellent carrier mobility, tunable band gap, and high theoretical specific capacity (954 mA h / g), making it a highly attractive candidate for electrochemical applications. However, several challenges remain when using silicene as an anode material in lithium-ion batteries. For example, lithium-ion diffusion between silicene layers exhibits low mobility and a high migration barrier (0.75 eV). Furthermore, significant volume expansion / contraction occurs during charge-discharge cycling, greatly limiting its structural stability, and its relatively low mechanical strength is also a major factor restricting its practical application.

[0069] Existing research has used theoretical design to construct heterostructures (such as silicene / BN and silicene / Ca2N) to replace silicene, which can overcome its inherent defects while retaining the advantages of monolayer materials. However, defects such as poor thermal stability or insufficient capacity (e.g., only 339.46 mA h / g) still exist. Therefore, it is necessary to analyze the performance of heterostructures composed of graphene and silicene, and based on the obtained performance analysis results, determine whether the heterostructures composed of graphene and silicene can replace silicene to obtain high-performance lithium-ion batteries.

[0070] Based on this, this exemplary embodiment first provides a performance analysis method for heterogeneous structures. This method can run on terminal devices, servers, server clusters, or cloud servers, etc. Of course, those skilled in the art can also run the method disclosed herein on other platforms as needed, and this exemplary embodiment does not impose any special limitations on this. Specifically, refer to... Figure 1 As shown, the performance analysis method for this heterostructure may include the following steps:

[0071] Step S110. In response to the assignment operation of the lattice constant on the interactive interface, determine the target lattice constant required to construct the target virtual structure model corresponding to the heterostructure, and call the original structure model corresponding to the heterostructure.

[0072] Step S120. Based on the original structural model and the target lattice constant, construct an original virtual structural model corresponding to the heterostructure, and determine the target interlayer spacing of the heterostructure based on the original virtual structural model;

[0073] Step S130. Adjust the original virtual structure model based on the target interlayer spacing to obtain the target virtual structure model, and determine the first performance parameter of the heterostructure in the physical performance dimension and the second performance parameter in the chemical performance dimension based on the target virtual structure model.

[0074] Step S140. Analyze the physical properties of the heterostructure based on the first performance parameter in the physical property dimension, and analyze the chemical properties of the heterostructure based on the second performance parameter in the chemical property dimension.

[0075] In the aforementioned method for analyzing the performance of heterostructures, the target lattice constant required for constructing a target virtual structure model corresponding to the heterostructure is determined in response to the assignment operation of the lattice constant on the interactive interface, and the original structure model corresponding to the heterostructure is invoked. Then, based on the original structure model and the target lattice constant, the original virtual structure model corresponding to the heterostructure is constructed, and the target interlayer spacing of the heterostructure is determined based on the original virtual structure model. Subsequently, the original virtual structure model is adjusted based on the target interlayer spacing to obtain the target virtual structure model, and the first performance parameter of the heterostructure in the physical performance dimension and the second performance parameter in the chemical performance dimension are determined based on the target virtual structure model. Finally, the physical performance of the heterostructure is analyzed based on the first performance parameter in the physical performance dimension, and the chemical performance of the heterostructure is analyzed based on the second performance parameter in the chemical performance dimension. Since the performance of the heterostructure can be determined from two different dimensions, namely chemical performance and physical performance, the accuracy of the obtained performance analysis results is improved.

[0076] The performance analysis method for heterostructures described in the exemplary embodiments of this disclosure will be explained and described in detail below with reference to the accompanying drawings.

[0077] First, the heterostructure involved in the exemplary embodiments of this disclosure will be explained and described. Specifically, the heterostructure described in the exemplary embodiments of this disclosure is an APA-graphene (Anti-Polyzulene Graphene, unit cell containing 40 C atoms) / silicene (unit cell containing 2 Si atoms) heterostructure; at the same time, in this APA-graphene / silicene heterostructure, the APA-graphene structure is located on top of the silicene structure; the structural unit cell of the constructed APA-graphene / silicene (APA / Si) contains 40 C atoms and 16 Si atoms.

[0078] In one example embodiment, the theoretical capacity of the aforementioned silicene (Si) is extremely high, but its poor cycling performance hinders its practical application. APA-graphene (APA) exhibits a unique negative Poisson's ratio (NPR) effect. Therefore, a systematic structural and electronic performance analysis was conducted on the feasibility of the APA-graphene / silicene (APA / Si) heterostructure as an anode material for lithium-ion batteries using first-principles calculations based on density functional theory (DFT). The results show that the APA / Si heterostructure has higher lithium-ion adsorption energy and ionic conductivity compared to pristine silicene and APA-graphene. Furthermore, during charge and discharge, APA-graphene can effectively buffer volume expansion, giving the APA / Si heterostructure excellent mechanical properties and helping to alleviate the volume expansion problem of silicene during lithium-ion insertion. The APA / Si heterostructure exhibits superior performance as an anode material, with a barrier height of only 0.12 eV. The lowest open-circuit voltage (OCV) is 0.40V, the total OCV is 0.701V, and the lithium storage capacity reaches 835.87 (mA h) / g, indicating that the APA / Si heterostructure is suitable as an anode material for lithium-ion batteries.

[0079] In one example embodiment, the first-principles calculation described above is based on the interaction between atomic nuclei and electrons, using quantum mechanics principles to numerically simulate the properties of matter, and directly solving the Schrödinger equation through adiabatic approximations, single-electron approximations, and other processing. All calculations in this example embodiment are performed using the Vienna Ab-initioSimulation Package (VASP), which uses a plane-wave basis set to consider pseudopotentials to perform calculations on periodic materials. The exchange-correlation functional is represented using the Perdew-Burke-Ernzerhof (PBE) functional with the generalized gradient approximation (GGA). Furthermore, in the actual calculations, a plane-wave cutoff energy of 500 eV and a 4*6*1 Γ-centered k-point grid are used, with an energy convergence criterion of 10. -5 eV, force convergence criterion is 0.03 Furthermore, to avoid periodic interactions, a setting can be made in the Z-axis direction. The vacuum layer; at the same time, considering the interlayer van der Waals interactions, DFT-D2 dispersion correction is adopted.

[0080] The following will combine Figures 2-4 right Figure 1 The performance analysis method for the heterostructure shown will be further explained and illustrated. Specifically:

[0081] In step S110, in response to the assignment operation of the lattice constant on the interactive interface, the target lattice constant required to construct the target virtual structure model corresponding to the heterostructure is determined, and the original structure model corresponding to the heterostructure is called.

[0082] Specifically, the target lattice constants described here include the first lattice constant corresponding to the APA-graphene structure and the second lattice constant corresponding to the silicene structure; the specific value of the first lattice constant can be... The specific value of the second lattice constant can be... Furthermore, the original structural models described herein may include a first original structural model corresponding to the APA-graphene structure and a second original structural model corresponding to the silicene structure; a specific example diagram of the first original structural model can be found in [reference needed]. Figure 2 As shown, a specific example diagram of the second original structural model can be found in [reference needed]. Figure 3 As shown.

[0083] In step S120, an original virtual structure model corresponding to the heterostructure is constructed based on the original structure model and the target lattice constant, and the target interlayer spacing of the heterostructure is determined based on the original virtual structure model.

[0084] In this example embodiment, firstly, an original virtual structure model is constructed. Specifically, this can be achieved as follows: A first original structure model (i.e., the allotrope model of graphene) corresponding to the APA-graphene structure is called, and the first original structure model is adjusted based on the first lattice constant to obtain the APA-graphene lattice. Then, a second original structure model corresponding to the silicene structure is called, and the second original structure model is adjusted based on the second lattice constant to obtain the silicene unit cell structure. The second original structure model is the unit cell structure of silicon crystal. The silicene unit cell structure is then redefined to obtain an orthorhombic silicene unit cell structure matching the APA-graphene lattice. Based on the APA-graphene lattice and the orthorhombic silicene unit cell structure, an original virtual structure model corresponding to the heterostructure is generated.

[0085] The following section will further explain and illustrate the specific process of determining the original virtual structure model. Specifically, in the process of modeling silicene, firstly, the cell structure of a silicon crystal is downloaded from the crystal structure library and optimized using VASP; secondly, the Cleave Surface function is used in Materials Studio to cut the optimized silicon crystal structure along the 111 plane, and then the cut structure is augmented with... The vacuum layer yielded a silane unit cell structure, which was then further optimized. Next, the Redefine lattice function in Materials Studio was used to redefine the silane unit cell lattice (specifically: a reverse (2 0 0), b direction (2 4 0), c reverse (0 0 1)) to make it an orthorhombic lattice. Then, the Redefine lattice function was used again to transform the x and y axis directions of the lattice (specifically: a reverse (0 -10), b reverse (10 0), c reverse (0 0 1)) to obtain an orthorhombic silane unit cell structure matching the APA-graphene lattice. Further, in the APA / Si heterostructure modeling process, the Build Layers function in Materials Studio was used first, with APA-graphene selected as the upper layer and orthorhombic silane as the lower layer, to build the APA / Si heterostructure and obtain the original virtual structure model (a specific structural example diagram can be found in [reference]). Figure 4 (as shown); then, export the structure file of the APA / Si heterojunction, and export the POSCAR file of the heterostructure in VESTA; where POSCAR is a file that can be recognized in VASP software.

[0086] Secondly, the target interlayer spacing of the heterostructure is determined based on the original virtual structural model, which can be achieved as follows: Static self-consistent calculations are performed on the original virtual structural model to determine the target plane wave cutoff energy and target K-grid density required for performance analysis of the heterostructure; based on the target plane wave cutoff energy and target K-grid density, the target interlayer spacing between the APA-graphene lattice and the orthorhombic silicene structure in the heterostructure is determined. Specifically, in determining the target interlayer spacing, static self-consistent calculations are first performed to determine the target plane wave cutoff energy ENCUT and the target K-grid density KPOINTS; during the determination of ENCUT, other parameters in the VASP input file INCAR remain unchanged, while the value of ENCUT is changed (200, 250, 300, 350, 400, etc.), and static self-consistent calculations are performed (a scenario example diagram of the specific calculation process can be found in the image). Figure 5 As shown), the optimal energy stability ENCUT is 500 eV. Furthermore, in determining KPOINTS, the VASP input file INCAR remains unchanged, while the KPOINTS file (121, 231, 341, 461, 581, etc.) is changed, and static self-consistent calculations are performed (a scenario example diagram of the specific calculation process can be found in [reference]). Figure 6As shown), the optimal KPOINTS for energy stability is 461. Secondly, in determining the interlayer distance (i.e., the target interlayer distance) of the heterostructure, the VASP input files INCAR, KPOINTS, and POTCAR remain unchanged, while the interlayer distances of the heterostructure in the structure file POSCAR are changed (1.9, 2.1, 2.3, 2.5, 2.7, etc.) for static self-consistent calculations are performed (a scenario example diagram of the specific calculation process can be found in [reference]). Figure 7 As shown), the optimal interlayer distance for energy stability is obtained as follows:

[0087] In step S130, the original virtual structure model is adjusted based on the target interlayer spacing to obtain the target virtual structure model, and the first performance parameter of the heterostructure in the physical performance dimension and the second performance parameter in the chemical performance dimension are determined based on the target virtual structure model.

[0088] In this example embodiment, the original virtual structure model is first adjusted to obtain the target virtual structure model. Specifically, in practical applications, the original interlayer spacing in the original virtual structure model can be directly replaced based on the target interlayer spacing to obtain the target virtual structure model. It should be noted that the reason for adjusting the interlayer spacing of the original virtual structure model is to configure a suitable spacing for the APA-graphene lattice and the orthorhombic silicene cell structure, so as to facilitate a better diffusion effect during subsequent lithium-ion diffusion, thereby improving the accuracy of the obtained performance analysis results.

[0089] Secondly, based on the target virtual structural model, the first performance parameter in the physical performance dimension and the second performance parameter in the chemical performance dimension of the heterostructure are determined; specifically, refer to... Figure 8 As shown, the specific calculation process for the first performance parameter and the second performance parameter may include the following steps:

[0090] Step S810: Obtain the pseudopotential parameters of the elements included in the APA-graphene structure and the silicene structure in the target virtual structure model, and generate a PBE functional pseudopotential file corresponding to the heterostructure based on the pseudopotential parameters of the elements.

[0091] Step S820: Determine the convergence criterion parameters, optimization step size parameters, and lattice optimization parameters required for performance analysis of the heterostructure, and generate an input parameter file based on the convergence criterion parameters, optimization step size parameters, lattice optimization parameters, and target plane wave cutoff energy.

[0092] Step S830: Generate a K-point file corresponding to the heterostructure based on the target K-grid density, and generate a cell position file corresponding to the heterostructure based on the target virtual structure model.

[0093] Step S840: Based on the PBE functional pseudopotential file, input parameter file, K-point file, and unit cell position file, determine the first performance parameter of the heterostructure in the physical performance dimension; wherein, the first performance parameter includes at least one of the phonon spectrum, molecular dynamics, elastic constant, and differential charge density of the heterostructure.

[0094] The following will explain the specific process for determining the first performance parameter. Specifically, in determining the first performance parameter, it is first necessary to perform structural relaxation on the target virtual structure model. During structural relaxation, it is necessary to obtain the PBE functional pseudopotential file, input parameter file, K-point file, and cell position file. The interlayer distance in the POSCAR cell position file mentioned here is the optimal interlayer distance obtained after testing. This interlayer distance is used to construct a heterogeneous structure model for structural relaxation optimization. The PBE functional pseudopotential file POTCAR mentioned here... Based on the element types and order in the unit cell structure file, corresponding pseudopotentials are extracted from the element pseudopotential library to form a pseudopotential file. The K-point file KPOINTS described here can be optimized to a density of 4*6*1 by considering computational accuracy and cost through convergence testing. The input parameter file INCAR described here can include ENCUT=500 (plane wave basis cutoff energy, in eV), EDIFF=10⁻⁵ (energy convergence criterion, in eV), and EDIFFG=-0.03 (stress convergence criterion, in eV). Based on the above files, the structural relaxation instructions are executed to obtain the structural relaxation results. Furthermore, the interlayer distance is calculated on the structural file CONTCAR after structural relaxation, and the results are the same as those from the initial interlayer distance convergence test. Moreover, the calculated binding energy of the heterojunction is negative, indicating that a stable heterostructure can be constructed. (The text also mentions various structural relaxation optimization methods, such as IBRION=2 (structural relaxation optimization method), ISIF=3 (simultaneous optimization of lattice size and atomic positions), ISPIN=1 (ignoring spin polarization), NSW=200 (maximum ionic steps of structural relaxation), NELM=150 (maximum electronic self-consistency steps), NELMIN=5 (minimum electronic self-consistency steps).

[0095] In one example embodiment, the specific calculation process of the phonon spectrum can be implemented as follows: The required input data are: Cell position file (POSCAR): The structure information file CONTCAR after structural relaxation is expanded by one time along the y-axis using the phonopy program, and then the resulting SPOSCAR file is renamed to POSCAR, which is the cell structure file for calculating the phonon spectrum; PBE functional pseudopotential file (POTCAR): According to the element types and order in the cell structure file, the corresponding pseudopotentials are extracted from the element pseudopotential library to form a pseudopotential file; K-point file (KPOINTS): Considering the calculation accuracy and cost, the K-point density used in the phonon spectrum calculation is 3*3*1; Input parameter file (INCAR): The basic parameter settings are the same as those for structural relaxation, such as ENCUT=500 (plane wave basis set cutoff energy, unit eV), ISIF=3 (simultaneously optimizes lattice size and atomic position), ISPIN=1 (spin polarization is not considered). Key parameters for phonon spectrum calculation include: EDIFF = 10⁻⁷ (energy convergence criterion, unit eV), EDIFFG = -0.01 (stress convergence criterion, unit eV). The input parameters are: IBRION = 8 (density functional perturbation theory considering symmetry), NSW = 1 (no structural relaxation), LREAL = F (calculation in reciprocal space), and POTIM = 0.2 (relaxation step size of 0.2fs). Further, a phonon spectrum calculation task is constructed based on the above input data. Executing this task yields the corresponding phonon spectrum calculation results. Furthermore, after obtaining the phonon spectrum calculation results, the result files OUTCAR and vasprun.xml can be processed and analyzed using the phonopy program to extract the phonon frequency information of the heterostructure and plot it. An example of the obtained phonon spectrum can be found in [reference needed]. Figure 9 As shown.

[0096] In one example embodiment, the specific calculation process of molecular dynamics can be implemented as follows: First, the required input data are: Cell position file (POSCAR): The structure information file CONTCAR after structural relaxation is expanded by one time along the y-axis using VEATA software, and then renamed POSCAR, which is the cell structure file for calculating molecular dynamics; PBE functional pseudopotential file (POTCAR): According to the element types and order in the cell structure file, the corresponding pseudopotentials are extracted from the element pseudopotential library to form a pseudopotential file; K-point file (KPOINTS): Considering the calculation accuracy and cost, only single Γ K-points (1*1*1) are used for calculation and analysis in molecular dynamics calculations; Input parameter file (INCAR): The basic parameter settings are the same as those for structural relaxation, such as ENCUT=500 (plane wave basis set cutoff energy, unit eV), EDIFF=10-5 (energy convergence standard, unit eV), EDIFFG=-0.03 (stress convergence standard, unit eV). The key parameters for molecular dynamics calculations are: NSW = 10000 (maximum number of ion steps, 10 ps for a 1 fs time step), IBRION = 0 (start molecular dynamics simulation), POTIM = 1 (1 fs time step), TEBEG = 300 (initial temperature, in K), TEEND (ending temperature, in K), SMASS = 0 (molecular dynamics simulation ensemble selected as NVT ensemble), and NBLOCK = 1 (output calculation results once per time step). Further, a molecular dynamics calculation task is constructed based on the above input data. Executing this task yields the corresponding molecular dynamics calculation results. Furthermore, after obtaining the molecular dynamics calculation results, the temperature and energy of each step can be extracted from the OUTCAR file. The results are then plotted and analyzed. The structural distortion can be observed from the CONTCAR file at the end of the simulation. The obtained temperature and energy plotting results can be referenced... Figure 10 As shown in the figure, observing the temperature and energy changes throughout the simulation process reveals that the energy and temperature fluctuate within a very small range throughout the molecular dynamics process. Moreover, the simulated structure does not exhibit atomic bond breaking or significant structural deformation, which demonstrates that the heterostructure possesses good thermodynamic stability and structural integrity.

[0097] In one example embodiment, the specific calculation process of the elastic constant can be implemented as follows: First, the required input data are: Cell structure file (POSCAR): The structure information file CONTCAR after structure relaxation, renamed to POSCAR, is the cell structure file of the elastic constant; PBE functional pseudopotential file (POTCAR): According to the element types and order in the cell structure file, the corresponding pseudopotentials are extracted from the element pseudopotential library to form a pseudopotential file; K-point file (KPOINTS): Through convergence testing, considering the calculation accuracy and calculation cost, the optimal K-point density is obtained as 4*6*1; Input parameter file (INCAR): The basic parameter settings are the same as those for structure relaxation, such as ENCUT=500 (plane wave basis set cutoff energy, unit eV), NSW=200 (maximum ion steps of structure relaxation), EDIFF=10-5 (energy convergence standard, unit eV), EDIFFG=-0.03 (stress convergence standard, unit eV). The key parameters for calculating elastic constants are: IBRION = 2 (structural relaxation optimization method), ISIF = 2 (optimizes only atomic positions), and ISPIN = 1 (does not consider spin polarization). Further, an elastic constant calculation task is constructed based on the above input data. Executing this task yields the corresponding elastic constant calculation results. During the execution of this task, a stress-strain file (VPKIT.in) needs to be applied: seven stresses are applied, namely -0.015, -0.010, -0.005, 0, 0.005, 0.010, and 0.015, with each independent elastic constant folder containing the file structure of these seven applied stresses. Furthermore, after the elastic constant calculation is completed, the elastic constant calculation results of the heterostructure can be processed using VASPKit's 201 function to obtain the stress matrix information of the heterostructure. Based on the data in the stress matrix and the two-dimensional material mechanical stability judgment criteria, the mechanical stability of the heterostructure is obtained.

[0098] In one example embodiment, the specific calculation process of differential charge density can be implemented as follows: First, the required input data are: Cell structure file (POSCAR): The structure information file CONTCAR after structure relaxation, renamed to POSCAR, which is the cell structure file 1 for differential charge density. APA-graphene and silicene are deleted from the POSCAR file to obtain cell structure files 2 and 3 for differential charge density calculation; PBE functional pseudopotential file (POTCAR): Based on the element types and order in the cell structure file, The pseudopotential file is composed of corresponding pseudopotentials extracted from the element pseudopotential library; K-point files (KPOINTS): considering computational accuracy and cost through convergence testing, the optimal K-point density is obtained as 4*6*1; Input parameter file (INCAR): the basic parameter settings are the same as those for structural relaxation; however, at this time, only electronic static self-consistent calculations are performed based on structural relaxation, and the key parameters are: NSW=0 (no structural relaxation optimization), LWAVE=T (determines the output wavefunction file WAVECAR), LCHARG (determines the output charge density file CHGCAR). Further, a differential charge density calculation task is constructed based on the above input data, and executing this task yields the corresponding differential charge density calculation results; even further, after performing static self-consistent calculations on cell position files 1, 2, and 3 respectively, the charge density files CHGCAR of the three structures are processed using VASPKit's 314 function to obtain the differential charge density of the heterostructure; an example diagram of the obtained differential charge density can be found in the reference diagram. Figure 11 As shown; it should also be noted that the differential charge density of the heterostructure clearly shows charge transfer from the APA-graphene layer to the silicene layer, indicating that there is a strong charge interaction between the heterostructure layers.

[0099] Step S850: Based on the PBE functional pseudopotential file, input parameter file, K-point file, and cell position file, determine the second performance parameter of the heterostructure in the chemical performance dimension; wherein, the second performance parameter includes at least one of the following: the band structure of the heterostructure, the adsorption energy of a single Li ion, the migration and diffusion barrier of Li ions in the heterostructure, the theoretical voltage capacity of the heterostructure, and the open circuit voltage.

[0100] Specifically, the calculation process for the second performance parameter of the heterostructure in terms of chemical properties can be achieved as follows: Based on the PBE functional pseudopotential file, input parameter file, K-point file, and unit cell position file, determine the band structure and the adsorption energy of a single Li ion in the heterostructure; determine the most stable adsorption site in the heterostructure based on the adsorption energy of a single Li ion, and determine the migration and diffusion barrier of a single Li ion in the heterostructure based on the most stable adsorption site; determine the maximum number of Li ions that can be adsorbed in a single heterostructure based on the adsorption energy of a single Li ion, and determine the theoretical voltage capacity and open-circuit voltage of the heterostructure based on the maximum number of Li ions that can be adsorbed in a single heterostructure.

[0101] In one example embodiment, the specific process of determining the most stable adsorption site can be achieved as follows: traversing the adsorption energies of the individual Li ions, extracting the smallest adsorption energy of a single Li ion from the adsorption energies of the individual Li ions, and taking the adsorption site corresponding to the smallest adsorption energy of a single Li ion as the most stable adsorption site in the heterostructure.

[0102] In one example embodiment, the specific calculation process for the maximum number of Li ions that can be adsorbed in a single heterostructure can be achieved as follows: the number of Li ions to be adsorbed is sequentially increased in the single heterostructure, and the adsorption energy of the increased single Li ion at the corresponding adsorption site is calculated; when the adsorption energy of any adsorption site is detected to be positive, the number of Li ions currently present in the single heterostructure is taken as the maximum number of Li ions that can be adsorbed in the single heterostructure.

[0103] The following section will further explain and illustrate the specific calculation process for the second performance parameter.

[0104] (1) The specific calculation process of the band structure in the second performance parameter can be achieved as follows: First, the required input data are: Cell structure file (POSCAR): The structure information file CONTCAR after structural relaxation, renamed to POSCAR, is the cell structure file for calculating the band structure; PBE functional pseudopotential file (POTCAR): According to the element types and order in the cell structure file, the corresponding pseudopotentials are extracted from the element pseudopotential library to form a pseudopotential file; K-point file (KPOINTS): The K-point density is 4*6*1 in electronic static self-consistency, and the high symmetry point K-grid of the Г-XSY-Г path is used in band structure calculation; Input parameter file (INCAR): The basic parameter settings are the same as those in structural relaxation; however, at this time, electronic static self-consistency and band structure calculation are performed based on structural relaxation. The key parameters for band structure calculation are: NSW = 0 (no structural relaxation optimization), LCHARG (determines the output charge density file CHGCAR), ICHARG = 11 (reads the statically self-consistent CHGCAR for band structure calculation), and NEDOS = 2000 (number of grid points for electronic density of states and dielectric function). Further, a band structure calculation task is constructed based on the above input data, and executing this task yields the corresponding band structure calculation results. During the execution of the band structure calculation task, a statically self-consistent calculation can be performed on the structurally relaxed heterostructure to obtain the charge density file CHGCAR. Then, the charge density information in the CHGCAR file is read for band structure calculation. The calculation results are then processed using VASPKit's 211 function to obtain the band structure results for the heterostructure. The obtained band structure results can be referenced... Figure 12 As shown.

[0105] (2) The specific calculation process for the adsorption energy of a single Li ion in the second performance parameter can be achieved as follows: First, the required input data is: Unit cell structure file (POSCAR): Based on the structure information file CONTCAR after structural relaxation, adsorb a Li ion at different positions within its unit cell, and then use Material... Studios and VESTA exported a series of POSCAR files for Li adsorption at different sites; PBE functional pseudopotential file (POTCAR): based on the element types and order in the cell structure file, the corresponding pseudopotentials were extracted from the element pseudopotential library to form a pseudopotential file; K-point file (KPOINTS): through convergence testing, considering computational accuracy and computational cost, the optimal K-point density was obtained as 4*6*1; Input parameter file (INCAR): the input parameters for single Li adsorption are consistent with the input parameters for structural relaxation; further, based on the above input data, a calculation task for the adsorption energy of a single Li ion is constructed, and the calculation result of the adsorption energy of the corresponding single Li ion can be obtained by executing the calculation task; it should also be noted that the calculation of the adsorption energy of a single Li ion is based on structural relaxation, and the structure of a Li adsorbed at different sites in the heterostructure is optimized. Static self-consistency is performed based on the optimized structure, and stable energy is extracted from the result file OUCAR of the self-consistency calculation. Then, the adsorption energy of different sites is calculated by the adsorption energy formula; the adsorption energy formula can be shown in the following formula (1):

[0106] E ad =E APA / Si+Li -E APA / Si -E Li ; Formula (1)

[0107] Among them, E ad E is the adsorption energy of a single Li ion. APA / Si+Li E represents the total energy of the heterostructure containing Li ions. APA / Si E represents the total energy of the heterostructure without Li ions. Li This represents the energy of a single Li ion in Li-bcc. A negative adsorption energy for a single Li ion indicates that the entire process is exothermic, meaning the adsorption site is stable; a smaller adsorption energy indicates greater stability. For specific examples of adsorption sites for single Li ions on heterostructures, please refer to [reference needed]. Figure 13 As shown.

[0108] (3) The specific calculation process of the migration and diffusion barrier of a single Li ion in a heterostructure can be achieved as follows: First, the required input data are: PBE functional pseudopotential file (POTCAR): Based on the element types and order in the unit cell structure file, the corresponding pseudopotentials are extracted from the element pseudopotential library to form a pseudopotential file; K-point file (KPOINTS): Through convergence testing, considering the calculation accuracy and cost, the optimal K-point density is obtained as 4*6*1; Input parameter file (INCAR): The basic parameter settings are the same as those for structural relaxation. The key parameters for calculating the diffusion barrier are: POTIM=0 (enable VTST optimization algorithm), LCLIMB=T (enable the CI-NEB climbing calculation method), IMAGES=n (n is the number of inserted intermediate structures), ICHAIN=0 (enable NEB method). Secondly, based on the input data mentioned above, a calculation task for the migration and diffusion barrier of a single Li ion in a heterostructure is constructed. Executing this task yields the calculation results for the migration and diffusion barrier of a single Li ion in the heterostructure. It should be further noted that during the calculation process, firstly, the most stable adsorption site structure information file is obtained from the single Li adsorption calculation, and then the cell is expanded by one time along the y-axis to determine the diffusion path. Furthermore, since the crystal structure is periodically repeating, expanding the cell of the heterostructure will display two equally stable adsorption sites within a single lattice. Simultaneously, one Li is adsorbed at each of these two sites to obtain two structures, which are used as the initial and final states for the diffusion barrier calculation. Secondly, the initial and final states are relaxed to obtain two relaxed structure files (CONT). The process involves performing a CAR (Carrier Array) calculation, followed by using the VTST script `dist.pl` to determine the rationality of the optimized initial and final state structures (if the output of `dist.pl` is less than 5, it is generally considered reasonable). The value of `dist.pl` is divided by 0.8 to obtain the number of structures to be inserted between the initial and final states. Then, the VTST script `nebmake.pl` is executed to insert these intermediate structures, and structural optimization calculations are performed on each of these inserted structures sequentially. Finally, after all calculations are completed, the VTST script `nebbarrier.pl` generates the `neb.dat` file, which provides the diffusion barrier of a single Li ion. Processing this barrier yields the migration and diffusion barrier of a single Li ion in the heterostructure. For details on the migration and diffusion barrier of a single Li ion in the heterostructure, please refer to [link to relevant documentation]. Figure 14 As shown.

[0109] (4) The specific calculation process of the theoretical voltage capacity and open-circuit voltage (OCV) of the heterostructure can be achieved in the following way: First, the required input data are: Cell structure file (POSCAR): Based on the structure information file CONTCAR after structural relaxation, different amounts of Li (1, 4, 8, 12, 16, 21, 25, 29, 30) are adsorbed in its cell, and a series of POSCAR files with different adsorbed Li amounts are exported through Material Studios and VESTA; PBE functional pseudopotential file (POTCAR): According to the element types and order in the cell structure file, the corresponding pseudopotentials are extracted from the element pseudopotential library to form a pseudopotential file; K-point file (KPOINTS): Through convergence testing, considering the calculation accuracy and calculation cost, the optimal K-point density is obtained as 4*6*1; Input parameter file (INCAR): The input parameter settings for theoretical capacity and open-circuit voltage (OCV) are consistent with the input parameters for single adsorbed Li and structural relaxation. Secondly, based on the input data mentioned above, calculation tasks for the theoretical voltage capacity and open-circuit voltage of the heterostructure are constructed. Executing these tasks yields the theoretical voltage capacity and open-circuit voltage calculation results. It should be further noted that during the calculation process, structural relaxation is first performed on structures with different amounts of Li adsorbed in the heterostructure until, after structural optimization, the Li adsorbed in the heterostructure is excluded from the heterojunction surface or an adsorption energy becomes positive. At this point, the maximum amount of Li that can be accommodated in a single cell of the heterostructure is obtained, along with the optimized structures for different adsorption amounts during the gradual adsorption of Li. After processing the energy in the results, the open-circuit voltage and theoretical voltage capacity can be obtained. An example diagram showing the change in adsorption energy of Li adsorbed between the layers of the APA / Si heterostructure can be found in [reference needed]. Figure 15 As shown in the figure, an example diagram illustrating the relationship between theoretical voltage capacity and OCV can be referenced. Figure 16 As shown; the specific calculation formulas for theoretical voltage capacity and open-circuit voltage can be shown in the following formulas (2) and (3):

[0110]

[0111] Where C is the theoretical voltage capacity, M is the molar mass of the heterostructure, n is the maximum number of Li ions that can be adsorbed in a single heterostructure, F is the Faraday constant, specifically F = 26801 (mA h) / mol; z is the electron charge of the Li ions in the electrolyte, specifically z = 1, E ads E represents the adsorption energy of all Li ions. APA / Si+Li E represents the total energy of the heterostructure containing Li ions. APA / Si E represents the total energy of the heterostructure without Li ions. Li represents the energy of a single Li ion in Li-bcc.

[0112] In step S140, the physical properties of the heterostructure are analyzed based on the first performance parameter of the heterostructure in the physical property dimension, and the chemical properties of the heterostructure are analyzed based on the second performance parameter of the heterostructure in the chemical property dimension.

[0113] Specifically, the physical performance analysis process can be implemented as follows: if the phonon spectrum of the heterostructure does not include imaginary frequencies, then the heterostructure is determined to have good dynamic stability; and / or if the oscillation range of the total molecular energy in the molecular dynamics of the heterostructure is less than a preset range threshold, then the heterostructure is determined to have good thermodynamic stability; and / or if the elastic constant of the heterostructure is less than a preset elastic threshold, then the heterostructure is determined to have good mechanical stability; and / or if the differential charge density of the heterostructure is less than a preset density threshold, then the heterostructure is determined to have good charge transfer properties. In other words, in practical applications, on the one hand, if the acoustic and optical branches in the phonon spectrum do not appear below 0, it indicates that the phonon spectrum has no imaginary frequencies, suggesting a stable crystal structure. Similarly, if the phonon spectrum of the APA / Si heterostructure does not show imaginary frequencies, it indicates its excellent dynamic stability. On the other hand, if the main chain structure of the APA / Si heterostructure does not exhibit significant structural deformation, it indicates its excellent thermodynamic stability. It should be added that in practical applications, if the energy and temperature remain stable and fluctuate only within a very small range, and if the structure does not disintegrate, does not break bonds, and has minimal structural distortion after AIMD, it indicates that the structure has thermal stability. Furthermore, the elastic constants can determine the mechanical stability of the heterostructure. Specifically, since the APA / Si heterostructure is an orthorhombic lattice, it has only four independent elastic constants: C11, C12, C22, and C13. And C66; therefore, according to the mechanical stability criteria of two-dimensional materials (C11C22-C122>0 and C66>0), the heterostructure is judged to have mechanical stability; the specific elastic constants obtained can be shown in Table 1 below; in addition, the differential charge density of the APA / Si heterostructure along the z-axis in one dimension (1D) and three dimensions (3D) can be calculated; among them, there is obvious charge accumulation in the interface region of the silicene layer, while the APA-graphene layer shows obvious charge consumption, indicating that there is charge transfer from the APA-graphene layer to the silicene layer; further Bader charge analysis quantitatively confirmed that 0.24e charge was transferred from the APA-graphene layer to the silicene layer; in the process of practical application, since there is charge transfer from APA-graphene to silicene and the amount of charge transfer is quantitatively described by Bader charge analysis, it can be said that there is strong charge interaction at the interface of the APA / Si heterostructure.

[0114] Table 1

[0115] System <![CDATA[C 11 (N / m)]]> <![CDATA[C 12 (N / m)]]> <![CDATA[C 22 (N / m)]]> <![CDATA[C 66 (N / m)]]> <![CDATA[Y 2D (N / m)]]> <![CDATA[ 2D ]]> APA-graphene 96.42 -11.09 156.70 114.22 155.42 -0.115 Silicene 68.86 23.39 66.29 22.85 58.35 0.340 APA / Si 157.90 10.73 190.52 136.71 189.79 0.068

[0116] Furthermore, the specific analytical process for chemical performance analysis can be achieved as follows: if the energy band of the heterostructure can cross the Fermi level, then the heterostructure is determined to have good electronic conductivity; and / or if the adsorption energy of a single Li ion at a certain position in the heterostructure is less than a preset adsorption threshold, then that position in the heterostructure is determined to have stable adsorption; and / or if the diffusion barrier between the heterostructures is less than a preset barrier threshold, then the heterostructure is determined to have good ion migration performance; and / or if the theoretical voltage capacity of the heterostructure is greater than a preset capacity threshold, then the heterostructure is determined to have good capacitive performance; and / or if the open-circuit voltage of the heterostructure is greater than a preset voltage threshold, then the heterostructure is determined to have good driving performance. In other words, in practical applications, on the one hand, if an energy band in the band structure crosses the Fermi level, it indicates that the APA / Si heterostructure exhibits metallic properties and has good electronic conductivity. On the other hand, if the adsorption energy of a single Li ion is negative, it indicates that the entire process is exothermic, suggesting that the adsorption site is stable. Furthermore, the larger the negative value of the adsorption energy (i.e., the smaller the adsorption energy), the more stable the structure. Additionally, the smaller the diffusion barrier between heterostructures, the better the ion migration performance of the heterostructure. Moreover, the larger the theoretical voltage capacity, the better the capacitive performance, and the larger the open-circuit voltage, the better the driving performance. The preset adsorption threshold, preset barrier threshold, preset capacity threshold, and preset voltage threshold described here can be determined through expert experience or based on corresponding threshold prediction models; this example does not impose any special restrictions on this.

[0117] The following are embodiments of the apparatus disclosed herein, which can be used to execute embodiments of the method disclosed herein. For details not disclosed in the apparatus embodiments of this disclosure, please refer to the embodiments of the method disclosed herein.

[0118] This disclosure also provides an example embodiment of a performance analysis apparatus for heterogeneous structures. Specifically, refer to... Figure 17 As shown, the performance analysis device for this heterostructure may include a target lattice constant determination module 1710, an original virtual structure model determination module 1720, a performance parameter determination module 1730, and a performance analysis module 1740. Wherein:

[0119] The target lattice constant determination module 1710 can be used to determine the target lattice constant required to construct the target virtual structure model corresponding to the heterostructure in response to the assignment operation of the lattice constant on the interactive interface, and call the original structure model corresponding to the heterostructure; the original virtual structure model determination module 1720 can be used to construct the original virtual structure model corresponding to the heterostructure based on the original structure model and the target lattice constant, and determine the target interlayer spacing of the heterostructure based on the original virtual structure model; the performance parameter determination module 1730 can be used to adjust the original virtual structure model based on the target interlayer spacing to obtain the target virtual structure model, and determine the first performance parameter of the heterostructure in the physical performance dimension and the second performance parameter in the chemical performance dimension based on the target virtual structure model; the performance analysis module 1740 can be used to analyze the physical performance of the heterostructure based on the first performance parameter in the physical performance dimension, and analyze the chemical performance of the heterostructure based on the second performance parameter in the chemical performance dimension.

[0120] In one example embodiment of this disclosure, the heterostructure is an APA-graphene / silicene heterostructure; in the APA-graphene / silicene heterostructure, the APA-graphene structure is located on top of the silicene structure; the target lattice constant includes a first lattice constant corresponding to the APA-graphene structure and a second lattice constant corresponding to the silicene structure; the original structural model includes a first original structural model corresponding to the APA-graphene structure and a second original structural model corresponding to the silicene structure.

[0121] In one example embodiment of this disclosure, an original virtual structure model corresponding to the heterostructure is constructed based on the original structure model and the target lattice constant. This includes: calling a first original structure model corresponding to the APA-graphene structure and adjusting the first original structure model based on the first lattice constant to obtain an APA-graphene lattice; calling a second original structure model corresponding to the silicene structure and adjusting the second original structure model based on the second lattice constant to obtain a silicene unit cell structure; wherein the second original structure model is the unit cell structure of a silicon crystal; redefining the silicene unit cell structure to obtain an orthorhombic silicene unit cell structure matching the APA-graphene lattice; and generating an original virtual structure model corresponding to the heterostructure based on the APA-graphene lattice and the orthorhombic silicene unit cell structure.

[0122] In one example embodiment of this disclosure, determining the target interlayer spacing of a heterostructure based on the original virtual structural model includes: performing static self-consistent calculations on the original virtual structural model to determine the target plane wave cutoff energy and the target K-grid density required for performance analysis of the heterostructure; and determining the target interlayer spacing between the APA-graphene lattice and the orthorhombic silicene structure in the heterostructure based on the target plane wave cutoff energy and the target K-grid density.

[0123] In one example embodiment of this disclosure, determining the first performance parameter of the heterostructure in the physical performance dimension and the second performance parameter in the chemical performance dimension based on the target virtual structure model includes: obtaining the pseudopotential parameters of the elements included in the APA-graphene structure and the silicene structure in the target virtual structure model, and generating a PBE functional pseudopotential file corresponding to the heterostructure based on the pseudopotential parameters of the elements; determining the convergence criterion parameters, optimization step size parameters, and lattice optimization parameters required for performance analysis of the heterostructure, and generating an input parameter file based on the convergence criterion parameters, optimization step size parameters, lattice optimization parameters, and the target plane wave cutoff energy; generating a K-point file corresponding to the heterostructure based on the target K-grid density, and generating a K-point file based on the target K-grid density; and generating a K-point file corresponding to the heterostructure based on the target K-grid density. A virtual structural model generates a cell position file corresponding to the heterostructure. Based on the PBE functional pseudopotential file, input parameter file, K-point file, and cell position file, the first performance parameter of the heterostructure in the physical performance dimension is determined. The first performance parameter includes at least one of the heterostructure's phonon spectrum, molecular dynamics, elastic constant, and differential charge density. Based on the PBE functional pseudopotential file, input parameter file, K-point file, and cell position file, the second performance parameter of the heterostructure in the chemical performance dimension is determined. The second performance parameter includes at least one of the heterostructure's band structure, adsorption energy of a single Li ion, migration and diffusion barrier of Li ions in the heterostructure, theoretical voltage capacity of the heterostructure, and open-circuit voltage.

[0124] In one example embodiment of this disclosure, a second performance parameter of the heterostructure in the chemical performance dimension is determined based on the PBE functional pseudopotential file, input parameter file, K-point file, and unit cell position file. This includes: determining the band structure and the adsorption energy of a single Li ion in the heterostructure based on the PBE functional pseudopotential file, input parameter file, K-point file, and unit cell position file; determining the most stable adsorption site in the heterostructure based on the adsorption energy of a single Li ion, and determining the migration and diffusion barrier of a single Li ion in the heterostructure based on the most stable adsorption site; determining the maximum number of Li ions that can be adsorbed in a single heterostructure based on the adsorption energy of a single Li ion, and determining the theoretical voltage capacity and open-circuit voltage of the heterostructure based on the maximum number of Li ions that can be adsorbed in a single heterostructure.

[0125] In one example embodiment of this disclosure, determining the most stable adsorption site in a heterostructure based on the adsorption energy of a single Li ion includes: traversing the adsorption energies of single Li ions, extracting the smallest adsorption energy of a single Li ion from the adsorption energies of single Li ions, and taking the adsorption site corresponding to the smallest adsorption energy of a single Li ion as the most stable adsorption site in the heterostructure.

[0126] In one example embodiment, determining the maximum number of Li ions that can be adsorbed in a single heterostructure based on the adsorption energy of a single Li ion includes: sequentially increasing the number of Li ions to be adsorbed in the single heterostructure, and calculating the adsorption energy of the added single Li ion at the corresponding adsorption site; when it is detected that the adsorption energy of any adsorption site is positive, taking the current number of Li ions in the single heterostructure as the maximum number of Li ions that can be adsorbed in the single heterostructure.

[0127] In one example embodiment of this disclosure, the physical properties of the heterostructure are analyzed based on a first performance parameter in the physical performance dimension, including: if the phonon spectrum of the heterostructure does not include an imaginary frequency, then the heterostructure is determined to have good dynamic stability; and / or if the oscillation range of the total molecular energy in the molecular dynamics of the heterostructure is less than a preset range threshold, then the heterostructure is determined to have good thermodynamic stability; and / or if the elastic constant of the heterostructure is less than a preset elastic threshold, then the heterostructure is determined to have good mechanical stability; and / or if the differential charge density of the heterostructure is less than a preset density threshold, then the heterostructure is determined to have good charge transfer properties.

[0128] In one example embodiment of this disclosure, the chemical properties of the heterostructure are analyzed based on a second performance parameter in the chemical performance dimension, including: if the energy band of the heterostructure can cross the Fermi level, then the heterostructure is determined to have good electronic conductivity; and / or if the adsorption energy of a single Li ion at a certain position in the heterostructure is less than a preset adsorption threshold, then that position in the heterostructure is determined to have stable adsorption; and / or if the diffusion barrier between the heterostructures is less than a preset barrier threshold, then the heterostructure is determined to have good ion migration performance; and / or if the theoretical voltage capacity of the heterostructure is greater than a preset capacity threshold, then the heterostructure is determined to have good capacitive performance; and / or if the open-circuit voltage of the heterostructure is greater than a preset voltage threshold, then the heterostructure is determined to have good driving performance.

[0129] The specific details of each module in the above-mentioned heterostructure performance analysis device have been described in detail in the corresponding heterostructure performance analysis method, so they will not be repeated here.

[0130] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0131] Furthermore, although the steps of the method in this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0132] In exemplary embodiments of this disclosure, an electronic device capable of implementing the above-described methods is also provided. Those skilled in the art will understand that various aspects of this disclosure can be implemented as systems, methods, or program products. Therefore, various aspects of this disclosure can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or an implementation combining hardware and software aspects, collectively referred to herein as a "circuit," "module," or "system."

[0133] The following reference Figure 18 To describe an electronic device 1800 according to such an embodiment of the present disclosure. Figure 18 The electronic device 1800 shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments disclosed herein.

[0134] like Figure 18 As shown, the electronic device 1800 is manifested in the form of a general-purpose computing device. The components of the electronic device 1800 may include, but are not limited to: at least one processing unit 1810, at least one storage unit 1820, a bus 1830 connecting different system components (including storage unit 1820 and processing unit 1810), and a display unit 1840.

[0135] The storage unit stores program code that can be executed by the processing unit 1810, causing the processing unit 1810 to perform the steps described in the "Exemplary Methods" section of this specification according to various exemplary embodiments of this disclosure. For example, the processing unit 1810 can perform actions such as... Figure 1Step S110: In response to the assignment operation of the lattice constant on the interactive interface, determine the target lattice constant required to construct the target virtual structure model corresponding to the heterostructure, and call the original structure model corresponding to the heterostructure; Step S120: Based on the original structure model and the target lattice constant, construct the original virtual structure model corresponding to the heterostructure, and determine the target interlayer spacing of the heterostructure based on the original virtual structure model; Step S130: Adjust the original virtual structure model based on the target interlayer spacing to obtain the target virtual structure model, and determine the first performance parameter of the heterostructure in the physical performance dimension and the second performance parameter in the chemical performance dimension based on the target virtual structure model; Step S140: Analyze the physical performance of the heterostructure based on the first performance parameter in the physical performance dimension, and analyze the chemical performance of the heterostructure based on the second performance parameter in the chemical performance dimension.

[0136] Storage unit 1820 may include readable media in the form of volatile storage units, such as random access memory (RAM) 18201 and / or cache memory 18202, and may further include read-only memory (ROM) 18203. Storage unit 1820 may also include a program / utility 18204 having a set (at least one) of program modules 18205, such program modules 18205 including but not limited to: operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0137] Bus 1830 can represent one or more of several types of bus structures, including memory cell bus or memory cell controller, peripheral bus, graphics acceleration port, processing unit, or local bus using any of the various bus structures.

[0138] Electronic device 1800 can also communicate with one or more external devices 1900 (e.g., keyboard, pointing device, Bluetooth device, etc.), one or more devices that enable a user to interact with electronic device 1800, and / or any device that enables electronic device 1800 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 1850. Furthermore, electronic device 1800 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 1860. As shown, network adapter 1860 communicates with other modules of electronic device 1800 via bus 1830. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 1800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0139] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0140] In exemplary embodiments of this disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the methods described above is stored. In some possible implementations, various aspects of this disclosure may also be implemented as a program product including program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps of the various exemplary embodiments of this disclosure described in the "Exemplary Methods" section above.

[0141] The program product for implementing the above-described method according to embodiments of the present disclosure may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto. In this document, the readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0142] The program product may take the form of any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0143] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0144] Program code for performing the operations of this disclosure can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0145] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of this disclosure and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0146] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention described herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not invented by this disclosure. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

Claims

1. A method for performance analysis of heterostructures, characterized in that, include: In response to the assignment operation of the lattice constant on the interactive interface, the target lattice constant required to construct the target virtual structure model corresponding to the heterostructure is determined, and the original structure model corresponding to the heterostructure is called. Based on the original structural model and the target lattice constant, an original virtual structural model corresponding to the heterostructure is constructed, and the target interlayer spacing of the heterostructure is determined based on the original virtual structural model, including: performing static self-consistent calculations on the original virtual structural model to determine the target plane wave cutoff energy and target K-grid density required for performance analysis of the heterostructure; and determining the target interlayer spacing between the APA-graphene lattice and the orthorhombic silicene structure in the heterostructure based on the target plane wave cutoff energy and the target K-grid density. The original virtual structure model is adjusted based on the target interlayer spacing to obtain a target virtual structure model. A first performance parameter in the physical performance dimension and a second performance parameter in the chemical performance dimension of the heterostructure are then determined based on the target virtual structure model. The first performance parameter includes at least one of the heterostructure's phonon spectrum, molecular dynamics, elastic constant, and differential charge density. The second performance parameter includes at least one of the heterostructure's band structure, adsorption energy of a single Li ion, migration and diffusion barrier of Li ions in the heterostructure, theoretical voltage capacity of the heterostructure, and open-circuit voltage. The physical properties of the heterostructure are analyzed based on the first performance parameter in the physical property dimension, and the chemical properties of the heterostructure are analyzed based on the second performance parameter in the chemical property dimension.

2. The performance analysis method for heterogeneous structures according to claim 1, characterized in that, The heterostructure is an APA-graphene / silicene heterostructure; in the APA-graphene / silicene heterostructure, the APA-graphene structure is located on top of the silicene structure. The target lattice constant includes a first lattice constant corresponding to the APA-graphene structure and a second lattice constant corresponding to the silicene structure; The original structural models include a first original structural model corresponding to the APA-graphene structure and a second original structural model corresponding to the silicene structure.

3. The performance analysis method for heterogeneous structures according to claim 1, characterized in that, Based on the original structural model and the target lattice constant, an original virtual structural model corresponding to the heterostructure is constructed, including: The first original structural model corresponding to the APA-graphene structure is called, and the first original structural model is adjusted based on the first lattice constant to obtain the APA-graphene lattice. The second primitive structure model corresponding to the silicene structure is invoked, and the second primitive structure model is adjusted based on the second lattice constant to obtain the silicene unit cell structure; wherein, the second primitive structure model is the unit cell structure of silicon crystal; The silicene unit cell structure is redefined to obtain an orthorhombic silicene structure that matches the APA-graphene lattice. Based on the APA-graphene lattice and the orthorhombic silicene structure, an original virtual structure model corresponding to the heterostructure is generated.

4. The performance analysis method for heterogeneous structures according to claim 1, characterized in that, Based on the target virtual structure model, the first performance parameter of the heterostructure in the physical performance dimension and the second performance parameter in the chemical performance dimension are determined, including: Obtain the pseudopotential parameters of the elements included in the APA-graphene structure and the silicene structure in the target virtual structure model, and generate a PBE functional pseudopotential file corresponding to the heterostructure based on the pseudopotential parameters of the elements. The convergence criterion parameters, optimization step size parameters, and lattice optimization parameters required for performance analysis of the heterostructure are determined, and an input parameter file is generated based on the convergence criterion parameters, optimization step size parameters, lattice optimization parameters, and target plane wave cutoff energy. Generate a K-point file corresponding to the heterostructure based on the target K-grid density, and generate a cell position file corresponding to the heterostructure based on the target virtual structure model; Based on the PBE functional pseudopotential file, input parameter file, K-point file, and cell position file, the first performance parameter of the heterostructure in the physical performance dimension is determined. Based on the PBE functional pseudopotential file, input parameter file, K-point file, and cell position file, the second performance parameter of the heterostructure in the chemical property dimension is determined.

5. The performance analysis method for heterostructures according to claim 4, characterized in that, Based on the PBE functional pseudopotential file, input parameter file, K-point file, and unit cell position file, the second performance parameter of the heterostructure in the chemical property dimension is determined, including: Based on the PBE functional pseudopotential file, input parameter file, K-point file, and cell position file, the energy band of the heterostructure and the adsorption energy of a single Li ion are determined. The most stable adsorption site in the heterostructure is determined based on the adsorption energy of a single Li ion, and the migration and diffusion barrier of a single Li ion in the heterostructure is determined based on the most stable adsorption site. The maximum number of Li ions that can be adsorbed in a single heterostructure can be determined based on the adsorption energy of a single Li ion, and the theoretical voltage capacity and open-circuit voltage of the heterostructure can be determined based on the maximum number of Li ions that can be adsorbed in a single heterostructure.

6. The performance analysis method for heterostructures according to claim 5, characterized in that, The most stable adsorption sites in the heterostructure are determined based on the adsorption energy of a single Li ion, including: By iterating through the adsorption energies of individual Li ions, the adsorption energy of the smallest individual Li ion is extracted from the adsorption energies of individual Li ions, and the adsorption site corresponding to the adsorption energy of the smallest individual Li ion is taken as the most stable adsorption site in the heterostructure.

7. The performance analysis method for heterostructures according to claim 5, characterized in that, The maximum number of Li ions that can be adsorbed in a single heterostructure can be determined based on the adsorption energy of a single Li ion, including: In a single heterostructure, the number of Li ions to be adsorbed is increased sequentially, and the adsorption energy of each additional Li ion at the corresponding adsorption site is calculated. When the adsorption energy of any adsorption site is positive, the number of Li ions currently present in a single heterostructure is taken as the maximum number of Li ions that can be adsorbed in a single heterostructure.

8. The performance analysis method for heterogeneous structures according to claim 1, characterized in that, The physical properties of the heterostructure are analyzed based on a first performance parameter in the physical performance dimension, including: If the phonon spectrum of the heterostructure does not include explicit imaginary frequencies, then the heterostructure is determined to have good dynamic stability; and / or If the oscillation range of the total molecular energy in the molecular dynamics of the heterostructure is less than a preset threshold, then the heterostructure is determined to have good thermodynamic stability; and / or If the elastic constant of the heterostructure is less than a preset elastic threshold, then the heterostructure is determined to have good mechanical stability; and / or If the differential charge density of the heterostructure is less than a preset density threshold, then the heterostructure is determined to have good charge transfer properties.

9. The performance analysis method for heterogeneous structures according to claim 1, characterized in that, The chemical properties of the heterostructure are analyzed based on the second performance parameter of the heterostructure in the chemical properties dimension, including: If the energy band of the heterostructure can cross the Fermi level, then the heterostructure is determined to have good electronic conductivity; and / or If the adsorption energy of a single Li ion at a certain position in the heterostructure is less than a preset adsorption threshold, then it is determined that the position in the heterostructure has stable adsorption properties; and / or If the diffusion barrier between the heterostructures is less than a preset barrier threshold, then the heterostructure is determined to have good ion migration performance; and / or If the theoretical voltage capacity of the heterostructure is greater than a preset capacity threshold, then the heterostructure is determined to have good capacitive performance; and / or If the open-circuit voltage of the heterostructure is greater than a preset voltage threshold, then the heterostructure is determined to have good driving performance.

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