Graphene-based material heterojunction directional design method based on thermodynamic property analysis
By analyzing the vibrational modes and thermodynamic properties of graphene-based heterojunctions using ab initio molecular dynamics and Fourier transform techniques, the problem of accuracy in the design of thermodynamic properties of graphene-based heterojunctions was solved, and efficient directional optimization and structural design were achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-19
- Publication Date
- 2026-03-31
Smart Images
Figure CN121768545A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of graphene material simulation technology, and in particular to a method for directional design of graphene-based material heterostructures based on thermodynamic property analysis. Background Technology
[0002] With the continuous development of new materials, graphene, as a two-dimensional material with excellent electronic, thermal, and mechanical properties, has shown broad application prospects in many fields. The heterojunction structure of graphene-based materials, due to its unique band structure, thermal conductivity, and mechanical properties, has significant application value in nanoelectronics, thermoelectric materials, and optoelectronic devices. However, how to precisely design and optimize the thermodynamic properties of graphene-based heterojunction materials to meet specific application requirements remains a pressing scientific and engineering problem to be solved.
[0003] Currently, traditional heterostructure design methods mainly rely on experimental verification and empirical models, which have limitations when dealing with complex material systems. In particular, accurately predicting the thermodynamic properties of materials, such as thermal conductivity, specific heat, and coefficient of thermal expansion, remains a challenging problem during the design process. Therefore, how to utilize theoretical calculations and simulations, combined with the thermodynamic properties of materials, for the directional design of graphene-based heterostructures has become an urgent issue to be addressed.
[0004] Based on this, a method for the directional design of graphene-based heterojunctions is proposed, based on thermodynamic property analysis. This method simulates graphene-based heterojunction systems using ab initio molecular dynamics (AIMD) algorithms, combined with Fourier transform techniques and phonon spectrum calculations, to effectively analyze the vibrational modes and thermodynamic properties of the materials, thereby achieving directional optimization design of graphene-based heterojunction structures. This method provides accurate thermodynamic properties such as thermal conductivity, specific heat, and coefficient of thermal expansion, offering theoretical basis and technical support for the design of graphene-based heterojunction materials. Summary of the Invention
[0005] This application provides a method for directional design of graphene-based heterojunctions based on thermodynamic property analysis, which can improve the directional design and optimization capability of graphene-based heterojunctions under the guidance of thermodynamic properties.
[0006] In a first aspect, this application provides a method for the directional design of graphene-based material heterostructures based on thermodynamic property analysis, the method comprising: S1. The ab initio molecular dynamics AIMD algorithm was used to simulate the atomic coordinate trajectory data of the graphene-based heterojunction system; S2. Perform a time-domain Fourier transform on the atomic coordinate trajectory data to determine the vibration spectrum of each atom, and further obtain the heterojunction periodic structure and crystal space grid relationship; S3. Based on the periodic structure of the heterojunction and the relationship of the crystal space grid, the vibration spectrum is mapped to the reciprocal space using the lattice space Fourier transform to obtain the reciprocal space wave vector spectrum. S4. Using inverse Fourier transform technology, extract the real space vibration modes at finite temperature from the reciprocal space wave vector spectrum; S5. Based on the real space vibration mode and the periodicity of the underlying original lattice, calculate the phonon spectrum and thermodynamic properties of the graphene-based heterojunction, and optimize the heterojunction orientation design based on the thermodynamic properties to obtain the optimized graphene-based heterojunction.
[0007] Optionally, the ab initio molecular dynamics AIMD algorithm is used to simulate the graphene-based heterojunction system to obtain preliminary atomic coordinate trajectory data; instantaneous position data and equilibrium position data of atoms are extracted from the preliminary atomic coordinate trajectory data; the instantaneous position data and the equilibrium position data are differentially processed to obtain the offset of atomic vibration; based on the offset of atomic vibration, the preliminary atomic coordinate trajectory data is smoothed to filter out noise fluctuations, and the final atomic coordinate trajectory data is obtained.
[0008] Optionally, time evolution data for each atom is extracted from the atomic coordinate trajectory data; Fourier transform is performed on the time evolution data to obtain vibration mode data; based on the vibration mode data, the vibration frequency and vibration amplitude of each atom are calculated to obtain the vibration spectrum; based on the vibration spectrum, a characteristic frequency range is identified to obtain effective phonon modes; the effective phonon modes are processed using a peak detection algorithm to obtain the main vibration modes; based on the main vibration modes, a heterojunction periodic structure is obtained, and the interaction relationship between the basic crystal unit and the atoms is determined; based on the interaction relationship, the wave vector grid relationship of the reciprocal space is obtained as the crystal space grid relationship.
[0009] Optionally, based on the periodic structure of the heterojunction, the correspondence between the basic crystal unit and the reciprocal space is determined; according to the crystal space grid relationship and in combination with the correspondence, a wave vector grid of the reciprocal space is established; the spatial relationship between the time data in the vibration spectrum and the wave vector grid is mapped and matched; the mapping and matching results are processed by Fourier transform to obtain the wave vector spectrum of the reciprocal space.
[0010] Optionally, based on the reciprocal space wave vector spectrum, a temperature dependence parameter reflecting the vibration mode under finite temperature conditions is determined; based on the temperature dependence parameter, combined with inverse Fourier transform technology, the vibration amplitude information and vibration mode information of each atom at the finite temperature are calculated; the vibration amplitude information and the vibration mode information are integrated and smoothed to obtain the real space vibration mode at the finite temperature.
[0011] Optionally, by analyzing the periodic structure of the crystal lattice and the real-space vibration modes, the phonon modes corresponding to different wave vectors in the crystal are determined; the phonon modes are processed using phonon spectrum calculation methods to obtain the phonon spectrum; based on the phonon spectrum, the energy distribution corresponding to different phonon modes is further analyzed to obtain the phonon band structure; based on the phonon band structure and combined with the phonon distribution at a finite temperature, the thermal conductivity of the graphene-based heterojunction is calculated; using the phonon spectrum, the heat absorbed by a unit mass of the graphene-based heterojunction under a unit temperature change is calculated to obtain the specific heat of the graphene-based heterojunction; the dependence of the phonon spectrum on temperature is analyzed to obtain the thermal expansion coefficient of the graphene-based heterojunction; integrating the thermal conductivity, specific heat, and thermal expansion coefficient, the thermodynamic properties of the graphene-based heterojunction are obtained; based on the thermodynamic properties, an optimization algorithm is used to directionally design the heterojunction structure to obtain the optimized graphene-based heterojunction.
[0012] Optionally, a dynamic matrix reconstruction technique is employed to construct a dynamic matrix based on real-space vibrational modes and interatomic interaction potentials; the dynamic matrix is diagonalized to obtain the polarization vectors corresponding to the phonon frequencies; the polarization vectors are projected onto the lattice basis vectors to obtain the phonon frequencies under each wave vector, generating phonon dispersion relations; based on the phonon dispersion relations, combined with the Brillouin zone integral method, the phonon density of states is calculated to further obtain the complete phonon spectrum.
[0013] Optionally, the group velocity of each phonon mode is obtained based on the phonon spectrum; according to the group velocity, combined with phonon lifetime information and phonon scattering rate information, the contribution value of different phonon modes to thermal conductivity is calculated to obtain a set of phonon mode contribution values; the Boltzmann transport equation is used to perform a weighted integral on the set of phonon mode contribution values to obtain the final thermal conductivity.
[0014] A second aspect of this application provides a computer device in which the memory stores machine-readable instructions executable by the processor. When the computer device is running, the processor communicates with the memory via a bus. When the machine-readable instructions are executed by the processor, the steps of the above-described method for directional design of graphene-based material heterojunctions based on thermodynamic property analysis are performed.
[0015] Thirdly, this application provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the above-described method for directional design of graphene-based material heterostructures based on thermodynamic property analysis.
[0016] The technical solution provided in this application brings technological advantages and practical benefits to the material design of graphene-based heterostructures. Traditional methods often rely on trial and error or simplified empirical models, making it difficult to accurately predict the thermodynamic behavior of complex heterostructures under real-world temperature conditions. This method, however, combines ab initio molecular dynamics with multi-scale Fourier transform analysis to accurately simulate and extract phonon vibrational modes and complete phonon spectra at finite temperatures at the atomic scale, thereby calculating key thermodynamic parameters such as thermal conductivity and specific heat. The direct benefit of this process is that it enables the quantitative and high-precision prediction of the thermal management performance of heterostructures, significantly reducing the time and economic cost of performance optimization through repeated experiments. Furthermore, the ultimate goal of this method is "directed design." This means that researchers can use the thermodynamic requirements of specific applications, such as electronic devices requiring ultra-high heat dissipation efficiency or composite materials with specific coefficients of thermal expansion, to guide the structural optimization of heterostructures. Attached Figure Description
[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0018] Figure 1 This is a flowchart of the directional design method for graphene-based material heterostructures based on thermodynamic property analysis according to this application. Figure 2 This is a flowchart of the finite-temperature real-space vibration mode reconstruction based on reciprocal space mapping in this application; Figure 3 This is a schematic block diagram of the graphene-based material heterojunction directional design device based on thermodynamic property analysis according to this application. Detailed Implementation
[0019] This application provides a method for the directional design of graphene-based material heterostructures based on thermodynamic property analysis. The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" or "having" and any variations thereof are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0020] For ease of understanding, the specific process of the embodiments of this application is described below. Please refer to [link / reference]. Figure 1 One embodiment of the graphene-based material heterostructure directional design method based on thermodynamic property analysis in this application includes: Step S1: Simulate the atomic coordinate trajectory data of the graphene-based heterojunction system using the ab initio molecular dynamics AIMD algorithm.
[0021] In one specific embodiment, the process of performing step S1 may specifically include the following steps: The ab initio molecular dynamics AIMD algorithm was used to simulate the graphene-based heterojunction system and obtain preliminary atomic coordinate trajectory data; Extract the instantaneous position data and equilibrium position data of the atoms from the preliminary atomic coordinate trajectory data; The instantaneous position data and equilibrium position data are differentially processed to obtain the offset of atomic vibration; Based on the offset of atomic vibrations, the preliminary atomic coordinate trajectory data is smoothed to filter out noise fluctuations, thus obtaining the final atomic coordinate trajectory data.
[0022] Specifically, a graphene-based heterostructure system was simulated using the ab initio molecular dynamics (AIMD) algorithm to obtain preliminary atomic coordinate trajectory data. During the simulation, the simulation duration was set to 100 ps, the time step to 1 fs, and the temperature was maintained at 300 K. The atomic coordinates at each time step were obtained through simulation, and the instantaneous position data of each atom was extracted from the preliminary atomic coordinate trajectory data. and its equilibrium position data Where n is the lattice point index, p is the atom index, and j is the Cartesian coordinate component. A difference operation is then performed on the two to calculate the vibrational offset of the atom. : Based on this offset, the initial atomic coordinate trajectory data is smoothed. A weighted average algorithm is used to average the data from each time step with the data from several preceding and following time steps, filtering out noise fluctuations generated during the calculation process. Through this smoothing process, the final denoised atomic coordinate trajectory data that accurately reflects the atomic vibration characteristics is obtained.
[0023] Step S2: Perform a time-domain Fourier transform on the atomic coordinate trajectory data to determine the vibration spectrum of each atom, and further obtain the periodic structure of the heterojunction and the relationship between the crystal space grid.
[0024] In one specific embodiment, the process of performing step S2 may specifically include the following steps: Extract the temporal evolution data of each atom from the atomic coordinate trajectory data; Fourier transform is performed on the time evolution data to obtain vibration mode data; Based on vibration mode data, the vibration frequency and vibration amplitude of each atom are calculated to obtain the vibration spectrum; Based on the vibration spectrum, the characteristic frequency range is identified to obtain effective phonon modes; The effective phonon modes are processed using a peak detection algorithm to obtain the main vibration modes; Based on the main vibrational modes, the periodic structure of the heterojunction was obtained, and the interaction relationship between the basic crystal unit and the atoms was determined. Based on the interaction relationship, the wave vector grid relationship of the reciprocal space is obtained as the crystal space grid relationship.
[0025] Specifically, in ab initio molecular dynamics (AIMD) simulations, the time evolution data of each atom was obtained, recording the changes in atomic positions at different time steps. It is assumed that graphene material is composed of... Composed of atoms, obtained through simulation The coordinate data of each atom at each time point is obtained. Next, a Fourier Transform (FFT) is performed on these atomic coordinate data to convert the time-domain signal into a frequency-domain signal, thereby obtaining the vibration mode data of each atom. For example, by performing a Fourier Transform on the coordinate data of a specific atom, its vibration characteristics in the frequency domain can be obtained. For example, if the principal vibration frequency is 10 THz, it means that the atom vibrates most strongly at that frequency.
[0026] Based on this, the vibrational frequency and amplitude of each atom are calculated, resulting in a complete vibrational spectrum. This spectrum reveals the vibrational characteristics of all atoms in the system. For example, the spectrum shows vibrational frequencies ranging from 1 THz to 20 THz, corresponding to different phonon modes. Within this frequency range, by analyzing the peaks in the spectrum, characteristic frequency ranges can be identified, allowing the extraction of effective phonon modes that significantly influence the material's thermal conductivity. Phonon modes refer to the vibrational modes exhibited by atoms or molecules in a crystal during thermal vibration, including acoustic and optical modes. Different phonon modes correspond to different vibrational frequencies, which can be analyzed using the vibrational spectrum. The characteristic frequency range refers to the specific frequency intervals within the vibrational spectrum that significantly influence the system's behavior by analyzing the vibrational frequencies of phonons. The effective phonon modes corresponding to the characteristic frequency range are those that significantly affect the macroscopic properties of the material, such as thermal conductivity and mechanical properties, within this frequency range. For example, low-frequency phonon modes typically contribute more to thermal conductivity because they can propagate over longer distances in the material, while high-frequency phonon modes contribute less.
[0027] Furthermore, a peak detection algorithm is used to process these effective phonon modes, screening out the dominant vibrational modes whose amplitudes exceed twice the average or median amplitudes of all vibrational modes. Analysis of these dominant vibrational modes not only reveals the motion of atoms within graphene but also allows for the deduction of the material's periodic structure. A periodic structure refers to the repeating arrangement of atoms or molecules in space according to a specific pattern. This structure exhibits periodicity over long distances, typically manifesting as a basic repeating unit appearing repeatedly in three-dimensional space with a specific orientation and spacing. For example, the hexagonal lattice structure and interlayer interactions of graphene can be verified through these dominant vibrational modes.
[0028] Determining the interactions between the fundamental units of a crystal and its atoms typically requires identifying the crystal's periodic structure and the fundamental unit cell—the smallest repeating unit in the crystal, composed of specific atoms arranged according to certain rules. The geometry and size of the unit cell determine the crystal's symmetry and physical properties. Then, using interatomic interaction models (such as the Lennard-Jones potential), the forces between atoms in the crystal can be quantitatively described, including electrostatic forces and van der Waals forces. Molecular dynamics simulations or density functional theory methods can be used to calculate the interaction energies between atoms and their effects, verifying the applicability of the potential energy model.
[0029] Having clarified the periodic structure of the crystal and the main interatomic interactions, a wave vector grid relation in reciprocal space can be constructed. This grid, based on the periodicity of the crystal, provides wave vector information in reciprocal space, thus providing the necessary geometric framework for subsequent phonon propagation analysis and thermal conductivity calculations.
[0030] Step S3: Based on the periodic structure of the heterojunction and the relationship between the crystal space grid, the vibration spectrum is mapped to the reciprocal space using the lattice space Fourier transform to obtain the reciprocal space wave vector spectrum.
[0031] In one specific embodiment, the process of performing step S3 may specifically include the following steps: Based on the periodic structure of heterojunctions, the correspondence between the basic crystal units and the reciprocal space is determined; Based on the crystal space grid relationship and the correspondence relationship, a wave vector grid with reciprocal space is established; Map and match the spatial relationship between the temporal data in the vibration spectrum and the wave vector grid. Fourier transform is used to process the mapping matching results to obtain the reciprocal space wave vector spectrum.
[0032] Specifically, taking graphene-based heterostructures as an example, assuming that the atomic coordinate trajectory data of graphene is obtained through molecular dynamics simulations, the crystal structure of graphene exhibits a hexagonal arrangement, with each carbon atom connected to its neighboring atoms via covalent bonds. To understand the thermal and mechanical properties of the material, this time-domain data needs to be converted into information in the frequency domain. Starting from the periodic structure of graphene, the correspondence between its basic crystal unit and reciprocal space is determined. The basic unit of graphene is a hexagonal lattice structure composed of carbon atoms, and the lattice basis vectors of reciprocal space can be defined through the periodic arrangement of this structure. Under this structure, the wave vector of reciprocal space... Closely related to the periodicity of crystals, the wave vector grid of reciprocal space can be derived by understanding the basic unit cells of crystals. Combining the crystal space grid relationships, the wave vector grid of reciprocal space is established. In the case of graphene, the wave vector grid of reciprocal space has a hexagonal structure, where each wave vector corresponds to a possible phonon mode in the crystal. For example, in graphene, the wave vector... It can represent the momentum of a phonon, and its direction and magnitude determine the phonon's propagation direction and wavelength in the crystal. By comparing it with atomic coordinate trajectory data, a correspondence between the wave vector and atomic vibration can be established.
[0033] The spatial relationship between time-domain vibrational data extracted from atomic coordinate trajectory data and the reciprocal space wave vector grid is mapped and matched. In this process, it is assumed that an atom undergoes periodic vibration in the time domain, with displacement changes at each moment within the vibration period. By using Fourier transform to convert this time-domain data into frequency-domain information, the vibrational modes of each atom in the frequency domain can be matched with the corresponding wave vectors in the reciprocal space. For example, the vibration of an atom in the high-frequency range corresponds to a region with a high wave vector in the reciprocal space, while low-frequency vibrations correspond to a region with a low wave vector. Through this matching, the vibrational data of the atom can be mapped to the corresponding wave vector frequencies in the reciprocal space. The mapping and matching results are processed using Fourier transform to obtain the wave vector spectrum in the reciprocal space. Through Fourier transform, the vibrational modes in the time domain are converted into wave vector spectra in the reciprocal space, revealing the propagation behavior of phonons in graphene crystals at different frequencies. For example, suppose that after Fourier transform, a significant peak is found in the wave vector spectrum of graphene at a frequency of about 10 THz, which means that phonon propagation is particularly strong at this frequency and plays a key role in the calculation of thermal conductivity.
[0034] Step S4: Extract the real space vibration modes at finite temperatures from the reciprocal space wave vector spectrum using inverse Fourier transform technology.
[0035] In one specific embodiment, the process of performing step S4 may specifically include the following steps: Based on the reciprocal space wave vector spectrum, temperature-dependent parameters reflecting vibration modes under finite temperature conditions are determined; Based on temperature-dependent parameters and combined with inverse Fourier transform technology, the vibration amplitude and vibration mode information of each atom at a finite temperature are calculated. By integrating vibration amplitude information and vibration mode information and performing smoothing processing, the real space vibration mode under finite temperature is obtained.
[0036] Specifically, in the case of graphene-based heterostructures, the wave vector spectrum in reciprocal space provides the distribution of vibrational frequencies for phonon modes. However, phonon vibrational modes are affected by temperature, particularly with increasing temperature, where both amplitude and frequency change, exhibiting temperature dependence. Therefore, it is necessary to determine temperature-dependent parameters, such as temperature-dependent phonon frequency and amplitude variations. For example, low-frequency phonon modes in graphene are relatively stable at low temperatures, while high-frequency modes show more significant vibrational changes with increasing temperature. By combining the wave vector spectrum in reciprocal space with temperature-dependent models (such as the Boltzmann factor), the temperature dependence parameters for each phonon mode at different temperatures can be calculated. These parameters can reflect the temperature-dependent trends of phonons, especially the shift in phonon frequency and the increase in vibrational amplitude at finite temperatures.
[0037] A temperature-dependent parameter is assigned to each wave vector mode as a temperature adjustment factor, representing the effect of temperature on the vibrational amplitude. These temperature-corrected wave vector spectra are then converted back to vibrational mode data in real space using an inverse Fourier transform. During this process, the vibrational amplitude and mode information of each atom are adjusted according to its position in reciprocal space, ensuring that the calculation results reflect the actual vibrational state at different temperatures. For example, in graphene calculations, if the vibrational mode of a certain atom is primarily a ground-state vibration at low temperatures, but at high temperatures, the vibrational amplitude of that atom increases, potentially exciting higher-frequency vibrational modes. These temperature-corrected vibrational mode data can be obtained through an inverse Fourier transform, and the vibrational information of each atom is updated as the temperature changes.
[0038] Because vibrational modes at finite temperatures are affected by noise and discrete effects, smoothing processes (such as Gaussian smoothing or moving averages) are typically used to remove unwanted fluctuations and noise, resulting in smoother and more accurate real-space vibrational modes. This vibrational mode data can provide information about the thermal behavior, phonon scattering, and heat conduction of materials at specific temperatures, supporting further thermodynamic analysis and materials design. (Reference) Figure 2 The figure illustrates the reconstruction process of finite-temperature real-space vibration modes based on reciprocal space mapping.
[0039] Step S5: Based on the real space vibration mode and combined with the periodicity of the underlying original lattice, calculate the phonon spectrum and thermodynamic properties of the graphene-based heterojunction, and optimize the heterojunction orientation design based on the thermodynamic properties to obtain the optimized graphene-based heterojunction.
[0040] In one specific embodiment, the process of performing step S5 may specifically include the following steps: By analyzing the periodic structure of the crystal lattice and the vibrational modes in real space, the phonon modes corresponding to different wave vectors in the crystal are determined. Phonon modes are processed using phonon spectrum calculation methods to obtain phonon spectra; Based on the phonon spectrum, further analysis of the energy distribution corresponding to different phonon modes yields the phonon band structure; Based on the phonon band structure and the phonon distribution at finite temperatures, the thermal conductivity of graphene-based heterojunctions is calculated. The specific heat of the graphene-based heterojunction is obtained by calculating the heat absorbed per unit mass of graphene-based heterojunction under a unit temperature change using phonon spectra. The dependence of phonon spectra on temperature was analyzed to obtain the thermal expansion coefficient of graphene-based heterostructures; By integrating thermal conductivity, specific heat, and coefficient of thermal expansion, the thermodynamic properties of graphene-based heterostructures are obtained. Based on thermodynamic properties, an optimization algorithm was used to directionally design heterojunction structures, resulting in optimized graphene-based heterojunctions.
[0041] Specifically, graphene's crystal lattice exhibits hexagonal symmetry, and the atomic arrangement and vibrational modes within the crystal directly influence its phonon distribution. Under finite-temperature conditions, phonons form different wave vector modes in reciprocal space, and the magnitude and direction of the wave vector determine the phonon's propagation characteristics. For example, low-frequency phonon modes typically correspond to regions with smaller wave vectors in reciprocal space, with values generally ranging from 0 to 1. Within this range, high-frequency phonon modes correspond to regions with larger wave vectors in reciprocal space, typically ranging from 1 to 10. Within this range. By analyzing these wave vectors, the vibrational characteristics of each phonon mode, such as frequency and amplitude, can be obtained, thus helping to understand the thermal behavior and elastic properties of materials.
[0042] Phonon spectra describe the distribution of phonon modes at different frequencies and reflect the thermal properties of crystals at different temperatures. For graphene-based heterostructures, phonon spectrum calculations involve using dynamical matrices and phonon dispersion relations to obtain the phonon density of states by processing the polarization vector of each phonon mode. This process determines the phonon density for each frequency range in the material, providing a basis for further calculations of thermal conductivity and specific heat. Based on the obtained phonon spectrum, the energy distribution corresponding to different phonon modes is further analyzed to obtain the phonon band structure. As a two-dimensional material, graphene's phonon band structure typically exhibits a specific geometric shape. In the low-frequency region, phonon energy is lower, while in the high-frequency region, phonon energy gradually increases. By analyzing the phonon spectrum, the phonon energy distribution can be obtained, and the phonon band structure at a specific temperature can be calculated using thermodynamic models. These data contribute to understanding properties such as thermal conductivity, phonon scattering, and the thermal conductivity of the material.
[0043] The influence of phonon band structure on thermal conductivity calculation lies in the fact that the distribution of phonon bands determines the phonon filling and propagation characteristics at different temperatures. The phonon band structure reflects the frequency distribution and propagation characteristics of phonons in a material, thus affecting the calculation of thermal conductivity. In graphene-based heterostructures, the phonon band structure and the phonon distribution at finite temperatures jointly determine the material's thermal conductivity. For example, in the case of graphene-based heterostructures, the influence of phonon band structure on thermal conductivity calculation is reflected through the changes in the contributions of high-frequency and low-frequency phonon modes. Specifically, high-frequency phonons are generally associated with higher thermal conductivity because they have strong conductivity in crystals, especially under high-temperature conditions. The phonon band structure determines the frequency distribution of phonon modes, which directly affects the occupancy of each phonon mode at different temperatures and their contribution to heat conduction. At low temperatures, the occupancy of low-frequency phonon modes is lower, resulting in lower thermal conductivity, while at high temperatures, the occupancy of high-frequency phonon modes increases, and their contribution to thermal conductivity also increases. This temperature dependence can be accurately captured by analyzing the phonon spectrum and phonon band structure.
[0044] Furthermore, the coefficient of thermal expansion is the expansion characteristic of a material as a function of temperature, and it is usually calculated by analyzing the change of phonon frequency with temperature. At high temperatures, the vibration amplitude of phonons increases, leading to lattice expansion; therefore, changes in the high-frequency region of the phonon spectrum are crucial for the calculation of the coefficient of thermal expansion.
[0045] Finally, the thermodynamic properties of the graphene-based heterostructure were obtained. These properties can provide important information for the practical application of the material, especially in thermal management and high-performance material design. Based on these thermodynamic properties, an optimization algorithm was used to directionally design the heterostructure structure, thereby obtaining an optimized graphene-based heterostructure. For example, the optimization algorithm can adjust the material combination at different levels in the heterostructure according to parameters such as thermal conductivity and specific heat to achieve optimal thermal management performance.
[0046] In applications requiring precise temperature control, such as spacecraft thermal protection systems or high-temperature detectors, the coefficient of thermal expansion of materials plays a crucial role. Graphene-based heterostructures possess a relatively stable coefficient of thermal expansion, allowing for the design of materials that remain stable under extreme temperature variations. For instance, in spacecraft thermal protection systems, graphene-based heterostructures can effectively cope with rapid temperature changes from extremely low to high temperatures, preventing damage caused by uneven material expansion or excessive contraction.
[0047] In the field of new energy, optimizing the thermal conductivity, specific heat, and coefficient of thermal expansion of graphene-based heterojunctions is crucial for improving the thermoelectric efficiency of materials. For example, in thermoelectric power generation devices, optimizing the structure and thermodynamic properties of graphene-based heterojunctions can improve energy conversion efficiency. Similarly, in solar cells, optimized graphene-based heterojunctions can enhance thermoelectric efficiency, enabling higher energy conversion efficiency even at lower temperature differences, thereby improving overall energy utilization.
[0048] Furthermore, the phonon spectrum calculation methods in S5 include: A dynamic matrix is constructed using dynamic matrix reconstruction technology based on real-space vibrational modes and interatomic interaction potentials; Diagonalizing the dynamic matrix yields the polarization vectors corresponding to the phonon frequencies; By projecting the polarization vector onto the direction of the lattice basis vector, the phonon frequencies under each wave vector are obtained, and the phonon dispersion relation is generated. Based on the phonon dispersion relation and combined with the Brillouin zone integral method, the phonon density of states is calculated, and the complete phonon spectrum is obtained.
[0049] Specifically, taking graphene as an example, the first step in phonon spectrum calculation is to employ dynamic matrix reconstruction technology. Based on the real-space vibrational modes and interatomic interaction potentials of graphene, a dynamic matrix is constructed. Graphene is a two-dimensional material with its atoms arranged in a hexagonal lattice, where each carbon atom forms strong covalent bonds with its three neighboring carbon atoms. Based on the crystal structure of graphene, the dynamic matrix is constructed by calculating the interatomic interaction potentials. This matrix reflects the mechanical forces exerted on each atom in graphene by its surrounding atoms, and these parameters are typically obtained using empirical potentials or first-principles calculations. For graphene, after diagonalization, the phonon frequency and polarization mode corresponding to each wave vector can be obtained. Graphene phonon modes include acoustic and optical modes. These polarization vectors describe the direction of phonon vibration, helping to understand the propagation characteristics of different phonon modes. Phonon dispersion relations demonstrate the frequency variation of phonons under different wave vectors. For example, the acoustic modes of graphene are typically in the low-frequency region, while the optical modes appear in the higher-frequency region. In this way, the phonon behavior under different wave vectors can be clearly observed. Its Brillouin zone exhibits hexagonal symmetry, thus the phonon density of states can be calculated by integrating over the entire Brillouin zone. The phonon spectrum reveals the distribution of phonons in graphene at different frequencies, further providing a foundation for calculating thermodynamic properties such as thermal conductivity and specific heat.
[0050] Furthermore, the methods for calculating the thermal conductivity of materials in S5 include: Group velocity of each phonon mode is obtained based on the phonon spectrum; Based on the group velocity, combined with phonon lifetime information and phonon scattering rate information, the contribution values of different phonon modes to thermal conductivity are calculated, and a set of phonon mode contribution values is obtained. The final thermal conductivity is obtained by weighted integration of the phonon mode contribution set using the Boltzmann transport equation.
[0051] Specifically, group velocity describes the speed at which phonons propagate in a crystal and is related to the phonon's frequency and wave vector. The group velocity of each phonon mode can be calculated by analyzing the dispersion relation in the phonon spectrum. For example, in graphene, due to its two-dimensional structure, low-frequency phonons typically have higher group velocities, while high-frequency phonons have relatively lower group velocities. Based on the group velocity, combined with phonon lifetime and phonon scattering rate information, the contribution of different phonon modes to thermal conductivity can be calculated. Phonon lifetime refers to the average time a phonon interacts with lattice defects, impurities, and other phonons during propagation; these interactions affect the phonon propagation efficiency. By combining group velocity, phonon lifetime, and phonon scattering rate, the contribution of each phonon mode to thermal conductivity can be calculated. For example, at high temperatures, the scattering between phonons and other phonons is enhanced, leading to a shorter phonon lifetime and thus reducing its contribution to thermal conductivity. Based on these calculations, a set of contribution values for each phonon mode is obtained. Low-frequency phonon modes typically contribute more to thermal conductivity because they have higher group velocities and longer lifetimes at low temperatures. In contrast, high-frequency phonon modes may contribute less due to their stronger scattering effect.
[0052] Specifically, the Boltzmann transport equation considers the heat transfer process of phonons propagating in the crystal and calculates the overall thermal conductivity based on the phonon distribution and the contribution of each phonon mode. By weighting the contributions of different phonon modes, the behavior of all phonon modes at different temperatures can be comprehensively considered to obtain the thermal conductivity of the material.
[0053] It is understood that the executing entity of this application can be a graphene-based material heterostructure directional design system based on thermodynamic property analysis, or it can be a terminal or a server; the specific implementation is not limited here. This application's embodiments use a server as an example for illustration.
[0054] Reference Figure 3 This invention also provides a graphene-based material heterojunction directional design device based on thermodynamic property analysis. This device can be a server, and its internal structure can be as follows: Figure 3As shown, the graphene-based heterojunction directional design device based on thermodynamic property analysis includes a processor, memory, display screen, input device, network interface, and database connected via a system bus. The processor in this computer design provides computational and control capabilities. The memory of the graphene-based heterojunction directional design device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of the graphene-based heterojunction directional design device based on thermodynamic property analysis stores the data corresponding to this embodiment. The network interface of the graphene-based heterojunction directional design device based on thermodynamic property analysis is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the above-described method.
[0055] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the graphene-based material heterojunction directional design device applied thereto based on thermodynamic property analysis.
[0056] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, wherein the computer-readable storage medium stores instructions that, when the instructions are executed on a computer, cause the computer to perform the steps of the graphene-based material heterostructure directional design method based on thermodynamic property analysis.
[0057] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.
[0058] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0059] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.
Claims
1. A method for the design of graphene-based material heterojunctions based on thermodynamic properties analysis, characterized in that, The method comprises: S1, simulating atomic coordinate trajectory data of a graphene-based heterojunction system by using an ab initio molecular dynamics AIMD algorithm; S2, performing time domain Fourier transform on the atomic coordinate trajectory data to determine the vibration frequency spectrum of each atom, and further obtaining the heterojunction periodic structure and the crystal space grid relationship; S3, based on the heterojunction periodic structure and the crystal space grid relationship, using lattice space Fourier transform, mapping the vibration frequency spectrum to reciprocal space to obtain reciprocal space wave vector spectrum; S4, extracting real space vibration modes at a finite temperature from the reciprocal space wave vector spectrum by using inverse Fourier transform technology; S5, based on the real space vibration modes, combining the periodicity of the underlying primitive lattice, calculating the phonon spectrum and thermodynamic properties of the graphene-based heterojunction, and optimizing the heterojunction design based on the thermodynamic properties to obtain an optimized graphene-based heterojunction.
2. The method of claim 1, wherein, The S1 comprises: Simulate a graphene-based heterojunction system by using an ab initio molecular dynamics AIMD algorithm to obtain preliminary atomic coordinate trajectory data; Extracting instantaneous position data of atoms and equilibrium position data of atoms from the preliminary atomic coordinate trajectory data; Performing difference processing on the instantaneous position data and the equilibrium position data to obtain the offset of atomic vibration; Based on the offset of atomic vibration, performing smoothing processing on the preliminary atomic coordinate trajectory data to filter out noise fluctuations to obtain the final atomic coordinate trajectory data.
3. The method of claim 2, wherein, The S2 comprises: Extracting time evolution data of each atom from the atomic coordinate trajectory data; Performing Fourier transform on the time evolution data to obtain vibration mode data; Based on the vibration mode data, calculating the vibration frequency and vibration amplitude of each atom to obtain the vibration frequency spectrum; Based on the vibration frequency spectrum, identifying a characteristic frequency range to obtain an effective phonon mode; Using a peak detection algorithm to process the effective phonon mode to obtain a main vibration mode; Based on the main vibration mode, obtaining a heterojunction periodic structure and determining the interaction relationship between a crystal basic unit and atoms; Based on the interaction relationship, obtaining a wave vector grid relationship in reciprocal space as a crystal space grid relationship.
4. The method of claim 3, wherein, The S3 comprises: Based on the heterojunction periodic structure, determining the correspondence between a crystal basic unit and reciprocal space; According to the crystal space grid relationship, combining the correspondence, establishing a wave vector grid in reciprocal space; Mapping and matching the spatial relationship between the time data in the vibration frequency spectrum and the wave vector grid; Using Fourier transform to process the mapping and matching result to obtain a reciprocal space wave vector spectrum.
5. The method of claim 1, wherein, The S4 comprises: Based on the reciprocal space wave vector spectrum, determining a temperature dependence parameter reflecting the vibration mode under a finite temperature condition; Based on the temperature dependence parameter, combining inverse Fourier transform technology, calculating the vibration amplitude information and vibration mode information of each atom at a finite temperature; Integrating the vibration amplitude information and the vibration mode information and performing smoothing processing to obtain a real space vibration mode at a finite temperature.
6. The method of claim 1, wherein, The S5 comprises: By analyzing the lattice periodic structure and the real-space vibration mode, a phonon mode corresponding to different wave vectors in the crystal is determined; By processing the phonon mode by using a phonon spectrum calculation method, a phonon spectrum is obtained; According to the phonon spectrum, further analysis is performed on the energy distribution corresponding to different phonon modes to obtain a phonon band structure; Based on the phonon band structure, in combination with the phonon distribution under a finite temperature, the thermal conductivity of the graphene-based heterojunction is calculated; By the phonon spectrum, the heat absorbed by the graphene-based heterojunction per unit mass per unit temperature change is calculated to obtain the specific heat of the graphene-based heterojunction; The dependence of the phonon spectrum on the temperature is analyzed to obtain the thermal expansion coefficient of the graphene-based heterojunction; The thermal conductivity, the specific heat and the thermal expansion coefficient are integrated to obtain the thermodynamic properties of the graphene-based heterojunction; Based on the thermodynamic properties, an optimization algorithm is used to design the heterojunction structure to obtain an optimized graphene-based heterojunction.
7. The method of claim 6, wherein, The phonon spectrum calculation method in S5 includes: By using a dynamic matrix reconstruction technology, a dynamic matrix is constructed based on the real-space vibration mode and the interatomic potential; The dynamic matrix is diagonalized to obtain a polarization vector corresponding to the phonon frequency; The polarization vector is projected onto the lattice basis vector direction to obtain the phonon frequency under each wave vector to generate a phonon dispersion relation; Based on the phonon dispersion relation, in combination with the Brillouin zone integration method, the phonon state density is calculated to further obtain a complete phonon spectrum.
8. The method of claim 7, wherein, The method for calculating the thermal conductivity of the material in S5 includes: Based on the phonon spectrum, the group velocity of each phonon mode is obtained; According to the group velocity, in combination with the phonon lifetime information and the phonon scattering rate information, the contribution value of different phonon modes to the thermal conductivity is calculated to obtain a phonon mode contribution value set; By using the Boltzmann transport equation, the phonon mode contribution value set is weighted and integrated to obtain the final thermal conductivity.
9. A device for the directional design of graphene-based material heterojunctions based on thermodynamic property analysis, characterized by, The device includes a memory and at least one processor, and the memory stores instructions; The at least one processor invokes the instructions in the memory to enable the graphene-based material heterojunction directional design device based on thermodynamic property analysis to perform the graphene-based material heterojunction directional design method based on thermodynamic property analysis according to any one of claims 1-8.
10. A computer-readable storage medium having stored thereon instructions, the computer-readable storage medium comprising: The instructions are executed by the processor to implement the graphene-based material heterojunction directional design method based on thermodynamic property analysis according to any one of claims 1-8.