Method for realizing h-BN efficient n-type doping and semiconductor material

Abstract

The invention belongs to the technical field of semiconductor material synthesis, and provides a method for realizing h-BN efficient n-type doping and a semiconductor material, graphene is introduced into hexagonal boron nitride as a quantum dot, the two materials form a type-I type band order difference, a local band edge state is formed, the doping energy level and the relative position of a band edge are changed, and the doping efficiency is improved. According to the method, the activation energy of the n-type dopant is compensated by utilizing the band order difference between graphene and an h-BN energy band, the ionization efficiency of doped atoms at the temperature of a working substance is improved, the carrier concentration is increased, the doping efficiency and the conductivity of the h-BN are improved, guidance is provided for realizing an h-BN material with high electron concentration, and the application prospect of the h-BN in power electronic devices is widened.

Description

Technical Field

[0001] The present invention belongs to the technical field of semiconductor material synthesis, and particularly relates to a method for realizing efficient n-type doping of h-BN and a wide-bandgap semiconductor material. Background Art

[0002] As an ultra-wide-bandgap two-dimensional semiconductor material, h-BN has a bandgap width of about 6.2 eV and has many excellent physical and chemical properties, such as excellent thermal stability and chemical stability; excellent in-plane thermal conductivity; and optical transparency, etc. Therefore, it is widely used in fields such as high-performance heat dissipation materials, electronic devices, and optical devices. Due to its relatively wide bandgap width and excellent optical properties, it has great application potential in deep ultraviolet light emission and detection devices and photoluminescence devices. In addition, in terms of electrical properties, h-BN also has a wide range of applications. For example, at room temperature, h-BN has excellent electrical insulation properties and can be used as a good gate insulating material in field-effect transistors; h-BN can also be doped with C, Si, or Be, Mg to achieve n-type or p-type conductivity and become a semiconductor material with excellent performance, so it can be used as a communication window material such as a triode.

[0003] h-BN belongs to an ultra-wide-bandgap semiconductor, so intrinsic h-BN is a good insulating material. To broaden the application of h-BN in the field of power electronic devices, it is first necessary to realize h-BN materials with different conduction types through doping. At present, p-type doping of h-BN can be achieved by doping elements such as Be, Mg, Zn, etc. For example, doping Be element by ion implantation can make the hole concentration of h-BN reach 3×10 19 cm -3 , but for n-type doping, there are still some problems at present. In recent years, through in-situ doping methods, using techniques such as RF sputtering, ion implantation, metal-organic chemical vapor deposition (MOCVD), etc., n-type doping of h-BN has been achieved by doping S, Si. However, the prepared annealed samples still show insulating properties at room temperature. The activation energy is about 1.2 eV, which is at a relatively high level. Therefore, the highest electron concentration is only 10 12 cm -3 ~10 15 cm -3 . Compared with p-type doping, the efficient n-type doping of h-BN still faces huge challenges. The main reason for the difficulty of n-type doping of h-BN is that as a wide-bandgap semiconductor, the valence band top of h-BN is much higher than that of other semiconductor materials. Therefore, the doping energy levels of common dopants tend to be localized in the middle of the bandgap, forming deep-level doping. That is to say, the activation energy of h-BN n-type dopants is too high, and it is difficult to ionize to generate carriers at working temperatures, which is the main reason restricting its doping efficiency.

[0004] This phenomenon in semiconductors where only one type of efficient doping can be achieved, and not both types simultaneously, is called doping asymmetry. This problem is particularly evident in wide-bandgap semiconductors. For example, n-type doping of diamond is much more difficult than p-type doping, and it is difficult to achieve effective p-type doping in Ga2O3. The doping asymmetry problem severely limits the application of wide-bandgap semiconductors.

[0005] Too high activation energy is the main cause of the doping asymmetry problem. Activation energy can be understood as the excitation of electrons (holes) from the doping energy level to the bottom of the conduction band (top of the valence band). Therefore, there are mainly two ways to reduce the activation energy: 1. Adjust the doping energy level to be closer to the band edge; 2. Adjust the band edge to be closer to the doping energy level. For the first approach, many solutions have been proposed by current researchers. For example, using the polarization effect to improve the p-type doping efficiency of AlGaN materials, but this method is only applicable to materials with polarization effects; or using the Coulomb repulsion of donor-acceptor pairs to shift the doping energy level towards the band edge, but due to the different wave function characteristics and symmetries of donor-acceptor impurities, the adjustment range is very limited; δ-doping is to obtain a certain broadening of the doping energy level by increasing the local doping concentration, but due to the small effective Bohr radius of the dopant and the strong locality of the doping energy level, the adjustment range is also very limited.

[0006] Generally speaking, the method of adjusting the doping energy level has certain limitations. Therefore, adjusting the band edge may be a new direction to solve the doping asymmetry problem of wide-bandgap semiconductors. Summary of the Invention

[0007] In view of this, the present invention aims to provide a method for achieving efficient n-type doping of h-BN and a semiconductor material to achieve high-efficiency n-type doping efficiency of h-BN.

[0008] To achieve the above object, the technical solution of the present invention is realized as follows: One of the purposes of this application is to provide a method for achieving efficient n-type doping of h-BN, including the following steps: Introduce graphene quantum dots into the h-BN material to form an h-BN: Gra QDs system; Verify the thermodynamic stability of the h-BN: Gra QDs system; Verify the energy band structure of the h-BN: Gra QDs system; Verify the doping effect of the h-BN: Gra QDs system; Verify the electrical conductivity of the h-BN: Gra QDs system.

[0009] In some of these embodiments, in the step of introducing graphene quantum dots into the h-BN material to form the h-BN: Gra QDs system, the following specific steps are included: expanding the primitive cell of the h-BN material, constructing a supercell of appropriate size for the intrinsic material, and replacing some of the B-N atom pairs in the supercell with C atoms to form graphene quantum dots, so as to form the h-BN: Gra QDs system.

[0010] In some of these embodiments, in the step of verifying the thermodynamic stability of the h-BN: Gra QDs system, the following specific steps are included: Fixing the lattice of the h-BN: Gra QDs system and performing structural optimization on the atomic positions using the VASP software; Calculating the phonon spectrum of the h-BN: Gra QDs system using the phonopy software for the h-BN: Gra QDs system after structural optimization.

[0011] In some of these embodiments, in the step of verifying the band structure of the h-BN: Gra QDs system, the following specific steps are included: Calculating the band unfolding structure and density of states of the h-BN: Gra QDs system using the DFT method; Verifying the influence of the local states of the graphene quantum dots on the h-BN band edge structure according to the density of states.

[0012] In some of these embodiments, in the step of verifying the doping effect of the h-BN: Gra QDs system, the following specific steps are included: By calculating different doping sites, selecting the activation energy and formation energy of different n-type dopants at each doping site to verify the effect of graphene quantum dots in the h-BN: Gra QDs system on reducing the doping activation energy; Determining the optimal doping position with a lower doping activation energy and a larger overlap of wave functions by analyzing the overlap of the wave functions of the dopant atoms at different doping positions with the graphene quantum dots; By calculating the doping concentration and carrier concentration of different dopants at the optimal doping position and simulating the influence of different growth temperatures and working temperatures on the doping effect, to optimize the doping effect and temperature conditions.

[0013] In some of these embodiments, in the step of verifying the effect of graphene quantum dots in the h-BN: Gra QDs system on reducing the doping activation energy by calculating different doping sites and selecting the activation energy and formation energy of different n-type dopants at each doping site, it specifically includes: Doping sites at different positions from the graphene quantum dots are selected. After the structural optimization of each doping site, the self-consistent energy calculation is carried out using the HSE hybrid functional method to obtain the activation energy and formation energy of different n-type dopants at each doping site, so as to verify the effect of graphene quantum dots on reducing the doping activation energy in the h-BN: Gra QDs system. The n-type dopants include C or Si or Ge.

[0014] In some of these embodiments, in the step of determining the optimal doping position with a lower dopant activation energy and a larger wave function overlap by analyzing the overlap of the wave functions of the dopant atoms at different doping positions with the band edge of the graphene quantum dots, the following specific steps are included: comparing the activation energy results before and after introducing the graphene quantum dots to verify that the graphene quantum dots reduce the activation energy of the n-type dopants; Calculate and output the band edge wave function of the h-BN: Gra QDs system through the VASP software to explore the wave function overlap of the dopant atoms, quantum dots, and h-BN in the h-BN: Gra QDs system; By analyzing the reduction of the dopant activation energy and the degree of wave function overlap, it is determined that the optimal doping position is the place in h-BN close to the graphene quantum dots.

[0015] In some of these embodiments, in the step of optimizing the doping effect and temperature conditions by calculating the doping concentration and carrier concentration of different dopants at the optimal doping position and simulating the influence of different growth temperatures and working temperatures on the doping effect, the following specific steps are included: Determine the optimal doping position and calculate the doping concentration and carrier concentration of different dopants at this position; Change the doping temperature. According to the previously calculated formation energy and activation energy of different dopants, obtain the doping concentration and carrier concentration at different growth temperatures when the dopant atoms are at the optimal doping position, and obtain the influence of different growth temperatures on the doping effect; Calculate the doping concentration and carrier concentration in the intrinsic h-BN material without introducing graphene quantum dots, and compare the doping effects of the same dopant before and after introducing graphene quantum dots at different temperatures to determine the optimal doping temperature; Further optimize the doping effect by adjusting the doping concentration of different dopants in combination with the optimal doping temperature.

[0016] In some of these embodiments, in the step of verifying the electrical conductivity of the h-BN: Gra QDs system, the following specific steps are included: Use the Nanodcal software to calculate the I-V characteristic curve of the h-BN: Gra QDs system under different bias voltages using the non-equilibrium Green's function method; Simulate and calculate the conductivity and resistivity of h-BN materials under different doping conditions, and combine the doping concentration and temperature conditions to verify the improvement of the conductivity of h-BN materials by graphene quantum dots.

[0017] Secondly, this application also provides a wide-bandgap semiconductor material prepared by the method for realizing efficient n-type doping of h-BN.

[0018] Compared with the prior art, the present invention can achieve the following beneficial effects: The method for realizing efficient n-type doping of h-BN and the semiconductor material provided by this application introduce graphene as quantum dots into hexagonal boron nitride (h-BN). The two materials form a type-I band offset, forming local band-edge states, changing the relative positions of the doping energy level and the band edge, using the band offset between the energy bands of graphene and h-BN to compensate for the activation energy of n-type dopants, improving the ionization efficiency of doping atoms at the working temperature, increasing the carrier concentration, improving the doping efficiency and the conductivity of h-BN, providing guidance for realizing h-BN materials with high electron concentration, and broadening the application prospects of h-BN in power electronic devices. Description of the Drawings

[0019] The drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The schematic embodiments and descriptions of the present invention are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings: Figure 1 is a flowchart of the steps of the method for realizing efficient n-type doping of h-BN provided by the embodiment of this application.

[0020] Figure 2 is a schematic diagram of the h-BN: Gra QDs structure provided by the embodiment of this application.

[0021] Figure 3 is a phonon spectrum diagram of the h-BN: Gra QDs system calculated by the embodiment of this application.

[0022] Figure 4 is a schematic diagram of the energy band unfolding of the h-BN: Gra QDs system calculated by the embodiment of this application.

[0023] Figure 5 is a schematic diagram of modeling for selecting different doping sites after introducing graphene as a quantum structure into h-BN provided by the embodiment of this application.

[0024] Figure 6 is a schematic diagram of the change in the activation energy of different dopants at different doping sites before and after introducing Gra QDs into h-BN provided by the embodiment of this application.

[0025] Figure 7 It is a schematic diagram of the band-edge wave function overlap when C is doped in the h-BN: Gra QDs system provided by the embodiment of the present application.

[0026] Figures 8(a) and (b) are respectively schematic diagrams of the doping concentration and carrier concentration in the h-BN: Gra QDs system provided by the embodiment of the present application.

[0027] Figure 9 It is a schematic diagram of the model for calculating the I-V characteristic curve of the h-BN: Gra QDs system provided by the embodiment of the present application.

[0028] Figure 10 They are the I-V characteristic curves calculated under different conditions when C is doped, provided by the embodiment of the present application. Detailed implementation manners

[0029] In order to make the purpose, technical solutions and advantages of the present invention clearer, the following further describes the present invention in detail with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, rather than limiting the present invention. Similar elements in different embodiments are labeled with related similar element numbers. In the following embodiments, many detailed descriptions are provided to enable a better understanding of the present invention. However, those skilled in the art can easily recognize that some of the features can be omitted in different situations, or can be replaced by other elements, materials, or methods. In some cases, some operations related to the present invention are not shown or described in the specification, which is to avoid the core part of the present invention being overwhelmed by excessive descriptions. For those skilled in the art, it is not necessary to describe these related operations in detail, and they can fully understand the related operations based on the descriptions in the specification and the general technical knowledge in the art.

[0030] It should be noted that, without conflict, the embodiments and features in the embodiments of the present invention can be combined with each other to form various implementation manners. At the same time, the steps or actions in the method description can also be adjusted in the order that is obvious to those skilled in the art. Therefore, the various orders in the specification and drawings are only for clearly describing a certain embodiment, and do not mean that they are the necessary orders, unless it is stated that a certain order must be followed.

[0031] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention. In addition, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first", "second", etc. may explicitly or implicitly include one or more of such features. In the description of the present invention, unless otherwise specified, the meaning of "a plurality" is two or more.

[0032] In the description of the present invention, it should be noted that unless otherwise clearly defined and limited, the terms "mounted", "connected", "coupled" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood through specific circumstances.

[0033] The present invention will be described in detail below with reference to the drawings and in conjunction with embodiments.

[0034] As Figure 1 shown, it is a step flow chart of a method for realizing efficient n-type doping of h-BN provided by an embodiment of the present application, including the following steps S110 to step S150. The implementation manners of each step are described in detail below.

[0035] Step S110: Introduce graphene quantum dots into the h-BN material to form an h-BN: Gra QDs system.

[0036] In this embodiment, first, the Material Studio software is used to expand the primitive cell of h-BN, construct a supercell of a suitable size for the intrinsic material, and replace some B-N atom pairs in the supercell with C atoms to form graphene quantum dots (Graphene Quantum Dots, Gra QDs) to form the h-BN: Gra QDs system structure. Please refer to Figure 2 .

[0037] It can be understood that in this embodiment, by introducing graphene quantum dots into the h-BN material to form a type-I heterojunction, the relative positions of the energy band structure and doping energy levels of the h-BN material are adjusted, the activation energy of the n-type dopant is reduced, and the doping efficiency is improved.

[0038] Furthermore, the morphology of the quantum heterojunction includes quantum dots, nanowires, quantum wells, etc. After introducing the graphene quantum structure into h-BN, theoretical simulation calculations are carried out and the system structure is optimized to verify the stability of the system.

[0039] Step S120: Verify the thermodynamic stability of the h-BN: Gra QDs system.

[0040] In this embodiment, for the system (h-BN: Gra QDs) after introducing the graphene quantum structure into h-BN, the stability and rationality of the system are verified by calculating thermodynamic properties such as phonon spectra. The specific steps are as follows: Please refer to Figure 2 As shown, fix the lattice of the h-BN: Gra QDs system, and use the VASP software to fully optimize the atomic positions to reach the convergence accuracy, where: the cut-off energy is set to 500 eV, the energy convergence progress is 10-5 eV, and the force convergence accuracy is set to 0.02 eV / Å; for the h-BN: Gra QDs system after structure optimization, use the phonopy software to calculate the phonon spectrum of the h-BN: Gra QDs system to prove the rationality of the structure design. The calculation results are as Figure 3 shown, from Figure 3 it can be seen that there are no imaginary frequencies, proving that the system has thermodynamic stability.

[0041] Step S130: Verify the energy band structure of the h-BN: Gra QDs system.

[0042] In this embodiment, the energy band structure, density of states and other electronic structure information of the h-BN: Gra QDs system are calculated, and the local band edge states introduced by the graphene quantum dots and their influence on the energy band structure of the h-BN material are analyzed. The specific steps are as follows: Use the DFT method to calculate the energy band unfolding structure and density of states of the h-BN:Gra QDs system, specifically: use the DFT method to calculate the energy band unfolding structure and density of states (DOS) of the h-BN:Gra QDs system. The results are as Figure 4 shown. Through calculation, it is found that graphene and h-BN have a type-I band offset, that is, graphene quantum dots can effectively introduce local band edge states, adjust the relative positions of the band edges and doping energy levels of h-BN, and thus effectively reduce the activation energy of the n-type dopant.

[0043] Verify the influence of the local states of the graphene quantum dots on the band-edge structure of h-BN according to the density of states. Specifically, by calculating the density of states, verify the influence of the local states of the graphene quantum dots on the band-edge structure of h-BN. This step provides a theoretical basis for the subsequent reduction of the activation energy of the dopant.

[0044] Step S140: Verify the doping effect of the h-BN: Gra QDs system.

[0045] In this embodiment, in the step of verifying the doping effect of the h-BN: Gra QDs system, the following steps are specifically included: Step S141: By calculating different doping sites, select the activation energy and formation energy of different n-type dopants at each doping site to verify the effect of graphene quantum dots in the h-BN: Gra QDs system on reducing the doping activation energy.

[0046] In this embodiment, select doping sites at different positions from the graphene quantum dots. After optimizing the structure of each doping site, perform self-consistent energy calculations using the HSE hybrid functional method to obtain the activation energy and formation energy of different n-type dopants at each doping site, so as to verify the effect of graphene quantum dots in the h-BN: Gra QDs system on reducing the doping activation energy. The n-type dopants include C or Si or Ge.

[0047] Specifically, as Figure 5 shown, in this embodiment, select doping sites at different positions from the graphene quantum dots. After optimizing the structure of each doping site, perform self-consistent energy calculations using the HSE hybrid functional method. Calculate the activation energy and formation energy of n-type dopants (such as C, Si, Ge) at different positions.

[0048] Specifically, the formation energy calculation formula is as follows: 1 Among them, ( ) represents the total energy of the supercell containing point defects in the charged state X , q ( ) represents the total energy of the supercell without point defects, represents the chemical formula of the introduced point defect impurity atom, then represents the chemical formula of the atom replaced after introducing the point defect, E F represents the Fermi level, E V represents the valence band top, It is a correction term after electrostatic potential alignment of the supercell with defects and the supercell without defects.

[0049] Specifically, the activation energy calculation formula is as follows: 2.

[0050] It can be understood that in this embodiment, by calculating different doping sites, the activation energy and formation energy of different n-type dopants (such as C, Si, Ge) at each doping site are selected to verify the effect of graphene quantum dots on reducing the doping activation energy.

[0051] Step S142: By analyzing the overlap of the wave functions of the dopant atoms at different doping positions with the band edges of the graphene quantum dots, determine the optimal doping position with a lower dopant activation energy and a larger wave function overlap.

[0052] In this embodiment, in the step of determining the optimal doping position with a lower dopant activation energy and a larger wave function overlap by analyzing the overlap of the wave functions of the dopant atoms at different doping positions with the band edges of the graphene quantum dots, the following specific steps are included: Step S1421: Compare the activation energy results before and after introducing the graphene quantum dots to verify that the graphene quantum dots reduce the activation energy of the n-type dopant.

[0053] In this embodiment, compare the activation energy results before and after introducing the graphene quantum dots to verify that the graphene quantum dots can effectively reduce the activation energy of the n-type dopant. For example, select the optimal doping position and calculate the activation energy of each dopant at this position. The calculated activation energy is as Figure 6 shown. It is found that the doping sites near the graphene quantum dots have a lower activation energy.

[0054] Step S1422: Calculate and output the band edge wave function situation of the h-BN: Gra QDs system through the VASP software, and explore the wave function overlap situation of the dopant atoms, quantum dots, and h-BN in the h-BN: Gra QDs system.

[0055] Step S1423: By analyzing the reduction of the dopant activation energy and the degree of wave function overlap, determine that the optimal doping position is the place near the graphene quantum dots in h-BN.

[0056] It can be understood that in this embodiment, the band edge wave function situation of the entire system is calculated and output through the VASP software, and the wave function overlap situation of the dopant atoms, quantum dots, and h-BN in the h-BN: Gra QDs system is explored to verify the improvement effect of graphene quantum dots on the ionization efficiency of the dopant. The results are as Figure 7As shown. By analyzing the reduction of dopant activation energy and the degree of wave function overlap, the optimal doping position is determined to be the place in h-BN close to the graphene quantum dot.

[0057] Step S143: Optimize the doping effect and temperature conditions by calculating the doping concentration and carrier concentration of different dopants at the optimal doping position, and simulating the influence of different growth temperatures and working temperatures on the doping effect.

[0058] In this embodiment, in the step of optimizing the doping effect and temperature conditions by calculating the doping concentration and carrier concentration of different dopants at the optimal doping position, and simulating the influence of different growth temperatures and working temperatures on the doping effect, the following steps are specifically included: Step S1431: Determine the optimal doping position and calculate the doping concentration and carrier concentration of different dopants at this position.

[0059] In this embodiment, according to the foregoing calculation, select the optimal doping position and calculate the doping concentration and carrier concentration of different dopants at this position. The specific calculation method is as follows: Charge state q in X the equilibrium concentration of ([[]] ) is a function of its formation energy E form and its relationship can be expressed as: 3 Where: is the formation energy of the defect X , is the number of defect points per unit volume, is the degeneracy factor, indicating the possible configurations of electrons occupying the defect layer, which changes with the charge state q and is the Boltzmann constant and T is the temperature.

[0060] Donor (acceptor) defects ionize to generate electrons (holes), resulting in charged state defects ( ). The equilibrium intrinsic carrier concentration can be calculated by the following formula: and 4 Where: N V and N C are the effective density of states at the valence band and conduction band edges respectively. The Fermi level (E_F), carrier concentration, and defect density of different charge states under different chemical potential conditions can be determined by self-consistently solving the charge neutrality condition:

[0061] It can be understood that based on the above, the optimal doping position and the doping concentrations and carrier concentrations of different dopants at this position can be obtained.

[0062] Step S1432: Change the doping temperature. According to the formation energies and activation energies of different dopants calculated previously, obtain the doping concentrations and carrier concentrations at different growth temperatures when the dopant atoms are located at the optimal doping position, and obtain the influence of different growth temperatures on the doping effect.

[0063] Step S1433: Calculate the doping concentration and carrier concentration in the intrinsic h-BN material without introducing graphene quantum dots, and compare the doping effects of the same dopant before and after introducing graphene quantum dots at different temperatures to determine the optimal doping temperature.

[0064] It should be noted that since defects are generated during the high-temperature growth process of semiconductor materials and then ionize during the rapid thermal annealing process, generating carriers and defects with different charge states. Therefore, first solve Equation 5 under high-temperature growth conditions to obtain the Fermi levels and densities of each defect with different charge states. q Then, solve Equation 5 again at a lower working temperature. At this time, the defect densities with different charge states will redistribute according to the Fermi-Dirac distribution. Thus, the Fermi level at the working temperature can be obtained, and then the redistributed defect density and carrier density can be calculated. By changing the temperature, according to the formation energies and activation energies of different dopants calculated previously, calculate the doping concentrations and carrier concentrations at different growth temperatures when the dopant atoms are located at the optimal doping position, obtain the influence of different growth temperatures on the doping effect, further calculate the doping concentration and carrier concentration in the intrinsic h-BN material without introducing graphene quantum dots, and compare the doping effects of the same dopant before and after introducing graphene quantum dots at different temperatures to determine the optimal doping temperature. Step S1434: Further optimize the doping effect by adjusting the doping concentrations of different dopants in combination with the optimal doping temperature.

[0065] It can be understood that by adjusting the doping concentrations of different dopants in combination with the optimal temperature conditions, the doping effect is further optimized. The calculated doping concentrations and carrier concentrations at different doping positions are shown in Figures 8(a) and 8(b). The experimental and calculated results show that graphene quantum dots can significantly improve the ionization efficiency of dopants, thereby improving the electrical conductivity of h-BN materials.

[0066] It can be understood that by calculating the doping concentrations and carrier concentrations of different dopants at the optimal doping positions and simulating the effects of different growth temperatures and working temperatures on the doping effect, the doping effect and temperature conditions can be optimized.

[0067] Step S150: Verify the electrical conductivity of the h-BN: Gra QDs system.

[0068] In this embodiment, in the step of verifying the electrical conductivity of the h-BN: Gra QDs system, it specifically includes the following steps: Using Nanodcal software, the non-equilibrium Green's function method is used to calculate the I-V characteristic curves of the h-BN: Gra QDs system under different bias voltages; The conductivity and resistivity of the h-BN material under different doping conditions are simulated and calculated, and combined with the doping concentration and temperature conditions to verify that the graphene quantum dots improve the electrical conductivity performance of the h-BN material.

[0069] Specifically, in order to verify the improvement effect of graphene quantum dots on the conductive characteristics of h-BN, it is necessary to calculate the carrier mobility, conductivity and other characteristics of the h-BN material. The specific steps are as follows: I-V characteristic defect calculation: By designing Figure 9 the shown structural model, using Nanodcal software, the non-equilibrium Green's function method is used to calculate the I-V characteristic curves under different bias voltages. The I-V characteristic curves of four structures, namely intrinsic h-BN, doped h-BN, h-BN with graphene quantum dots introduced, and h-BN with graphene quantum dots introduced and dopants doped, are calculated respectively. The calculation results are as Figure 10 shown. The results show that the graphene quantum dots significantly improve the electron mobility of h-BN.

[0070] Resistivity calculation: The resistivity of the h-BN material under different doping conditions is simulated and calculated, and combined with the doping concentration and temperature conditions to verify that the graphene quantum dots can improve the electrical conductivity performance of the h-BN material. The calculated resistivity is much lower than the previous reports, effectively proving that by introducing graphene quantum dots, the doping efficiency can be effectively improved and the electrical conductivity of h-BN can be enhanced.

[0071] It can be understood that in this embodiment, by calculating the carrier mobility, conductivity and other characteristics of the h-BN material with and without graphene quantum structures, the improvement effect of graphene quantum dots on the electrical conductivity performance of the h-BN material is verified.

[0072] The method for realizing efficient n-type doping of h-BN provided by the present invention innovatively proposes a quantum heterojunction doping method. By introducing graphene as quantum dots into h-BN, a type-I heterojunction is formed to adjust the relative positions of the band edges and doping energy levels, so as to achieve the goal of reducing the activation energy of n-type dopants and improving the doping efficiency.

[0073] Verification of quantum heterojunction morphology selection and structural stability provided by the above embodiments of the present application: Considering different quantum structure morphologies, such as quantum dots, nanowires, quantum wells, etc., a theoretical simulation calculation model is designed, and the stability of the entire system (h-BN: Gra QDs) after introducing graphene quantum structures into h-BN is verified. The system structure is relaxed and optimized, and through the calculation of thermodynamic properties such as phonon spectra, the rationality and stability of the designed system are verified.

[0074] Verification of energy band structure provided by the above embodiments of the present application: On the basis of verifying rationality and stability, electronic structure information such as the energy band structure and density of states of h-BN: Gra QDs is calculated, and it is analyzed and verified that graphene quantum dots can change the band edge structure of h-BN, introducing local band edge states, and the feasibility of the energy band structure of the system and the doping method of the quantum heterojunction is verified.

[0075] Verification of the effectiveness of h-BN-graphene quantum heterojunction doping provided by the above embodiments of the present application: Further select doping sites at different positions from the quantum dots, calculate the activation energy, formation energy, etc. of common n-type dopants C, Si, Ge at different doping sites, and compare with the results of directly doping h-BN to verify that the graphene quantum structure can effectively reduce the activation energy; further analyze the overlap of the wave functions of the dopant atoms at different doping positions with the band edge of the graphene quantum dots, and combine the activation energy at each position to determine the best doping position with low activation energy and large wave function overlap; through the above calculations, the effectiveness of doping h-BN with the graphene quantum structure is verified.

[0076] Verification of the doping effect of h-BN-graphene quantum heterojunction provided by the above embodiments of the present application: After determining the best doping position by combining the activation energy and wave function overlap, further calculate the doping concentration, carrier concentration, etc. of different dopants at the best doping position, and simulate and calculate the influence of different growth temperatures and working temperatures on the doping effect of the dopants, and complete the determination of the doping effect of h-BN-graphene quantum heterojunction and the best doping temperature and working temperature.

[0077] Improvement of the transport properties of h-BN materials by the graphene quantum structure provided by the above embodiments of the present application: By calculating the mobility, conductivity and other properties of carriers in h-BN with and without the graphene quantum structure, the improvement of the conductive properties of h-BN materials by the graphene quantum dots is verified.

[0078] The method and semiconductor material for realizing efficient n-type doping of h-BN provided by this application introduce graphene as quantum dots into hexagonal boron nitride (h-BN). The two materials form a type-I band offset, forming local band-edge states, changing the relative positions of the doping energy level and the band edge, and using the band offset between the energy bands of graphene and h-BN to compensate for the activation energy of n-type dopants, improving the ionization efficiency of doping atoms at the working temperature, increasing the carrier concentration, improving the doping efficiency and the conductivity of h-BN, providing guidance for realizing h-BN materials with high electron concentration, and broadening the application prospects of h-BN in power electronic devices.

[0079] It should be understood that various forms of the processes shown above can be used, steps can be reordered, added or deleted. For example, the steps recited in the disclosure of the present invention can be executed in parallel, sequentially or in a different order, as long as the desired results of the technical solutions disclosed in the present invention can be achieved, and no limitations are imposed herein.

[0080] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for realizing efficient n-type doping of h-BN, characterized in that: Including the following steps: Introduce graphene quantum dots into h-BN material to form an h-BN: Gra QDs system; Verify the thermodynamic stability of the h-BN: Gra QDs system; Verify the energy band structure of the h-BN: Gra QDs system; Verify the doping effect of the h-BN: Gra QDs system; Verify the electrical conductivity of the h-BN: Gra QDs system.

2. The method for realizing efficient n-type doping of h-BN according to claim 1, wherein: In the step of introducing graphene quantum dots into h-BN material to form an h-BN: Gra QDs system, it specifically includes the following steps: expand the primitive cell of the h-BN material, construct the supercell of the intrinsic material, and replace some B-N atom pairs in the supercell with C atoms to form graphene quantum dots, so as to form an h-BN: Gra QDs system.

3. The method for realizing efficient n-type doping of h-BN according to claim 1, characterized in that: In the step of verifying the thermodynamic stability of the h-BN:Gra QDs system, it specifically includes the following steps: Fix the lattice of the h-BN: Gra QDs system and optimize the atomic positions with VASP software; Use phonopy software to calculate the phonon spectrum of the h-BN: Gra QDs system after structural optimization.

4. The method for realizing efficient n-type doping of h-BN according to claim 1, characterized in that: In the step of verifying the energy band structure of the h-BN:Gra QDs system, it specifically includes the following steps: Use the DFT method to calculate the energy band unfolding structure and density of states of the h-BN:Gra QDs system; Verify the influence of the local states of the graphene quantum dots on the h-BN band edge structure according to the density of states.

5. The method for realizing efficient n-type doping of h-BN according to claim 1, characterized in that: In the step of verifying the doping effect of the h-BN:Gra QDs system, it specifically includes the following steps: By calculating different doping sites, select the activation energy and formation energy of different n-type dopants at each doping site to verify the effect of graphene quantum dots in the h-BN: Gra QDs system on reducing the doping activation energy; Determine the optimal doping position with lower doping activation energy and larger wave function overlap by analyzing the overlap of the wave functions of the dopant atoms and graphene quantum dots at different doping positions; By calculating the doping concentration and carrier concentration of different dopants at the optimal doping position and simulating the influence of different growth temperatures and working temperatures on the doping effect, optimize the doping effect and temperature conditions.

6. The method for realizing efficient n-type doping of h-BN according to claim 5, wherein: In the step of verifying the effect of graphene quantum dots in the h-BN: Gra QDs system on reducing the doping activation energy by calculating different doping sites and selecting the activation energy and formation energy of different n-type dopants at each doping site, it specifically includes: Select doping sites at different distances from the graphene quantum dots. After optimizing the structure of each doping site, perform self-consistent energy calculations using the HSE hybrid functional method to obtain the activation energy and formation energy of different n-type dopants at each doping site, so as to verify the effect of graphene quantum dots in the h-BN: Gra QDs system on reducing the doping activation energy. The n-type dopants include C or Si or Ge.

7. The method for realizing efficient n-type doping of h-BN according to claim 5, characterized in that: In the step of determining the optimal doping position with a lower dopant activation energy and a larger wave function overlap by analyzing the overlap of dopant atoms at different doping positions with the edge wave function of graphene quantum dots, the following specific steps are included: Compare the activation energy results before and after introducing graphene quantum dots to verify that graphene quantum dots reduce the activation energy of n-type dopants; Calculate and output the edge wave function of the h-BN: Gra QDs system by VASP software to explore the wave function overlap of dopant atoms, quantum dots, and h-BN in the h-BN:Gra QDs system; Determine that the optimal doping position is the place in h-BN close to graphene quantum dots by analyzing the reduction of dopant activation energy and the degree of wave function overlap.

8. The method for realizing efficient n-type doping of h-BN according to claim 5, characterized in that: In the step of optimizing the doping effect and temperature conditions by calculating the doping concentration and carrier concentration of different dopants at the optimal doping position and simulating the influence of different growth temperatures and working temperatures on the doping effect, the following specific steps are included: Determine the optimal doping position and calculate the doping concentration and carrier concentration of different dopants at this position; Change the doping temperature, and according to the formation energy and activation energy of different dopants calculated previously, obtain the doping concentration and carrier concentration at different growth temperatures when the dopant atoms are at the optimal doping position, and get the influence of different growth temperatures on the doping effect; Calculate the doping concentration and carrier concentration in the h-BN material without introducing graphene quantum dots, and compare the doping effects of the same dopant before and after introducing graphene quantum dots at different temperatures to determine the optimal doping temperature; Further optimize the doping effect by adjusting the doping concentration of different dopants and combining the optimal doping temperature.

9. The method for realizing efficient n-type doping of h-BN according to claim 1, wherein: In the step of verifying the electrical conductivity of the h-BN:Gra QDs system, the following specific steps are included: Use Nanodcal software to calculate the I-V characteristic curve of the h-BN: Gra QDs system under different bias voltages by the non-equilibrium Green's function method; Simulate and calculate the conductivity and resistivity of the h-BN material under different doping conditions, and combine the doping concentration and temperature conditions to verify that graphene quantum dots improve the electrical conductivity of the h-BN material.

10. A semiconductor material, characterized in that: Prepared by the method for realizing efficient n-type doping of h-BN according to any one of claims 1 to 9.

Images