Hamiltonian parameter determination method and device, equipment and medium

Abstract

The invention provides a Hamiltonian parameter determination method and device, equipment and a medium. The Hamiltonian parameter determination method comprises the following steps: calculating a first nanowire energy band value for a target size of a target material by using a first principle; based on the Hamiltonian model of the target material, constructing a Hamiltonian matrix of the target size, and calculating according to the Hamiltonian matrix to obtain a second nanowire energy band value of the target size of the target material; the optimized Hamiltonian parameter of the Hamiltonian model is calculated according to the energy band value of the first nanowire and the energy band value of the second nanowire, that is, the Hamiltonian model of the target material is corrected by combining the accurate energy band value of the first nanowire with the energy band value of the second nanowire; therefore, the optimized Hamiltonian parameter of the optimized Hamiltonian model is obtained, the Hamiltonian parameter of the small-size ring gate nanowire field effect transistor is re-determined, the Hamiltonian parameter is used for device simulation, and the device simulation accuracy is improved.

Description

Technical Field

[0001] The present invention relates to the field of semiconductors, and in particular to a method, device, equipment and medium for determining Hamiltonian parameters. Background Art

[0002] With the continuous development of complementary metal oxide semiconductor (CMOS) technology, suppressing the short channel effect in semiconductor devices has become an urgent task. Ring gate nanowire field effect transistors are gradually replacing fin field effect transistors (FinFETs) with their excellent gate control characteristics and becoming the mainstream logic device structure.

[0003] Currently, simulation software is commonly used to simulate gate-all-around nanowire field-effect transistors to study their performance. However, as the size of gate-all-around nanowire field-effect transistors continues to decrease and materials become nanoscale, a series of significant quantum effects, surface effects, lattice distortion, and defects have made the default material parameters no longer applicable, such as the Hamiltonian parameters, no longer accurate.

[0004] Therefore, there is an urgent need to redefine the material parameters of small-sized ring-gate nanowire field-effect transistors to improve the accuracy of device simulation. Summary of the Invention

[0005] In view of this, the purpose of the present application is to provide a method, device, equipment and medium for determining Hamiltonian parameters, which can redefine the Hamiltonian parameters of small-sized ring-gate nanowire field-effect transistors and improve the accuracy of device simulation.

[0006] To achieve the above objectives, this application has the following technical solutions:

[0007] This application provides a method for determining Hamiltonian parameters, comprising:

[0008] Calculate the first nanowire energy band value for the target material and target size using first principles;

[0009] constructing a Hamiltonian matrix of the target size based on a Hamiltonian model of the target material, and calculating a second nanowire energy band value of the target size for the target material according to the Hamiltonian matrix;

[0010] The optimized Hamiltonian parameters of the Hamiltonian model are calculated according to the first nanowire energy band value and the second nanowire energy band value.

[0011] Optionally, the calculating of the first nanowire energy band value of the target size for the target material using the first principles includes:

[0012] Constructing a nanowire lattice structure with a target size and a target crystalline phase for a target material;

[0013] The energy band of the nanowire lattice structure is calculated using a density functional method to obtain a first nanowire energy band value.

[0014] Optionally, constructing the Hamiltonian matrix of the target size based on the Hamiltonian model of the target material, and calculating the second nanowire energy band value of the target size of the target material according to the Hamiltonian matrix includes:

[0015] Based on the Hamiltonian model of the target material, constructing the Hamiltonian matrix of the target size and target crystal phase;

[0016] Discretizing the Hamiltonian matrix to obtain a nanowire Hamiltonian form;

[0017] The second nanowire energy band value for the target size and target crystal phase of the target material is calculated according to the nanowire Hamiltonian form.

[0018] Optionally, the performing discretization processing on the Hamiltonian matrix to obtain the nanowire Hamiltonian form includes:

[0019] Discretizing the Hamiltonian matrix to obtain a real-space nanowire Hamiltonian form;

[0020] Converting the nanowire Hamiltonian form in the real space into a nanowire Hamiltonian form in the moduli space by reducing the dimensionality of the nanowire Hamiltonian form in the real space;

[0021] The second nanowire energy band value for the target size and target crystal phase of the target material is calculated according to the nanowire Hamiltonian form, comprising:

[0022] The second nanowire energy band value for the target size and target crystal phase of the target material is calculated based on the nanowire Hamiltonian form of the modulus space.

[0023] Optionally, the Hamiltonian model includes initial Hamiltonian parameters, and the optimized Hamiltonian parameters of the Hamiltonian model calculated according to the first nanowire energy band value and the second nanowire energy band value include:

[0024] Constructing a functional relationship based on the second nanowire energy band value and the initial Hamiltonian parameter, and constructing a difference relationship based on the difference between the first nanowire energy band value and the second nanowire energy band value;

[0025] The difference relationship is minimized, and combined with the functional relationship, the optimized Hamiltonian parameters of the Hamiltonian model are calculated.

[0026] Optionally, the minimizing the difference relationship and calculating the optimized Hamiltonian parameters of the Hamiltonian model in combination with the functional relationship includes:

[0027] The difference relationship is minimized by using the least squares method or the gradient descent method, and the optimized Hamiltonian parameters of the Hamiltonian model are calculated in combination with the functional relationship.

[0028] Optionally, the method further includes:

[0029] Updating the Hamiltonian model of the target material based on the optimized Hamiltonian parameters;

[0030] The Hamiltonian model of the target material is used to calculate the optimized nanowire energy band value for the target size of the target material.

[0031] The present application provides a Hamiltonian parameter determination device, comprising:

[0032] A first calculation unit is used to calculate a first nanowire energy band value of a target size for a target material using first principles;

[0033] A second calculation unit is configured to construct a Hamiltonian matrix of the target size based on a Hamiltonian model of the target material, and calculate a second nanowire energy band value of the target size for the target material according to the Hamiltonian matrix;

[0034] The third calculation unit is used to calculate the optimized Hamiltonian parameters of the Hamiltonian model according to the first nanowire energy band value and the second nanowire energy band value.

[0035] The present application provides a Hamiltonian parameter determination device, the device comprising: a processor and a memory;

[0036] The memory is used to store instructions;

[0037] The processor is configured to execute the instructions in the memory and perform the method according to any one of claims 1 to 7.

[0038] The present application provides a computer-readable medium, characterized in that it includes instructions, which, when executed on a computer, enable the computer to execute the method described above.

[0039] The present application provides a method for determining Hamiltonian parameters, comprising: calculating a first nanowire energy band value for a target size of a target material using first principles, that is, obtaining an accurate first nanowire energy band value of the target material at the target size using first principles calculation; constructing a Hamiltonian matrix of the target size based on a Hamiltonian model of the target material, and obtaining a second nanowire energy band value for the target size of the target material according to the Hamiltonian matrix, that is, obtaining the second nanowire energy band value by calculating the Hamiltonian matrix of the target material at the target size obtained by constructing; obtaining optimized Hamiltonian parameters of the Hamiltonian model based on the first nanowire energy band value and the second nanowire energy band value, that is, correcting the Hamiltonian model of the target material using the accurate first nanowire energy band value combined with the second nanowire energy band value, thereby obtaining optimized Hamiltonian parameters of the optimized Hamiltonian model, thereby re-determining the Hamiltonian parameters of a small-sized ring-gate nanowire field-effect transistor, so as to use the Hamiltonian parameters to perform device simulation and improve the accuracy of device simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0041] Figure 1 A schematic diagram of a process for determining Hamiltonian parameters provided by an embodiment of the present application is shown;

[0042] Figure 2 A schematic diagram of a Hamiltonian parameter determination process provided in an embodiment of the present application is shown;

[0043] Figure 3 A schematic diagram showing the calculated results of the energy band structure of a silicon material of different sizes provided in an embodiment of the present application is shown;

[0044] Figure 4 A schematic diagram of the energy bands of a silicon nanowire with a size of 4 nm × 4 nm and a crystal phase of

[100] obtained by Hamiltonian model and first principles calculations provided in an embodiment of the present application is shown;

[0045] Figure 5 A schematic diagram of optimizing Hamiltonian parameters provided by an embodiment of the present application is shown;

[0046] Figure 6 A schematic diagram of the energy bands of a silicon nanowire with a size of 4 nm × 4 nm and a crystal phase of

[100] obtained by optimizing Hamiltonian parameters and first-principles calculations provided in an embodiment of the present application is shown;

[0047] Figure 7 A schematic structural diagram of a Hamiltonian parameter determination device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0048] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are described in detail below with reference to the accompanying drawings.

[0049] In the following description, many specific details are set forth to facilitate a full understanding of the present application. However, the present application may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present application. Therefore, the present application is not limited to the specific embodiments disclosed below.

[0050] This application is described in detail with reference to schematic diagrams. When describing the embodiments of this application, for ease of explanation, cross-sectional views of device structures may be partially enlarged and not to scale. Furthermore, these schematic diagrams are merely illustrative and should not limit the scope of protection of this application. Furthermore, in actual production, three-dimensional dimensions, including length, width, and depth, should be included.

[0051] Currently, simulation software is commonly used to simulate gate-all-around nanowire field-effect transistors to study their performance. However, as the size of gate-all-around nanowire field-effect transistors continues to decrease and the materials become nanoscale, a series of significant quantum effects, surface effects, lattice distortions, and defects have made the default material parameters no longer applicable. For example, the Hamiltonian (k·p) parameters are no longer accurate. Especially for small-sized silicon nanowires, fine-tuning and optimizing the material parameters for silicon nanowires of different lengths, widths, and cross-sections has become an indispensable task. At future technology nodes, these calibrated material parameters will have important guiding significance for device simulation of small-sized gate-all-around nanowire field-effect transistors.

[0052] Therefore, there is an urgent need to redefine the material parameters of small-sized ring-gate nanowire field-effect transistors to improve the accuracy of device simulation.

[0053] Based on this, the present application provides a method for determining Hamiltonian parameters, including: using the first principles to calculate the first nanowire energy band value for the target size of the target material, that is, using the first principles to calculate the accurate first nanowire energy band value of the target material at the target size; based on the Hamiltonian model of the target material, constructing the Hamiltonian matrix of the target size, and calculating the second nanowire energy band value for the target size of the target material according to the Hamiltonian matrix, that is, calculating the second nanowire energy band value by constructing the Hamiltonian matrix of the target material at the target size; calculating the optimized Hamiltonian parameters of the Hamiltonian model according to the first nanowire energy band value and the second nanowire energy band value, that is, using the accurate first nanowire energy band value combined with the second nanowire energy band value to correct the Hamiltonian model of the target material, thereby obtaining the optimized Hamiltonian parameters of the optimized Hamiltonian model, so as to redetermine the Hamiltonian parameters of the small-sized ring-gate nanowire field-effect transistor, so as to use the Hamiltonian parameters to perform device simulation and improve the accuracy of device simulation.

[0054] In order to better understand the technical solutions and technical effects of the present application, specific embodiments will be described in detail below with reference to the accompanying drawings.

[0055] refer to Figure 1 FIG. 1 is a flow chart of a method for determining Hamiltonian parameters according to an embodiment of the present application. The method for determining Hamiltonian parameters according to an embodiment of the present application comprises the following steps:

[0056] S101, calculating the energy band value of a first nanowire of a target size for a target material using first principles.

[0057] In the embodiments of the present application, simulation of semiconductor devices typically requires calculating the energy band values ​​of the relevant materials included in the semiconductor devices. For nanowires of target material and target size, the first nanowire energy band values ​​can be calculated using first principles. That is, the first nanowire energy band values ​​of the target material and target size can be accurately calculated using first principles.

[0058] As a possible implementation method, a nanowire lattice structure with a target size and a target crystal phase for a target material can be constructed, that is, a target size and a target crystal phase are selected, and a nanowire lattice structure based on the target size and the target crystal phase for a target material is constructed. The energy bands of the nanowire lattice structure are calculated using the density functional method (DFT) including the first principles to obtain the first nanowire energy band value.

[0059] refer to Figure 2As shown, the energy band structure of bulk materials can be obtained. Bulk materials are large-scale target materials, such as bulk silicon. The desired crystal phase and size of the target material are selected, the lattice structure is constructed, and the dangling bonds of the lattice structure are passivated. Then, the band structure of the nanowire at small scale is calculated using high-precision functional methods.

[0060] As an example, the target material is silicon material, and nanowire lattice structures of different crystal phases and sizes are built using silicon primitives. The nanowire lattice structure is passivated by hydrogen atom adsorption around it, and then the band structure of silicon nanowires at small sizes is calculated based on high-precision functional methods.

[0061] refer to Figure 3 (a), (b), (c), (d) and (e) in the figure respectively illustrate the energy band values ​​of the first nanowire when the target material is silicon and the target sizes are 2nm×2nm, 3nm×3nm, 4nm×4nm, 5nm×5nm and 6nm×6nm, that is, the calculated results of the energy band structure of silicon nanowires at different sizes.

[0062] S102 , constructing a Hamiltonian matrix of a target size based on a Hamiltonian model of a target material, and calculating a second nanowire energy band value of a target size for the target material according to the Hamiltonian matrix.

[0063] In an embodiment of the present application, a Hamiltonian model of a target material can be obtained. Based on the Hamiltonian model of the target material, a Hamiltonian matrix of a target size is constructed, i.e., a Hamiltonian matrix of a small size is constructed using the Hamiltonian model of the target material at a large size. Based on the constructed Hamiltonian matrix of the target size, the second nanowire energy band values ​​for the target material at the target size are calculated, i.e., the second nanowire energy band values ​​are calculated using the constructed Hamiltonian matrix of the target material at the target size.

[0064] As a possible implementation method, based on the Hamiltonian model of the target material, the Hamiltonian matrix of the target size and target crystal phase is constructed, that is, the target size and target crystal phase of the target material are selected, and the Hamiltonian matrix of the nanowire under the target size and target crystal phase is constructed. Then, the Hamiltonian matrix is ​​discretized to obtain the Hamiltonian form of the nanowire, which is convenient for calculation. Then, the second nanowire energy band value for the target size and target crystal phase of the target material is calculated according to the nanowire Hamiltonian form.

[0065] As an example, assuming the target material is silicon, the Hamiltonian model for bulk silicon can be derived based on theoretical knowledge such as group theory, or directly obtained from the literature. The Hamiltonian model for bulk silicon can be shown below.

[0066]

[0067] Among them, L, M and N are Hamiltonian parameters, k x 、k y and k z are the x, y, and z components of K space respectively.

[0068] For the selected target crystal orientation, the Hamiltonian matrix of the silicon nanowire at a small size is constructed, the boundary conditions are selected, and discretization is performed using the following formula.

[0069]

[0070] Where α is x, y, or z, r α is the real space coordinate, k α is the k-space coordinate.

[0071] In practical applications, for the nanowire lattice structure of a general crystal phase, a simple coordinate transformation can be performed on the Hamiltonian model of bulk silicon material. The specific transformation formula is shown below. After the coordinate transformation, the Hamiltonian matrix is ​​discretized.

[0072]

[0073] Among them, R is the transposed matrix, which is used for coordinate transformation, k ′ x 、k ′ y and k ′ z k x 、k y and k z The x, y, and z components of the K space after coordinate transformation.

[0074] In an embodiment of the present application, after the Hamiltonian matrix of the target size and the target crystal phase is discretized, the nanowire Hamiltonian form obtained is the nanowire Hamiltonian form in real space. Since the real space Hamiltonian matrix system is large and it is time-consuming to analytically solve the energy band, dimensionality reduction processing can be performed to reduce the dimensionality of the nanowire Hamiltonian form in real space and convert it into the nanowire Hamiltonian form in modulus space. The second nanowire energy band value for the target size and target crystal phase of the target material is calculated according to the nanowire Hamiltonian form in modulus space. Since the matrix dimension of the Hamiltonian in modulus space is greatly reduced, the band structure of the target material in the target size and target crystal phase can be quickly obtained. Figure 2 shown.

[0075] Specifically, the calculation time for calculating energy bands in real space is much longer than that in modulo space, the data storage size for calculating energy bands in real space is larger than that in modulo space, and the matrix dimension for calculating energy bands in real space is larger than that in modulo space. By comparing the matrix dimension, storage size and calculation time, it can be seen that the performance of calculating energy bands in modulo space is significantly improved compared to that in real space, which can greatly improve the efficiency of material fitting through the Hamiltonian model.

[0076] As an example, the nanowire Hamiltonian form in real space is transformed into k-space and finally into moduli space, and finally the nanowire Hamiltonian form in moduli space is obtained, as shown in the following formula.

[0077]

[0078] Among them, H M is the nanowire Hamiltonian form in moduli space, U + is the transposed transformation matrix, H R is the real-space Hamiltonian form of the nanowire, and U is the transposed matrix.

[0079] The second nanowire energy band values ​​for the target size and target crystal phase of the silicon material are calculated based on the nanowire Hamiltonian form in the moduli space, as shown in the following formula.

[0080]

[0081] Among them, ψ k is the K-space wave function, E k It is the second nanowire energy band value for the target size and target crystal phase of the silicon material.

[0082] S103 , calculating and obtaining optimized Hamiltonian parameters of the Hamiltonian model according to the first nanowire energy band value and the second nanowire energy band value.

[0083] In an embodiment of the present application, after the first nanowire energy band value and the second nanowire energy band value of the small-sized nanowire are calculated using the first principles and the Hamiltonian model respectively, the optimized Hamiltonian parameters of the Hamiltonian model are further calculated based on the first nanowire energy band value and the second nanowire energy band value, that is, the Hamiltonian model of the target material is corrected using the accurate first nanowire energy band value combined with the second nanowire energy band value, thereby obtaining the optimized Hamiltonian parameters of the optimized Hamiltonian model, and re-determining the Hamiltonian parameters of the small-sized ring-gate nanowire field-effect transistor, so as to use the Hamiltonian parameters to perform device simulation and improve the accuracy of device simulation.

[0084] As one possible implementation, a functional relationship is constructed based on the second nanowire energy band values ​​and the initial Hamiltonian parameters, and a difference relationship is constructed based on the difference between the first and second nanowire energy band values. This difference relationship is minimized, and combined with the functional relationship, the optimized Hamiltonian parameters of the Hamiltonian model are calculated. Since the first nanowire energy band values ​​are accurate, by constructing a functional relationship between the second nanowire energy band values ​​and the initial Hamiltonian parameters, and by constructing a difference relationship between the first and second nanowire energy band values, a smaller difference relationship indicates that the second nanowire energy band values ​​are closer to the first nanowire energy band values, the more accurate the second nanowire energy band values ​​are, and the more accurate the optimized Hamiltonian parameters determined using the functional relationship are.

[0085] As an example, for small-sized silicon nanowires, there are many quantum effects, etc., and the default Hamiltonian parameters may fail. Figure 4 As shown, Figure 4 The energy band diagram of a silicon nanowire with a size of 4nm×4nm and a crystal phase of

[100] is shown using the default Hamiltonian parameters and first principles calculations. Figure 4 As can be seen in the figure, there is a discrepancy between the energy band values ​​of the silicon nanowires calculated using the default Hamiltonian parameters and those obtained using first-principles calculations. The energy band values ​​of the silicon nanowires calculated using first-principles calculations are used as the standard reference energy band data, and the energy band values ​​of the silicon nanowires calculated using the default Hamiltonian parameters are treated as the function y = f(x, a). The default Hamiltonian parameters serve as the parameter a of this function, x is the input k-point coordinate, and y is the energy band value of the silicon nanowires calculated using the default Hamiltonian parameters. This means that the functional relationship between the second nanowire energy band value and the initial Hamiltonian parameters is y = f(x, a).

[0086] The difference between the energy band values ​​of the first nanowire and the second nanowire is expressed by the following formula.

[0087]

[0088] in, is the energy band value of the silicon nanowire obtained by first-principles calculation, that is, the energy band value of the first nanowire, is the energy band value of the silicon nanowire calculated by the default Hamiltonian parameters, that is, the energy band value of the second nanowire, i is the number of the i-th energy band, δ is the difference relationship, N b is the number of energy bands, N k is the number of k points, w i,k is the weight of the kth point in the i-th energy band.

[0089] Specifically, the least squares method or gradient descent method can be used to minimize the difference relationship, combined with the functional relationship, to ultimately calculate the optimized Hamiltonian parameters of the Hamiltonian model. In other words, a nonlinear least squares curve fitting function can be used to define the iterative termination condition. Once the iterative termination condition is reached, the optimized Hamiltonian parameters of the silicon nanowire at the small size are immediately output. Weighted processing can also be performed on the energy bands and k-points near the band edges. In addition to the least squares fitting method, gradient descent can also be used for parameter fitting. With the help of the PyTorch machine learning framework, the Adam optimizer is used for model training, and the learning rate is initialized to 0.01.

[0090] In the embodiments of the present application, after calculating the optimized Hamiltonian parameters of the Hamiltonian model, the Hamiltonian model of the target material can be updated based on the optimized Hamiltonian parameters. The Hamiltonian model of the target material can then be used to calculate the optimized nanowire band energy values ​​for the target material and the target size. Thus, after calculating the optimized Hamiltonian parameters, the optimized Hamiltonian parameters can be used to perform numerical calculations of nanowire band energy values ​​for any material at small sizes and in any crystalline phase, greatly improving device simulation efficiency.

[0091] refer to Figure 5 As shown, Figure 5 The optimized Hamiltonian parameters are shown, and the optimized Hamiltonian parameters can be used to replace the initial Hamiltonian parameters. Figure 6 As shown, Figure 6 The energy band diagram of a silicon nanowire with a size of 4nm×4nm and a crystal phase of

[100] is shown by optimizing Hamiltonian parameters and first-principles calculation. Figure 6 It can be seen that the gap between the energy band values ​​of silicon nanowires calculated by optimizing the Hamiltonian parameters and those calculated by first principles is small, and it is more accurate to optimize the Hamiltonian parameters for band edge fitting.

[0092] This application calculates silicon nanowire structures of different sizes, discretizes the Hamiltonian of silicon materials and extracts Hamiltonian parameters in a targeted manner, calibrates and optimizes device simulation parameters, and improves calibration accuracy, providing a foundation for future research on new principles and new materials for advanced nodes. Silicon is used as an example for illustration, and the method of this application can be used to optimize and calibrate Hamiltonian parameters for other materials and different crystal phases, such as elemental materials (Ge, Si, C), compound materials (GaN, InP, SiC), and oxide materials (SiO2, ZnO).

[0093] It can be seen that the present application provides a method for determining Hamiltonian parameters, including: using the first principles to calculate the first nanowire energy band value for the target size of the target material, that is, using the first principles to calculate the accurate first nanowire energy band value of the target material at the target size; based on the Hamiltonian model of the target material, constructing the Hamiltonian matrix of the target size, and calculating the second nanowire energy band value for the target size of the target material according to the Hamiltonian matrix, that is, the second nanowire energy band value is calculated by constructing the Hamiltonian matrix of the target material at the target size; calculating the optimized Hamiltonian parameters of the Hamiltonian model according to the first nanowire energy band value and the second nanowire energy band value, that is, using the accurate first nanowire energy band value combined with the second nanowire energy band value to correct the Hamiltonian model of the target material, thereby obtaining the optimized Hamiltonian parameters of the optimized Hamiltonian model, so as to realize the re-determination of the Hamiltonian parameters of the small-sized ring-gate nanowire field-effect transistor, so as to use the Hamiltonian parameters to perform device simulation and improve the accuracy of device simulation.

[0094] Based on the Hamiltonian parameter determination method provided in the above embodiment, the present application embodiment also provides a Hamiltonian parameter determination device, referring to Figure 7 FIG. 1 is a schematic diagram of a Hamiltonian parameter determination device according to an embodiment of the present application. The Hamiltonian parameter determination device 200 includes:

[0095] A first calculation unit 210 is configured to calculate a first nanowire energy band value of a target size and a target material using first principles;

[0096] A second calculation unit 220 is configured to construct a Hamiltonian matrix of the target size based on a Hamiltonian model of the target material, and calculate a second nanowire energy band value of the target size for the target material according to the Hamiltonian matrix;

[0097] The third calculation unit 230 is configured to calculate and obtain optimized Hamiltonian parameters of the Hamiltonian model according to the first nanowire energy band value and the second nanowire energy band value.

[0098] As a possible implementation, the first computing unit 210 is configured to:

[0099] Constructing a nanowire lattice structure with a target size and a target crystalline phase for a target material;

[0100] The energy band of the nanowire lattice structure is calculated using a density functional method to obtain a first nanowire energy band value.

[0101] As a possible implementation, the second computing unit 220 is configured to:

[0102] Based on the Hamiltonian model of the target material, constructing the Hamiltonian matrix of the target size and target crystal phase;

[0103] Discretizing the Hamiltonian matrix to obtain a nanowire Hamiltonian form;

[0104] The second nanowire energy band value for the target size and target crystal phase of the target material is calculated according to the nanowire Hamiltonian form.

[0105] As a possible implementation, the second computing unit 220 is configured to:

[0106] Discretizing the Hamiltonian matrix to obtain a real-space nanowire Hamiltonian form;

[0107] Converting the nanowire Hamiltonian form in the real space into a nanowire Hamiltonian form in the moduli space by reducing the dimensionality of the nanowire Hamiltonian form in the real space;

[0108] The second nanowire energy band value for the target size and target crystal phase of the target material is calculated based on the nanowire Hamiltonian form of the modulus space.

[0109] As a possible implementation, the Hamiltonian model includes initial Hamiltonian parameters, and a third calculation unit 230 configured to:

[0110] Constructing a functional relationship based on the second nanowire energy band value and the initial Hamiltonian parameter, and constructing a difference relationship based on the difference between the first nanowire energy band value and the second nanowire energy band value;

[0111] The difference relationship is minimized, and combined with the functional relationship, the optimized Hamiltonian parameters of the Hamiltonian model are calculated.

[0112] As a possible implementation, the third computing unit 230 is configured to:

[0113] The difference relationship is minimized by using the least squares method or the gradient descent method, and the optimized Hamiltonian parameters of the Hamiltonian model are calculated in combination with the functional relationship.

[0114] As a possible implementation, the apparatus further includes a fourth computing unit, where the fourth computing unit is configured to:

[0115] Updating the Hamiltonian model of the target material based on the optimized Hamiltonian parameters;

[0116] The Hamiltonian model of the target material is used to calculate the optimized nanowire energy band value for the target size of the target material.

[0117] Based on the method for determining Hamiltonian parameters provided in the above embodiment, an embodiment of the present application further provides a device for determining Hamiltonian parameters, the device comprising:

[0118] The processor and the memory may be one or more processors. In some embodiments of the present application, the processor and the memory may be connected via a bus or other means.

[0119] The memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of the memory may also include NVRAM. The memory stores an operating system and operating instructions, executable modules, or data structures, or subsets or extended sets thereof. The operating instructions may include various operating instructions for implementing various operations. The operating system may include various system programs for implementing various basic services and processing hardware-based tasks.

[0120] The processor controls the operation of the terminal device and may also be referred to as a CPU.

[0121] The methods disclosed in the above embodiments of the present application can be applied to or implemented by a processor. The processor can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits in the processor or by software instructions. The above processor can be a general-purpose processor, a DSP, an ASIC, an FPGA, or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component. The methods, steps, and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of the present application can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above method.

[0122] An embodiment of the present application also provides a computer-readable medium for storing program code, which is used to execute any implementation of the methods of the aforementioned embodiments.

[0123] In the context of the present application, computer-readable medium can be a tangible medium that can contain or store a program for use by an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. Computer-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. More specific examples of computer-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0124] It should be noted that the computer-readable medium mentioned above in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this application, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. This propagated data signal can take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.

[0125] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0126] The various embodiments in this specification are described in a progressive manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the device embodiments are generally similar to the method embodiments, so the description is relatively simple. For relevant parts, refer to the description of the method embodiments.

[0127] The above is only a preferred embodiment of the present application. Although the present application has been disclosed as a preferred embodiment, it is not intended to limit the present application. Any technician familiar with the art can use the above-disclosed methods and technical contents to make many possible changes and modifications to the technical solution of the present application without departing from the scope of the technical solution of the present application, or modify it into an equivalent embodiment with equivalent changes. Therefore, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present application without departing from the content of the technical solution of the present application are still within the scope of protection of the technical solution of the present application.

Claims

1. A method for determining Hamiltonian parameters, characterized in that: include: Calculate the first nanowire energy band value for the target material and target size using first principles; constructing a Hamiltonian matrix of the target size based on a Hamiltonian model of the target material, and calculating a second nanowire energy band value of the target size for the target material according to the Hamiltonian matrix; The optimized Hamiltonian parameters of the Hamiltonian model are calculated according to the first nanowire energy band value and the second nanowire energy band value.

2. The method according to claim 1, characterized in that The calculation of the first nanowire energy band value of the target material and the target size by using the first principles includes: Constructing a nanowire lattice structure with a target size and a target crystalline phase for a target material; The energy band of the nanowire lattice structure is calculated using a density functional method to obtain a first nanowire energy band value.

3. The method according to claim 1, characterized in that The constructing the Hamiltonian matrix of the target size based on the Hamiltonian model of the target material, and calculating the second nanowire energy band value of the target size of the target material according to the Hamiltonian matrix includes: Based on the Hamiltonian model of the target material, constructing the Hamiltonian matrix of the target size and target crystal phase; Discretizing the Hamiltonian matrix to obtain a nanowire Hamiltonian form; The second nanowire energy band value for the target size and target crystal phase of the target material is calculated according to the nanowire Hamiltonian form.

4. The method according to claim 3, characterized in that The performing discretization processing on the Hamiltonian matrix to obtain the nanowire Hamiltonian form includes: Discretizing the Hamiltonian matrix to obtain a real-space nanowire Hamiltonian form; Converting the nanowire Hamiltonian form in the real space into a nanowire Hamiltonian form in the moduli space by reducing the dimensionality of the nanowire Hamiltonian form in the real space; The second nanowire energy band value for the target size and target crystal phase of the target material is calculated according to the nanowire Hamiltonian form, comprising: The second nanowire energy band value for the target size and target crystal phase of the target material is calculated based on the nanowire Hamiltonian form of the modulus space.

5. The method according to claim 1, characterized in that The Hamiltonian model includes initial Hamiltonian parameters, and the optimized Hamiltonian parameters of the Hamiltonian model calculated according to the first nanowire energy band value and the second nanowire energy band value include: Constructing a functional relationship based on the second nanowire energy band value and the initial Hamiltonian parameter, and constructing a difference relationship based on the difference between the first nanowire energy band value and the second nanowire energy band value; The difference relationship is minimized, and combined with the functional relationship, the optimized Hamiltonian parameters of the Hamiltonian model are calculated.

6. The method according to claim 5, characterized in that The step of minimizing the difference relationship and calculating the optimized Hamiltonian parameters of the Hamiltonian model in combination with the functional relationship includes: The difference relationship is minimized by using the least squares method or the gradient descent method, and the optimized Hamiltonian parameters of the Hamiltonian model are calculated in combination with the functional relationship.

7. The method according to claim 1, characterized in that The method further comprises: Updating the Hamiltonian model of the target material based on the optimized Hamiltonian parameters; The Hamiltonian model of the target material is used to calculate the optimized nanowire energy band value for the target size of the target material.

8. A device for determining Hamiltonian parameters, characterized in that: include: A first calculation unit is used to calculate a first nanowire energy band value of a target size for a target material using first principles; A second calculation unit is configured to construct a Hamiltonian matrix of the target size based on a Hamiltonian model of the target material, and calculate a second nanowire energy band value of the target size for the target material according to the Hamiltonian matrix; The third calculation unit is used to calculate the optimized Hamiltonian parameters of the Hamiltonian model according to the first nanowire energy band value and the second nanowire energy band value.

9. A Hamiltonian parameter determination device, characterized in that: The device includes: a processor and a memory; The memory is used to store instructions; The processor is configured to execute the instructions in the memory and perform the method according to any one of claims 1 to 7.

10. A computer-readable medium, characterized in that The method comprises instructions which, when executed on a computer, cause the computer to perform the method according to any one of claims 1 to 7.

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