Boundary condition processing method and device applied to semiconductor device simulation

Abstract

The invention discloses a boundary condition processing method and device applied to semiconductor device simulation. The method comprises the following steps: carrying out iterative calculation on a metal half boundary condition by utilizing acquired ionization donor doping concentration and ionization acceptor doping concentration; in the current iteration process, dynamically adjusting the metal half boundary condition of the current iteration process by using a solving result obtained in the previous iteration process; after the metal half boundary condition of the current iteration process is substituted into the nonlinear simulation equation set, a solving result of the current iteration process is obtained, and iteration is terminated when it is determined that the solving result of the current iteration process converges or the number of iterations reaches the preset number of iterations. According to the method, the convergence and the accuracy of semiconductor device simulation are improved by dynamically adjusting the boundary condition.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of semiconductor simulation, in particular to a boundary condition processing method and device applied to semiconductor device simulation. BACKGROUND

[0002] With the wide application of new semiconductor materials and the significant increase in the complexity of device structures, the simulation verification of some new materials, new processes and new device structures usually uses Technology Computer Aided Design (TCAD) tools to perform semiconductor device simulation. In the process of semiconductor device simulation, the boundary conditions are used to correspond to the actual physical interface characteristics of the device, and to describe the physical behavior at the junction of different materials.

[0003] In the prior art, a fixed Dirichlet boundary condition is usually used, which may cause a large deviation in the setting of the boundary value, and cannot match the carrier concentration when there is a defect state, thereby resulting in poor convergence of semiconductor device simulation and low simulation accuracy. SUMMARY

[0004] Based on the above problems, the present application provides a boundary condition processing method and device applied to semiconductor device simulation, which aims to improve the convergence and accuracy of semiconductor device simulation.

[0005] The embodiments of the present application disclose the following technical solutions:

[0006] In a first aspect, the present application provides a boundary condition processing method applied to semiconductor device simulation, comprising:

[0007] obtaining an ionized donor doping concentration and an ionized acceptor doping concentration;

[0008] iteratively calculating a Schottky boundary condition based on the ionized donor doping concentration and the ionized acceptor doping concentration; the Schottky boundary condition is a processing condition of the semiconductor-metal contact boundary in the process of semiconductor device simulation;

[0009] In the i+1th iteration process, the electron concentration and the hole concentration in the solution obtained in the ith iteration process are used to calculate the built-in potential of the i+1th iteration process; i is a positive integer;

[0010] determining the Schottky boundary condition of the i+1th iteration process based on the built-in potential of the i+1th iteration process;

[0011] substituting the gold half boundary condition of the i+1th iteration process into the nonlinear simulation equation set to obtain a solution result of the i+1th iteration process; the nonlinear simulation equation set comprises a defect state physical model;

[0012] determining whether the solution result of the i+1th iteration process converges, and terminating iteration when it is determined that the solution result of the i+1th iteration process converges or the number of iterations reaches a preset number of iterations.

[0013] Optionally, in the method described above, the built-in potential of the i+1th iteration process is calculated by using the electron concentration and the hole concentration in the solution result of the ith iteration process in the i+1th iteration process, and the calculation comprises:

[0014] the electron concentration and the hole concentration in the solution result of the ith iteration process are used to calculate the donor-like defect charge concentration and the acceptor-like defect charge concentration of the ith iteration process in the i+1th iteration process;

[0015] the built-in potential in the i+1th iteration process is calculated based on the donor-like defect charge concentration and the acceptor-like defect charge concentration of the ith iteration process.

[0016] Optionally, in the method described above, the calculation expression for calculating the built-in potential in the i+1th iteration process based on the donor-like defect charge concentration and the acceptor-like defect charge concentration of the ith iteration process is:

[0017] ;

[0018] in the formula, is the built-in potential in the i+1th iteration process, k is the Boltzmann constant, T is the absolute temperature, q is the electron charge, is the ionized donor doping concentration, is the ionized acceptor doping concentration, is the donor-like defect charge concentration of the ith iteration process, is the acceptor-like defect charge concentration of the ith iteration process, is the intrinsic carrier concentration.

[0019] Optionally, in the method described above, the gold half boundary condition comprises a potential boundary condition and a carrier concentration boundary condition, and the gold half boundary condition of the i+1th iteration process is determined based on the built-in potential of the i+1th iteration process, and the calculation comprises:

[0020] the potential boundary condition is calculated based on the built-in potential of the i+1th iteration process and the obtained contact potential;

[0021] calculate a built-in potential of the i+1th iteration process based on the built-in potential of the i+1th iteration process.

[0022] Optionally, the method as described above, the non-linear simulation equation set comprises a Poisson equation, a carrier continuity equation, a drift-diffusion equation and a defect state physical model.

[0023] Optionally, the method as described above, the judging whether the solution result of the i+1th iteration process converges comprises:

[0024] calculating a residual value by using a Newton iteration method based on the solution result of the i+1th iteration process and the solution result of the ith iteration process, and judging whether the residual value is greater than a preset threshold value;

[0025] if the residual value is less than or equal to the preset threshold value, the solution result of the i+1th iteration process converges;

[0026] or,

[0027] if the residual value is greater than the preset threshold value, the solution result of the i+1th iteration process does not converge.

[0028] In a second aspect, the present application provides a boundary condition processing device applied in semiconductor device simulation, comprising:

[0029] an acquisition module, configured to acquire an ionized donor doping concentration and an ionized acceptor doping concentration;

[0030] a processing module, configured to perform iterative calculation on a metal-semiconductor boundary condition based on the ionized donor doping concentration and the ionized acceptor doping concentration; the metal-semiconductor boundary condition is a processing condition of a metal-semiconductor contact boundary in a semiconductor device simulation process;

[0031] the processing module is configured to calculate a built-in potential of the i+1th iteration process by using an electron concentration and a hole concentration in a solution result of an ith iteration process in the i+1th iteration process; i is a positive integer;

[0032] the processing module is configured to determine a metal-semiconductor boundary condition of the i+1th iteration process based on the built-in potential of the i+1th iteration process;

[0033] the processing module is configured to substitute the metal-semiconductor boundary condition of the i+1th iteration process into a non-linear simulation equation set for solution, to obtain a solution result of the i+1th iteration process; the non-linear simulation equation set comprises a defect state physical model;

[0034] The processing module is configured to determine whether the solution of the i+1th iteration process converges, and to terminate the iteration when it is determined that the solution of the i+1th iteration process converges or the number of iterations reaches a preset number of iterations.

[0035] Optionally, in the i+1th iteration process, the processing module comprises:

[0036] a defect charge concentration calculation unit configured to calculate, in the i+1th iteration process, the donor-like defect charge concentration and the acceptor-like defect charge concentration of the ith iteration process by using the electron concentration and the hole concentration in the solution of the ith iteration process.

[0037] a built-in potential calculation unit configured to calculate the built-in potential in the i+1th iteration process based on the donor-like defect charge concentration and the acceptor-like defect charge concentration of the ith iteration process.

[0038] In a third aspect, the present application provides an electronic device, which comprises a processor and a memory connected to the processor in communication;

[0039] The memory stores computer-executable instructions.

[0040] The processor executes the computer-executable instructions stored in the memory to implement the boundary condition processing method for semiconductor device simulation according to any one of the above embodiments.

[0041] In a fourth aspect, the present application provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are executed by a processor, the computer-executable instructions are used to implement the boundary condition processing method for semiconductor device simulation according to any one of the above embodiments.

[0042] Compared with the prior art, the present application has the following beneficial effects:

[0043] The method of the present application obtains ionized donor doping concentration and ionized acceptor doping concentration; iteratively calculates the Schottky boundary condition based on the ionized donor doping concentration and the ionized acceptor doping concentration; in the i+1th iteration process, the built-in potential of the i+1th iteration process is calculated by using the electron concentration and the hole concentration in the solution result obtained in the ith iteration process, which can reflect the modulation of the current internal carrier concentration on the boundary potential, so that the built-in potential in the current iteration process is closer to the actual device behavior; then the Schottky boundary condition of the i+1th iteration process determined based on the built-in potential of the i+1th iteration process can dynamically adjust the Schottky boundary condition in the current iteration process according to the calculation result of the last iteration, improve the accuracy of the boundary condition, and provide boundary conditions closer to the real solution for the iteration process; and then the Schottky boundary condition of the i+1th iteration process is substituted into the nonlinear simulation equation set containing the defect state physical model for solving, considering the direct influence of the defect state on the semiconductor-metal contact surface, and then the solution result of the i+1th iteration process is closer to the actual device behavior; it is judged whether the solution result of the i+1th iteration process converges, and when it is determined that the solution result of the i+1th iteration process converges or the iteration number reaches the preset iteration number, the iteration is terminated. The method of the present application dynamically adjusts the Schottky boundary condition, changes the boundary condition from static preset to real-time update based on the carrier concentration and the built-in potential, improves the simulation accuracy; at the same time, the built-in potential is dynamically calculated by using the solution result of the last iteration in the iteration process and the boundary condition is updated, which can provide more accurate input for the nonlinear simulation equation set, greatly reduce the iteration number, and improve the convergence of the semiconductor device simulation. BRIEF DESCRIPTION OF DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0045] Figure 1 A flowchart of a boundary condition processing method applied in semiconductor device simulation provided by an embodiment of the present application;

[0046] Figure 2 A structure diagram of a semiconductor device provided by an embodiment of the present application;

[0047] Figure 3 A flowchart of an iteration process in the boundary condition processing method provided by the present application;

[0048] Figure 4A structural schematic diagram of a boundary condition processing device applied in semiconductor device simulation is provided in the embodiments of the present application.

[0049] Figure 5 A structural schematic diagram of an electronic device is provided in the embodiments of the present application. DETAILED DESCRIPTION

[0050] To make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the embodiments and the accompanying drawings. It should be particularly noted that the embodiments described in the embodiments of the present application are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative work fall within the scope of protection of the present application.

[0051] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should be understood as the common meanings of the same by those skilled in the art. The terms "first", "second" and similar terms used in the embodiments of the present application do not represent any order, number or importance, but are only used to distinguish different components. The terms "include" or "contain" and similar terms mean that the components or objects before the terms cover the components or objects listed after the terms and their equivalents, and do not exclude other components or objects. The terms "connect" or "connected" and similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. The terms "up", "down", "left", "right" and the like are only used to represent relative positional relationships, and when the absolute positions of the described objects are changed, the relative positional relationships may also be changed accordingly.

[0052] As described above, in the current semiconductor device simulation, the semiconductor device boundary condition is usually given based on the fixed doping concentration or initial assumption, however, when the fixed boundary value is faced with other defect state physical models which greatly affect the semiconductor device carrier concentration distribution, the simulation convergence is poor or even not convergent, which leads to the reduction of the accuracy of the semiconductor device simulation.

[0053] The inventor has proposed a boundary condition processing method applied in semiconductor device simulation, which uses the solution obtained by solving the nonlinear simulation equation set containing the defect state physical model in the last iteration process to dynamically adjust the boundary condition of the current iteration process, so as to improve the convergence and accuracy of the semiconductor device simulation.

[0054] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0055] See Figure 1 This figure is a flowchart illustrating a boundary condition handling method applied in semiconductor device simulation, as provided in an embodiment of this application. Figure 1 As shown, the method includes:

[0056] S101: Obtain the concentration of ionized donor doping and the concentration of ionized acceptor doping.

[0057] In this embodiment, the ionized donor doping concentration is the concentration of positively charged ions released after the donor impurities in the semiconductor are ionized. This concentration can be achieved using... It indicates that the ionized acceptor doping concentration is the concentration of ions in a semiconductor that capture electrons and become negatively charged after the acceptor impurities are ionized. This can be expressed using... express.

[0058] S102: Iterative calculation of the boundary conditions of gold semi-metal based on the concentrations of ionized donor doping and ionized acceptor doping.

[0059] Among them, the metal-semiconductor boundary condition refers to the processing conditions of the semiconductor-metal contact boundary during semiconductor device simulation. For example, such as Figure 2 As shown in the diagram, the green area represents the metal area; the orange area represents the insulator area; the gray area represents the semiconductor area; and the red line between the green and gray areas represents the contact surface between the semiconductor area and the metal area.

[0060] In this embodiment, for the first iteration, since there is no solution result from the previous iteration, the potential boundary condition in the initial gold semi-metal boundary condition is calculated using the following formula:

[0061] ;

[0062] in, This represents the initial potential boundary condition; This represents the initial built-in potential; This refers to the contact potential. Specifically, the built-in potential refers to the inherent potential difference formed on both sides of the interface between two different materials in equilibrium, due to charge separation caused by carrier diffusion.

[0063] Specifically, the initial built-in potential The following formula is used for calculation:

[0064] ;

[0065] wherein, represents the ionized donor doping concentration; represents the ionized acceptor doping concentration; represents the Boltzmann constant, which is a constant representing the energy of thermal motion; represents the absolute temperature, in units of Kelvin (K); represents the electronic charge, in units of Coulomb (C); is the intrinsic carrier concentration, which is an inherent parameter of the semiconductor material.

[0066] The carrier concentration boundary condition in the initial gold half-boundary condition can be calculated using the following formula, respectively:

[0067] ;

[0068] wherein, represents the initial electron concentration boundary condition; represents the conduction band effective state density; represents the valence band effective state density; represents the electronic charge; represents the initial built-in potential; represents the band gap of the semiconductor material; represents the Boltzmann constant; represents the absolute temperature.

[0069] ;

[0070] wherein, represents the initial hole concentration boundary condition; represents the conduction band effective state density; represents the valence band effective state density; represents the electronic charge; represents the initial built-in potential; represents the band gap of the semiconductor material; represents the Boltzmann constant; represents the absolute temperature.

[0071] S103: In the i+1th iteration process, the built-in potential of the i+1th iteration process is calculated using the electron concentration and the hole concentration in the solution result obtained in the ith iteration process; i is a positive integer.

[0072] In the present embodiment, taking i = 1 as an example, in the second iteration process, the electron concentration in the solution obtained in the first iteration process is utilized to calculate the built-in potential in the second iteration process and the hole concentration . .

[0073] As an implementable manner, in the (i+1)th iteration process, the electron concentration and the hole concentration in the solution obtained in the ith iteration process are utilized to calculate the built-in potential in the (i+1)th iteration process, and the specific implementation steps can include:

[0074] In the (i+1)th iteration process, the electron concentration and the hole concentration in the solution obtained in the ith iteration process are utilized to calculate the donor-like defect charge concentration and the acceptor-like defect charge concentration in the ith iteration process.

[0075] In the present embodiment, in the current iteration process, the electron concentration and the hole concentration in the solution obtained in the last iteration process are utilized to calculate the donor-like defect charge concentration and the acceptor-like defect charge concentration in the last iteration process, which can be calculated by the following steps:

[0076] If the single-energy-level defect electron capture probability corresponding to the acceptor-like energy level is and , the donor-like defect charge concentration of the single-energy-level and the acceptor-like defect charge concentration can be respectively represented by the following formulas:

[0077] ;

[0078] wherein, is the acceptor-like defect energy level density; represents the single-energy-level defect electron capture probability corresponding to the acceptor-like energy level.

[0079] ;

[0080] wherein, is the donor-like defect energy level density; represents the single-energy-level defect hole capture probability corresponding to the donor-like energy level.

[0081] Specifically, if it is assumed that the charge capture cross section of all defect energy levels is constant, the single-energy-level defect state capture probability of the corresponding charge can be represented by the following formula:

[0082] ;

[0083] wherein, represents the single-energy-level defect electron capture probability corresponding to the acceptor-like energy level; Indicates the thermal emission efficiency of electrons; Indicates the thermal emission efficiency of holes; Represents the electron capture cross section; The trapping cross section represents the hole; N represents the electron concentration in the solution of the previous iteration; P represents the hole concentration in the solution of the previous iteration. Intrinsic carrier concentration, This is the intrinsic Fermi level; Represents the acceptor defect energy level; Represents the Boltzmann constant; This indicates absolute temperature.

[0084] ;

[0085] in, This represents the probability of a hole being trapped in a single-level defect corresponding to a donor-like energy level. Indicates the thermal emission efficiency of electrons; Indicates the thermal emission efficiency of holes; Represents the electron capture cross section; The trapping cross section represents the hole; N represents the electron concentration in the solution of the previous iteration; P represents the hole concentration in the solution of the previous iteration. Intrinsic carrier concentration, This is the intrinsic Fermi level; Represents the donor defect energy level; Represents the Boltzmann constant; This indicates absolute temperature.

[0086] When there are multiple acceptor-like and donor-like energy levels within the bandgap, the acceptor-like defect charge concentration from the previous iteration is... and donor defect charge concentration It can be expressed using the following formula:

[0087] ;

[0088] ;

[0089] in, Indicates the number of energy levels of the class acceptor level; Indicates the number of energy levels that represent donor-like energy levels; Indicates the first The concentration of trapped electrons in each class of acceptor energy levels; Indicates the first The concentration of captured holes at each donor level.

[0090] Similarly, the donor-like defect charge concentration in the i-th iteration process and acceptor defect charge concentration The electron concentration can be obtained from the solution obtained through the i-th iteration process. and hole concentration It is calculated using the method described above.

[0091] Based on the donor-like defect charge concentration and acceptor-like defect charge concentration in the i-th iteration process, calculate the built-in potential in the (i+1)-th iteration process.

[0092] In this embodiment, the donor-like defect charge concentration is based on the i-th iteration process. and acceptor-like defect charge concentration Combined with the obtained ionized donor doping concentration With ionized acceptor doping concentration The built-in potential during the (i+1)th iteration can be calculated. .

[0093] In this embodiment, during the (i+1)th iteration, the electron and hole concentrations obtained from the solution obtained in the i-th iteration are used to calculate the donor-like defect charge concentration and acceptor-like defect charge concentration in the i-th iteration. Based on the donor-like defect charge concentration and acceptor-like defect charge concentration in the i-th iteration, the built-in potential in the (i+1)th iteration is calculated. By combining the influence of defect states on the carrier concentration distribution of the semiconductor device, the built-in potential is dynamically calculated using the solution results of the previous iteration, thereby obtaining more accurate boundary conditions to improve the convergence and accuracy of semiconductor device simulation.

[0094] As an feasible approach, based on the donor-like defect charge concentration and acceptor-like defect charge concentration in the i-th iteration, the built-in potential in the (i+1)-th iteration can be calculated using the following expression:

[0095] ;

[0096] In the formula, This represents the built-in potential during the (i+1)th iteration. Represents the Boltzmann constant; Indicates absolute temperature; Indicates the amount of electron charge; Indicates the concentration of ionized donor doping. Indicates the concentration of ionized acceptor doping. This represents the donor-type defect charge concentration in the i-th iteration. This represents the acceptor-like defect charge concentration in the i-th iteration. This indicates the intrinsic carrier concentration.

[0097] S104: determining the Schottky boundary condition of the i+1th iteration process based on the built-in potential of the i+1th iteration process.

[0098] In the embodiment, the built-in potential of the i+1th iteration process is utilized to determine the Schottky boundary condition of the i+1th iteration process. The Schottky boundary condition of the i+1th iteration process can be determined through calculation.

[0099] As an implementable manner, the Schottky boundary condition includes a potential boundary condition and a carrier concentration boundary condition. Based on the built-in potential of the i+1th iteration process, the specific implementation steps of determining the Schottky boundary condition of the i+1th iteration process can include:

[0100] calculating the potential boundary condition based on the built-in potential of the i+1th iteration process and the obtained contact potential.

[0101] In the embodiment, the potential boundary condition of the i+1th iteration process can be expressed by the following formula:

[0102] ;

[0103] wherein, φi+1represents the potential boundary condition of the i+1th iteration process; φi+1represents the built-in potential of the i+1th iteration process; φi+1represents the obtained contact potential.

[0104] calculating the carrier concentration boundary condition based on the built-in potential of the i+1th iteration process.

[0105] In the embodiment, the potential boundary condition is calculated based on the built-in potential of the i+1th iteration process and the obtained contact potential, and the carrier concentration boundary condition is calculated based on the built-in potential of the i+1th iteration process, so as to dynamically adjust the Schottky boundary condition, to improve the accuracy of the semiconductor device simulation, and to make the Schottky boundary condition more consistent with the actual situation and accelerate the convergence.

[0106] In the embodiment, the electron concentration boundary condition and the hole concentration boundary condition of the carrier concentration boundary condition of the i+1th iteration process can be respectively expressed by the following formula:

[0107] ;

[0108] wherein, ni+1represents the electron concentration boundary condition of the i+1th iteration process; the meanings of the remaining letters have been explained in the foregoing formula and will not be explained here.

[0109] ;

[0110] wherein, is the hole concentration boundary condition of the i+1th iteration process; the meanings of the remaining letters have been explained in the foregoing formula and will not be explained here.

[0111] S105: Substitute the Schottky half boundary condition of the i+1th iteration process into the nonlinear simulation equation set for solving to obtain the solving result of the i+1th iteration process. The nonlinear simulation equation set contains a defect state physical model. As an implementable manner, the nonlinear simulation equation set is a control equation of semiconductor device simulation, and the nonlinear simulation equation set can also include, but is not limited to, Poisson equation, carrier continuity equation, drift-diffusion equation.

[0112] In this embodiment, the Poisson equation, the carrier continuity equation, the drift-diffusion equation and the defect model and other physical equations are coupled and assembled to solve the nonlinear simulation equation set. The Schottky half boundary condition of the i+1th iteration process is substituted into the nonlinear simulation equation set for solving to obtain the solving result of the i+1th iteration process. Specifically, the solving result includes electric potential, electron concentration and hole concentration.

[0113] S106: Determine whether the solving result of the i+1th iteration process converges, and terminate the iteration when it is determined that the solving result of the i+1th iteration process converges or the iteration number reaches a preset iteration number.

[0114] In this embodiment, the solving result of the i+1th iteration process is determined based on a preset convergence condition to determine whether the convergence is completed. Specifically, when it is determined that the solving result of the i+1th iteration process satisfies the convergence condition or the iteration number i+1 reaches the preset iteration number, the iteration is terminated, and thus the processing of the boundary condition is completed.

[0115] As an implementable manner, the specific implementation steps of determining whether the solving result of the i+1th iteration process converges can include:

[0116] Based on the solving result of the i+1th iteration process and the solving result of the ith iteration process, a residual value is calculated by using Newton iteration method, and it is determined whether the residual value is greater than a preset threshold.

[0117] In this embodiment, if the solving result of the i+1th iteration process is electric potential , electron concentration and hole concentration , and the solving result of the ith iteration process is electric potential , electron concentration and hole concentration , the potential residual value between the potential and the potential is calculated by using the Newton iteration method , the potential residual value between the potential and the potential is calculated by using the Newton iteration method , the potential residual value between the potential and the potential is calculated by using the Newton iteration method , the potential residual value between the potential and the potential is calculated by using the Newton iteration method , the potential residual value between the potential and the potential is calculated by using the Newton iteration method , the potential residual value between the potential and the potential is calculated by using the Newton iteration method , the potential residual value between the potential and the potential is calculated by using the Newton iteration method , the potential residual value between the potential and the potential is calculated by using the Newton iteration method , the potential residual value between the potential and the potential is calculated by using the Newton iteration method , the potential residual value between the potential and the potential is calculated by using the Newton iteration method , the potential residual value between the potential and the potential is calculated by using the Newton iteration method , the potential residual value between the potential and the potential is calculated by using the Newton iteration method , the potential residual value between the potential and the potential is calculated by using the Newton iteration method

[0118] If the residual value is less than or equal to the preset threshold, the solution result of the i+1 iteration process converges; or if the residual value is greater than the preset threshold, the solution result of the i+1 iteration process does not converge.

[0119] In the embodiment, the potential residual value , the electron concentration residual value , and / or the hole concentration residual value are compared with the preset corresponding threshold, and it is determined that the solution result of the current iteration process converges if the residual value is less than or equal to the corresponding threshold; similarly, if the residual value is greater than the corresponding threshold, it is determined that the solution result of the current iteration process does not converge.

[0120] In the embodiment, based on the solution result of the i+1 iteration process and the solution result of the i iteration process, the residual value is calculated by using the Newton iteration method, and it is determined whether the residual value is greater than the preset threshold; if the residual value is less than or equal to the preset threshold, the solution result of the i+1 iteration process converges; or if the residual value is greater than the preset threshold, the solution result of the i+1 iteration process does not converge, which can accurately evaluate whether the iteration meets the engineering precision requirement, and avoid wasting calculation resources due to over-convergence or causing unreliable simulation results due to under-convergence.

[0121] In the embodiment, by acquiring the ionized donor doping concentration and the ionized acceptor doping concentration, the Schottky boundary condition is iteratively calculated based on the ionized donor doping concentration and the ionized acceptor doping concentration, in the i+1th iteration process, the built-in potential of the i+1th iteration process is calculated by using the electron concentration and the hole concentration in the solving result obtained in the ith iteration process, which can reflect the modulation of the current internal carrier concentration on the boundary potential, so that the built-in potential in the current iteration process is closer to the actual device behavior, and then the Schottky boundary condition of the i+1th iteration process determined based on the built-in potential of the i+1th iteration process can be dynamically adjusted according to the calculation result of the last iteration, so as to improve the accuracy of the boundary condition and provide the boundary condition closer to the real solution for the iteration process, and then the Schottky boundary condition of the i+1th iteration process is substituted into the nonlinear simulation equation set containing the defect state physical model for solving, considering the direct influence of the defect state on the semiconductor-metal contact surface, and then the solving result of the i+1th iteration process is closer to the actual device behavior, the solving result of the i+1th iteration process is judged whether it converges, and when the solving result of the i+1th iteration process converges or the iteration number reaches the preset iteration number, the iteration is terminated. The method of the application dynamically adjusts the Schottky boundary condition, changes the boundary condition from static presetting to real-time updating based on the carrier concentration and the built-in potential, improves the simulation accuracy, and at the same time, the built-in potential is dynamically calculated by using the solving result of the last iteration in the iteration process and the boundary condition is updated, which can provide the nonlinear simulation equation set with input closer to the real solution, greatly reduces the iteration number, and improves the convergence of the semiconductor device simulation.

[0122] As a specific implementation process, as shown in the figure, Figure 3 the flow of the iteration process in the boundary condition processing method in the embodiment includes the following steps:

[0123] S1001: set the current iteration number i=1, the preset iteration number Y, the initial potential boundary condition , the initial electron concentration boundary condition , and the initial hole concentration boundary condition .

[0124] S1002: judge whether the current iteration number i is equal to 1, if i=1, execute S1005-S1006; if i≠1, execute S1003-S1004.

[0125] S1003: according to the solving result obtained in the S1005 step in the last iteration process, the Schottky boundary condition of the current iteration process is obtained.

[0126] S1004: Determine whether the current iteration number i is less than or equal to the preset iteration number Y; if i ≤ Y, then execute S1005-S1006; if i > Y, then end.

[0127] S1005: Solve the nonlinear simulation equations using the semi-gold boundary conditions of the current iteration process to obtain the solution result corresponding to the current iteration number i.

[0128] S1006: Determine whether the solution has converged based on the solution result of the current iteration process; if the solution result has converged, then end; if it has not converged, then execute S1007.

[0129] S1007: Increment i by 1 and return to S1002.

[0130] See Figure 4 This figure is a schematic diagram of a boundary condition processing device applied in semiconductor device simulation, provided in an embodiment of this application. Figure 3 As shown, the device 20 includes an acquisition module 21 and a processing module 22.

[0131] The acquisition module 21 is used to acquire the ionized donor doping concentration and the ionized acceptor doping concentration; the processing module 22 is used to perform iterative calculations on the gold-semiconductor boundary conditions based on the ionized donor doping concentration and the ionized acceptor doping concentration; the gold-semiconductor boundary conditions are the processing conditions of the semiconductor-metal contact boundary during semiconductor device simulation; in the (i+1)th iteration, the built-in potential of the (i+1)th iteration is calculated using the electron concentration and hole concentration obtained from the solution result of the (i)th iteration; i is a positive integer; the processing module is used to determine the gold-semiconductor boundary conditions of the (i+1)th iteration based on the built-in potential of the (i+1)th iteration; the gold-semiconductor boundary conditions of the (i+1)th iteration are substituted into the nonlinear simulation equations for solution to obtain the solution result of the (i+1)th iteration; the nonlinear simulation equations include a defect-state physical model; it is determined whether the solution result of the (i+1)th iteration converges, and the iteration is terminated when the solution result of the (i+1)th iteration converges or the number of iterations reaches the preset number of iterations.

[0132] The boundary condition processing device for semiconductor device simulation provided in this application embodiment can execute the technical solution shown in the above method embodiment. Its implementation principle and beneficial effects are similar, and will not be repeated here.

[0133] Furthermore, based on the above embodiments, when the processing module 22 calculates the built-in potential of the (i+1)th iteration process using the electron concentration and hole concentration in the solution obtained in the i-th iteration process, the processing module 22 specifically includes a defect charge concentration calculation unit and a built-in potential calculation unit.

[0134] The defect charge concentration calculation unit is used to calculate the donor-like defect charge concentration and acceptor-like defect charge concentration in the solution results obtained in the i+1th iteration process using the electron concentration and hole concentration obtained in the i-th iteration process; the built-in potential calculation unit is used to calculate the built-in potential in the i+1th iteration process based on the donor-like defect charge concentration and acceptor-like defect charge concentration in the i-th iteration process.

[0135] The boundary condition processing device for semiconductor device simulation provided in this application embodiment can execute the technical solution shown in the above method embodiment. Its implementation principle and beneficial effects are similar, and will not be repeated here.

[0136] Furthermore, based on the above embodiments, the built-in potential calculation unit calculates the built-in potential in the (i+1)th iteration process based on the donor-like defect charge concentration and acceptor-like defect charge concentration in the i-th iteration process, using the following expression:

[0137] ;

[0138] In the formula, Let be the built-in potential during the (i+1)th iteration, k be the Boltzmann constant, T be the absolute temperature, and q be the electron charge. The concentration of ionized donor doping. The concentration of ionized acceptor doping. Let be the donor-like defect charge concentration in the i-th iteration. Let be the acceptor-like defect charge concentration in the i-th iteration process. This represents the intrinsic carrier concentration.

[0139] The boundary condition processing device for semiconductor device simulation provided in this application embodiment can execute the technical solution shown in the above method embodiment. Its implementation principle and beneficial effects are similar, and will not be repeated here.

[0140] Furthermore, based on the above embodiments, when the gold-half boundary conditions include potential boundary conditions and carrier concentration boundary conditions, and the gold-half boundary conditions of the (i+1)th iteration process are determined based on the built-in potential of the (i+1)th iteration process, the processing module 22 is specifically used to calculate the potential boundary conditions based on the built-in potential of the (i+1)th iteration process and the acquired contact potential; and to calculate the carrier concentration boundary conditions based on the built-in potential of the (i+1)th iteration process.

[0141] The boundary condition processing device for semiconductor device simulation provided in this application embodiment can execute the technical solution shown in the above method embodiment. Its implementation principle and beneficial effects are similar, and will not be repeated here.

[0142] Further, on the basis of the above-mentioned embodiments, the nonlinear simulation equation set in the processing module 22 includes Poisson equation, carrier continuity equation, drift-diffusion equation and defect state physical model.

[0143] The boundary condition processing device for semiconductor device simulation provided in the embodiments of the present application can execute the technical solutions shown in the method embodiments, and has similar implementation principles and beneficial effects, which will not be repeated here.

[0144] Further, on the basis of the above-mentioned embodiments, when judging whether the solution result of the i+1th iteration process converges, the processing module 22 is specifically configured to: based on the solution result of the i+1th iteration process and the solution result of the ith iteration process, calculate a residual value by using Newton iteration method and judge whether the residual value is greater than a preset threshold value; if the residual value is less than or equal to the preset threshold value, the solution result of the i+1th iteration process converges; or if the residual value is greater than the preset threshold value, the solution result of the i+1th iteration process does not converge.

[0145] The boundary condition processing device for semiconductor device simulation provided in the embodiments of the present application can execute the technical solutions shown in the method embodiments, and has similar implementation principles and beneficial effects, which will not be repeated here.

[0146] Referring to Figure 5 , the figure is a structural schematic diagram of an electronic device provided in the embodiments of the present application, which includes:

[0147] The memory 11 is configured to store a computer program.

[0148] The processor 12 is configured to execute the computer program to implement the steps of the boundary condition processing method for semiconductor device simulation in any method embodiment.

[0149] In the embodiments, the device can be a vehicle-mounted computer, a PC (Personal Computer), and can also be a terminal device such as a smart phone, a tablet computer, a palm computer, a portable computer, etc.

[0150] The device can include a memory 11, a processor 12 and a bus 13.

[0151] The memory 11 includes at least one type of readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 can be an internal storage unit of the device in some embodiments, such as a hard disk of the device. The memory 11 can also be an external storage device of the device in other embodiments, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Further, the memory 11 can include both an internal storage unit and an external storage device. The memory 11 can be used to store application software installed in the device and various data, such as program codes for implementing the boundary condition processing method applied to semiconductor device simulation, and to temporarily store data that has been output or will be output. The processor 12 can be a central processing unit (CPU) in some embodiments.

[0152] The processor 12 can be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip, which is used to run program codes stored in the memory 11 or process data, such as program codes for implementing the boundary condition processing method applied to semiconductor device simulation, in some embodiments.

[0153] The bus 13 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For convenience of representation, Figure 5 Only one thick line is used to represent the bus in the figure, but it does not mean that there is only one bus or only one type of bus.

[0154] Further, the device can also include a network interface 14, which can optionally include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), and is usually used to establish a communication connection between the device and other electronic devices.

[0155] Optionally, the device can further comprise a user interface 15, which can include a display, an input unit such as a keyboard, and optionally the user interface 15 can further include a standard wired interface, a wireless interface. Optionally, in some embodiments, the display can be an LED display, a liquid crystal display, a touch liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, etc. Wherein the display can also be appropriately called a display screen or a display unit, for displaying information processed in the device and for displaying a visualized user interface.

[0156] Figure 5 Only the device with components 11-15 is shown, and those skilled in the art can understand that, Figure 5 The structure shown does not constitute a limitation on the device, and can include fewer or more components than shown, or combine certain components, or different component arrangements.

[0157] Based on the same inventive concept, corresponding to the method of any of the above embodiments, the embodiments of the present application also provide a computer readable storage medium, which stores computer instructions for causing the computer to execute the boundary condition processing method applied in semiconductor device simulation as described in any of the above embodiments.

[0158] The computer readable medium of the embodiments of the present application includes permanent and non-permanent, removable and non-removable media, which can be implemented by any method or technology to store information. The information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device, or any other non-transmission medium that can be used to store information accessible by a computing device.

[0159] The computer instructions stored in the storage medium of the above embodiments are used to cause the computer to execute the boundary condition processing method applied in semiconductor device simulation as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which are not described here.

[0160] It should be noted that each of the embodiments of the present specification is described in a progressive manner, and the same or similar parts between the embodiments can be mutually referred to, and each embodiment focuses on the difference from other embodiments. In particular, for the method, device, electronic device and medium, since they are basically similar to the method embodiment, they are described more simply, and the relevant parts can refer to the part of the description of the method embodiment. The above-described method, device, electronic device and medium are only illustrative, and the units described as separate components can be or can not be physically separated, and the components prompted as units can be or can not be physical units, that is, they can be located in one place, or can be distributed on multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiments of the present application according to actual needs. Those skilled in the art can understand and implement it without creative labor.

[0161] The above describes only one specific embodiment of the present application, but the protection scope of the present application is not limited to this. Any skilled person in the art can easily think of changes or replacements within the technical range disclosed in the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A boundary condition handling method applied in semiconductor device simulation, characterized in that, include: Obtain the concentrations of ionized donor doping and ionized acceptor doping; Based on the ionized donor doping concentration and the ionized acceptor doping concentration, the gold-semiconductor boundary conditions are iteratively calculated; the gold-semiconductor boundary conditions are the processing conditions for the semiconductor-metal contact boundary during semiconductor device simulation. In the (i+1)th iteration, the built-in potential of the (i+1)th iteration is calculated using the electron concentration and hole concentration obtained from the solution obtained in the ith iteration; i is a positive integer. Based on the built-in potential of the (i+1)th iteration process, the gold semi-boundary conditions of the (i+1)th iteration process are determined. The boundary conditions of the gold semi-metallic boundary in the (i+1)th iteration process are substituted into the nonlinear simulation equations and solved to obtain the solution result of the (i+1)th iteration process; the nonlinear simulation equations include a defect-state physical model. Determine whether the solution result of the (i+1)th iteration process has converged, and terminate the iteration when it is determined that the solution result of the (i+1)th iteration process has converged or the number of iterations has reached the preset number of iterations.

2. The method according to claim 1, characterized in that, In the (i+1)th iteration, the built-in potential of the (i+1)th iteration is calculated using the electron concentration and hole concentration obtained from the solution obtained in the ith iteration, including: In the (i+1)th iteration, the electron concentration and hole concentration in the solution obtained in the i-th iteration are used to calculate the donor-like defect charge concentration and acceptor-like defect charge concentration in the i-th iteration. Based on the donor-like defect charge concentration and acceptor-like defect charge concentration in the i-th iteration process, the built-in potential in the (i+1)-th iteration process is calculated.

3. The method according to claim 2, characterized in that, The expression for calculating the built-in potential in the (i+1)th iteration process based on the donor-like defect charge concentration and acceptor-like defect charge concentration in the i-th iteration process is as follows: ； In the formula, Let be the built-in potential during the (i+1)th iteration, k be the Boltzmann constant, T be the absolute temperature, and q be the electron charge. The concentration of ionized donor doping. The concentration of ionized acceptor doping. Let be the donor-like defect charge concentration in the i-th iteration. Let be the acceptor-like defect charge concentration in the i-th iteration process. This represents the intrinsic carrier concentration.

4. The method according to any one of claims 1-3, characterized in that, The gold-half boundary conditions include potential boundary conditions and carrier concentration boundary conditions. The determination of the gold-half boundary conditions for the (i+1)th iteration process based on the built-in potential of the i+1th iteration process includes: Based on the built-in potential and the acquired contact potential in the (i+1)th iteration process, the potential boundary conditions are calculated. Based on the built-in potential of the (i+1)th iteration process, the carrier concentration boundary conditions are calculated.

5. The method according to claim 1, characterized in that, The nonlinear simulation equation set includes the Poisson equation, the carrier continuity equation, the drift-diffusion equation, and the defect state physical model.

6. The method according to claim 1, characterized in that, The determination of whether the solution result of the (i+1)th iteration process converges includes: Based on the solution results of the (i+1)th iteration process and the solution results of the i-th iteration process, the residual value is calculated using the Newton iteration method, and it is determined whether the residual value is greater than a preset threshold. If the residual value is less than or equal to a preset threshold, the solution result of the (i+1)th iteration process converges. or, If the residual value is greater than a preset threshold, the solution result of the (i+1)th iteration process will not converge.

7. A boundary condition processing device applied in semiconductor device simulation, characterized in that, include: The acquisition module is used to acquire the concentrations of ionized donor doping and ionized acceptor doping. The processing module is used to iteratively calculate the gold-semiconductor boundary conditions based on the ionized donor doping concentration and the ionized acceptor doping concentration; the gold-semiconductor boundary conditions are the processing conditions of the semiconductor-metal contact boundary during semiconductor device simulation. The processing module is used to calculate the built-in potential of the (i+1)th iteration process by using the electron concentration and hole concentration in the solution result obtained in the i-th iteration process; i is a positive integer. The processing module is used to determine the gold semi-circular boundary conditions of the (i+1)th iteration process based on the built-in potential of the (i+1)th iteration process. The processing module is used to substitute the gold semi-boundary conditions of the (i+1)th iteration process into the nonlinear simulation equation set for solution, and obtain the solution result of the (i+1)th iteration process; the nonlinear simulation equation set includes a defect state physical model. The processing module is used to determine whether the solution result of the (i+1)th iteration process has converged, and to terminate the iteration when it is determined that the solution result of the (i+1)th iteration process has converged or the number of iterations has reached the preset number of iterations.

8. The apparatus according to claim 7, characterized in that, In the (i+1)th iteration, when calculating the built-in potential of the (i+1)th iteration using the electron and hole concentrations obtained from the solution obtained in the (i)th iteration, the processing module includes: The defect charge concentration calculation unit is used to calculate the donor-like defect charge concentration and acceptor-like defect charge concentration in the i+1th iteration process by using the electron concentration and hole concentration in the solution result obtained in the i-th iteration process. The built-in potential calculation unit is used to calculate the built-in potential in the (i+1)th iteration process based on the donor-like defect charge concentration and acceptor-like defect charge concentration in the i-th iteration process.

9. An electronic device, characterized in that, The device includes: a processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1 to 6.

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