Modeling method of metal oxide semiconductor

Abstract

The invention provides a modeling method of a metal oxide semiconductor, which comprises the following steps of: establishing an initial sub-circuit simulation model as follows: # imgabs0 #, in which YMF is a multi-interdigital effect correction parameter, NF is an interdigital index of a grid electrode of an MOS (Metal Oxide Semiconductor) device, Xnf0, A, Xnf1, B, Xnf2, C, Xnf3, D, Xnf4, E, Xnf5 and F are fitting parameters, W is a channel width, L is a channel length, and Xnf6 is a fitting parameter; acquiring a plurality of actually measured electrical characteristic parameters of the metal oxide semiconductor under different cross indexes, different channel widths and different channel lengths; fitting parameters are adjusted, so that when errors of multi-interdigital effect correction parameters obtained through simulation under different interdigitals, different channel widths and different channel lengths are all within set values, values of the corresponding fitting parameters at the moment are determined; and establishing the following multi-interdigital effect model: Y = K + YMF.

Description

Technical Field

[0001] The present invention relates to the field of semiconductor technology, and in particular to a method for modeling a metal oxide semiconductor. Background Art

[0002] SPICE (Simulation Program with Integrated Circuit Emphasis) is a language simulator software for circuit description and simulation, used to detect the integrity of circuit connections and functions, and to predict the behavior of circuits. SPICE is mainly used for the simulation of analog circuits and mixed-signal circuits. For SPICE to work well, device-level model parameters must be provided. Commonly used SPICE models in the industry include the BSIM series, PSP, or empirical models, etc. SPICE modeling engineers rely on device theory and experience to extract model parameters for use in SPICE simulation programs. Metal oxide semiconductor field effect transistors can be modeled and simulated using SPICE to obtain electrical simulation data, such as electrical characteristic parameters like threshold voltage, source-drain saturation current, source-drain linear current, etc.

[0003] The existing method for modeling a metal oxide semiconductor is mainly a SPICE modeling method for LDMOS devices with different NFs. Specifically, three parameters, namely the threshold voltage vth0, the low-field mobility u0, and the gate voltage-dependent parameter ub, are selected from the original BSIM model of LDMOS and formulated as in such a form, where P 0 is the BSIM model parameter value when the finger index NF = 1, P 1 is NF, P 2 is the exponential parameter of NF, and NF is the finger index of the MOS device gate, Number of finger, an inherent value of the MOS device. In this way, the formulated vth0, u0, and ub can incorporate the effect of changing with NF on the device characteristics, and calibrate the characteristics of LDMOS devices with different finger indices NF that cannot be accurately fitted by a single BSIM model.

[0004] However, the modeling methods of the prior art have the following two disadvantages: 1. The BSIM model parameter formula is a power function and is monotonic within the range of the fork index NF > 1, and it cannot simulate the measured data with increasing and decreasing trends of the NF effect of MOS devices. 2. The prior art is based on the NF effect of LDMOS. The characteristic of LDMOS is that the channel length L is fixed and the channel width W is very large. The effect of the channel width of LDMOS is very small, and since the channel length L is fixed, there is no short-channel effect. Therefore, the BSIM model parameters that have an overall impact on the electrical properties of devices of different sizes are selected for formulaization. If this method is migrated to the NF effect modeling of general low-voltage MOS devices, the characteristics of devices of different sizes cannot be simulated very precisely. For example, from the measured data, the multi-finger (NF) effect trend of MOS devices with short channel lengths is inconsistent with that of devices with a channel length of 10 microns and a channel width of 10 microns. Therefore, the existing model technology cannot accurately simulate the characteristics of MOS devices with different channel widths W and channel lengths L changing with different fork indices NF. Summary of the Invention

[0005] The object of the present invention is to provide a modeling method for metal oxide semiconductors, which can simulate the measured data with increasing and decreasing trends as the fork index NF increases. And it can accurately simulate the characteristics of MOS devices with different channel widths W and channel lengths L changing with different fork indices NF.

[0006] To achieve the above object, the present invention provides a modeling method for metal oxide semiconductors, including:

[0007] Establish an initial sub-circuit simulation model as follows:

[0008]

[0009] Wherein, Y_MF is the multi-finger effect correction parameter, NF is the fork index of the MOS device gate, X nf0 , A, X nf1 , B, X nf2 , C, X nf3 , D, X nf4 , E, X nf5 and F are all fitting parameters, W is the channel width, L is the channel length, X nf6 is a fitting parameter;

[0010] Obtain multiple measured electrical characteristic parameters of the metal oxide semiconductor under different fingers, different channel widths and different channel lengths;

[0011] Adjust the fitting parameters so that when the errors between the multi-finger effect correction parameters obtained by simulation under different finger structures, different channel widths, and different channel lengths and the measured electrical characteristic parameters are all within the set value, determine the value of the corresponding fitting parameters at this time;

[0012] Establish the following multi-finger effect model:

[0013] Y = K + Y_MF, where K is a constant, Y is the correction parameter, and Y_MF is the multi-finger effect correction parameter.

[0014] Optionally, in the above-mentioned metal oxide semiconductor modeling method, the correction parameters include: the long-channel threshold voltage without body bias effect, the low-field mobility, the first-order coefficient of mobility degradation caused by the longitudinal electric field, the second-order coefficient of mobility degradation caused by the longitudinal electric field, the channel length dependence coefficient of the bulk charge effect, the gate voltage dependence coefficient of the bulk charge effect, and / or the carrier saturation velocity.

[0015] Optionally, in the above-mentioned metal oxide semiconductor modeling method, the fitting parameter X nf0 has a value range of -1e 12 to 1e 12 , the fitting parameter A has a value range of -1e 12 to 1e 12 The fitting parameter X nf1 has a value range of -1e 6 to 1e 6 , the fitting parameter B has a value range of -1e 6 to 1e 6 The fitting parameter X nf2 has a value range of -1e6 to 1e6, the fitting parameter C has a value range of -1e 6 to 1e 6 The fitting parameter X nf3 has a value range of -1e -6 to -1e -10 or 1e -10 to 1e -6 , the fitting parameter D has a value range of -1e 6 to 1e 6 The fitting parameter X nf4 has a value range of -1e -6 to -1e -10 or 1e -10 to 1e -6 , the fitting parameter E has a value range of -1e 6 to 1e 6 The fitting parameter X nf5 has a value range of -1e -12 to -1e -16 or 1e-16 ~1e -12 The value range of the fitting parameter F is -1e 6 ~1e 6 .

[0016] Optionally, in the modeling method of the metal oxide semiconductor, the value of k includes 0.21.

[0017] Optionally, in the modeling method of the metal oxide semiconductor, the set value includes 0.9% to 1.1%.

[0018] The present invention also provides a modeling method for a metal oxide semiconductor, including:

[0019] Establish an initial sub-circuit simulation model as follows:

[0020]

[0021] where Y_MF is the multi-finger effect correction parameter, NF is the number of fingers of the MOS device gate, X nf0 , A, X nf1 , B, X nf2 , C, X nf3 , D, X nf4 , E, X nf5 and F are all fitting parameters, W is the channel width, L is the channel length, X nf6 is a fitting parameter;

[0022] Obtain multiple measured electrical characteristic parameters of the metal oxide semiconductor under different numbers of fingers, different channel widths, and different channel lengths;

[0023] Adjust the fitting parameter so that when the error between the multi-finger effect correction parameter obtained by simulation and the measured electrical characteristic parameter under different fingers, different channel widths, and different channel lengths is within the set value, determine the value of the corresponding fitting parameter at this time;

[0024] Establish the following multi-finger effect model:

[0025] Y = K + Y_MF, where K is a constant, Y is the correction parameter, and Y_MF is the multi-finger effect correction parameter.

[0026] Optionally, in the modeling method of the metal oxide semiconductor, the correction parameter includes: the long-channel threshold voltage without body bias effect, the low-field mobility, the first-order coefficient of mobility degradation caused by the longitudinal electric field, the second-order coefficient of mobility degradation caused by the longitudinal electric field, the channel length dependence coefficient of the body charge effect, the gate voltage dependence coefficient of the body charge effect, and / or the carrier saturation velocity.

[0027] Optionally, in the method for modeling a metal oxide semiconductor, the fitting parameter X nf0 has a value range of -1e 12 to 1e 12 , the fitting parameter A has a value range of -1e 12 to 1e 12 , the fitting parameter X nf1 has a value range of -1e 6 to 1e 6 , the fitting parameter B has a value range of -1e 6 to 1e 6 , the fitting parameter X nf2 has a value range of -1e6 to 1e6, the fitting parameter C has a value range of -1e 6 to 1e 6 , the fitting parameter X nf3 has a value range of -1e -6 to -1e -10 or 1e -10 to 1e -6 , the fitting parameter D has a value range of -1e 6 to 1e 6 , the fitting parameter X nf4 has a value range of -1e -6 to -1e -10 or 1e -10 to 1e -6 , the fitting parameter E has a value range of -1e 6 to 1e 6 , the fitting parameter X nf5 has a value range of -1e -12 to -1e -16 or 1e -16 to 1e -12 , the fitting parameter F has a value range of -1e 6 to 1e 6 .

[0028] Optionally, in the method for modeling a metal oxide semiconductor, the value of k includes 0.21.

[0029] Optionally, in the method for modeling a metal oxide semiconductor, the set value includes 0.9% to 1.1%.

[0030] In the method for modeling a metal oxide semiconductor provided by the present invention, the model of the present invention can simulate the measured data with an increasing and decreasing NF effect trend. Moreover, it accurately simulates the characteristics of MOS devices with different channel widths W and channel lengths L changing with different finger numbers. Description of the Drawings

[0031] Figure 1 It is a flowchart of the modeling method of the metal oxide semiconductor according to the first embodiment of the present invention;

[0032] Figure 2 It is a flowchart of the modeling method of the metal oxide semiconductor according to the second embodiment of the present invention;

[0033] Figures 3 to 5 It is a model simulation comparison diagram of the metal oxide semiconductor of the present invention and the prior art. Specific Embodiments

[0034] The specific embodiments of the present invention will be described in more detail below with reference to the schematic diagrams. According to the following description, the advantages and features of the present invention will be clearer. It should be noted that the drawings are all in very simplified forms and use non-precise scales, only for conveniently and clearly assisting in explaining the purposes of the embodiments of the present invention.

[0035] In the following text, terms such as "first", "second", etc. are used to distinguish between similar elements and are not necessarily used to describe a specific order or time sequence. It should be understood that, under appropriate circumstances, these terms used in this way can be replaced. Similarly, if the methods described herein include a series of steps, and the order of these steps presented herein is not necessarily the only order in which these steps can be executed, and some of the described steps can be omitted and / or some other steps not described herein can be added to the method.

[0036] Moreover, it should be understood that when a layer (or film), region, pattern, or structure is referred to as being "on" a substrate, layer (or film), region, and / or pattern, it can be directly on another layer or substrate, and / or there can also be an intervening layer. Additionally, it should be understood that when a layer is referred to as being "under" another layer, it can be directly under another layer, and / or there can also be one or more intervening layers. Additionally, the references to "on" and "under" each layer can be based on the drawings.

[0037] First Embodiment

[0038] Please refer to Figure 1 , the first embodiment of the present invention provides a modeling method for a metal oxide semiconductor, including:

[0039] S11: Establish an initial sub-circuit simulation model as follows:

[0040]

[0041] Among them, Y_MF is the correction parameter for the multi-finger (MF) effect, X nf0 , NF A , X nf1 , NF B , X nf2 , NFB 、X nf3 、NF C 、X nf4 、NF D 、X nf5 and NF E are all fitting parameters, W is the channel width, L is the channel length, and X nf6 is a constant;

[0042] S12: Obtain multiple measured electrical characteristic parameters of the metal oxide semiconductor under different finger numbers, different channel widths, and different channel lengths;

[0043] S13: Adjust the fitting parameters. When the errors between the multi-finger effect correction parameters obtained by simulation under different finger numbers, different channel widths, and different channel lengths and the measured electrical characteristic parameters are all within the set value, determine the values of the corresponding fitting parameters at this time;

[0044] S14: Establish the following multi-finger (MF) effect model:

[0045] Y = K + Y_MF, where K is a constant. K is the value obtained when performing model fitting when the number of fingers is 1, that is, NF = 1. In the embodiments of the present invention, the value can be 0.21. Y is the correction parameter, Y_MF is the multi-finger (MF) effect correction parameter. Y is a certain parameter in the selected BSIM model. Select Y and add MF to it to obtain the effect correction parameter Y_MF. The BSIM model (Berkeley Short-channel IGFET Model) is a mathematical model used to describe the behavior of field-effect transistors (FETs) and is widely used in integrated circuit design and analysis. Y is the parameter to be corrected among them. Adding the multi-finger (MF) effect correction parameter to the parameter correction can simulate the characteristics of MOS devices with different channel widths W and channel lengths L changing with different finger numbers NF.

[0046] Preferably, the correction parameters include: the long-channel threshold voltage vth0 without body bias effect, the low-field mobility u0, the first-order coefficient ua of mobility degradation caused by the longitudinal electric field, the second-order coefficient ub of mobility degradation caused by the longitudinal electric field, the channel length dependence coefficient a0 of the body charge effect, the gate voltage dependence coefficient ags of the body charge effect, and / or the carrier saturation velocity vsat. One or several of them can be selected for correction. The long-channel threshold voltage vth0 without body bias effect also includes the threshold voltage with a smaller channel length and the threshold voltage with a smaller channel width. The low-field mobility u0 includes the mobility with a smaller channel length. The carrier saturation velocity vsat includes the carrier saturation velocity with a smaller channel length and the carrier saturation velocity with both a smaller channel length and a smaller channel width. Taking the long-channel threshold voltage vth0 without body bias effect as an example, the initial sub-circuit simulation model is:

[0047]

[0048] Among them, dvth0_MF is the correction parameter for the multi-finger effect of the long-channel threshold voltage vth0 without body bias effect, NF is the number of fingers of the MOS device gate, dvth nf0 , A, dvth nf1 , B, dvth nf2 , C, dvth nf3 , D, dvth nf4 , E, dvth nf5 and F are all fitting parameters, W is the channel width, L is the channel length, dvth nf6 is a fitting parameter.

[0049] In the formula, the W*L term (the first term on the right side of the equal sign of the formula) takes effect when both the channel width W and the channel length L are very large. Therefore, when both the channel width W and the channel length L are very large, adjust the fitting parameters dvth nf0 and A of the W*L term. The W term (the second term on the right side of the equal sign of the formula) or the L term (the third term on the right side of the equal sign of the formula) takes effect when the channel width W is very large or the channel length L is very large. Therefore, when the channel width W is very large or the channel length L is very large, adjust the fitting parameter dvth nf1 of the W term and B or the fitting parameter dvth nf2 of the L term and C. The term takes effect when both the channel width W and the channel length L are very small. Therefore, when both the channel width W and the channel length L are very small, adjust the fitting parameter dvth of the term and F. nf5 The term or or takes effect when the channel width W is very small or the channel length L is very small. Therefore, when the channel width W is very small or the channel length L is very small, adjust Fitting parameter dvth of the item nf3 and D or Fitting parameter dvth of the item nf4 and E. dvth nf6 can be debugged at any time. Therefore, by debugging the above simulation parameters, dvth0_MF and the measured value can be within the set value, and the values of multiple fitting parameters at this time can be determined. Substituting them into the formula of dvth0_MF, the model of dvth0_MF can be obtained. Similarly, when the simulation parameters are the low-field mobility u0, the first-order coefficient ua of the mobility degradation caused by the longitudinal electric field, the second-order coefficient ub of the mobility degradation caused by the longitudinal electric field, the channel length dependence coefficient a0 of the bulk charge effect, the gate voltage dependence coefficient ags of the bulk charge effect, and / or the carrier saturation velocity vsat, directly substitute them into the sub-model of the embodiment of the present invention.

[0050] In the embodiment of the present invention, the fitting parameter X nf0 has a value range of -1e 12 ~1e 12 ; the fitting parameter A has a value range of -1e 12 ~1e 12 ; the fitting parameter X nf1 has a value range of -1e 6 ~1e 6 ; the fitting parameter B has a value range of -1e 6 ~1e 6 ; the fitting parameter X nf2 has a value range of -1e6~1e6; the fitting parameter C has a value range of -1e 6 ~1e 6 ; the fitting parameter X nf3 has a value range of -1e -6 ~-1e -10 or 1e -10 ~1e -6 ; the fitting parameter D has a value range of -1e 6 ~1e 6 ; the fitting parameter X nf4 has a value range of -1e -6 ~-1e -10 or 1e -10 ~1e -6 ; the fitting parameter E has a value range of -1e 6 ~1e 6 ; the fitting parameter X nf5 has a value range of -1e -12 ~-1e -16 or 1e -16 ~1e -12 ; the fitting parameter F has a value range of -1e 6 ~1e6 。

[0051] The set value in the first embodiment of the present invention includes 0.9% to 1.1%. For example, it can take the value of 1%. Therefore, when adjusting the fitting parameters so that the errors between the multi-finger effect correction parameters obtained by simulation under different finger numbers, different channel widths, and different channel lengths and the measured electrical characteristic parameters are all within 1%, the value of the corresponding fitting parameter at this time is the determined fitting parameter value. In other embodiments of the present invention, the set value can also be other values.

[0052] Embodiment 2

[0053] Please refer to Figure 2 , the embodiment of the present invention provides a modeling method for a metal oxide semiconductor, including:

[0054] S21: Establish an initial sub-circuit simulation model as follows:

[0055]

[0056] Among them, Y_MF is the multi-finger (MF) effect correction parameter, NF is the number of fingers of the MOS device gate, X nf0 , A, X nf1 , B, X nf2 , C, X nf3 , D, X nf4 , E, X nf5 and F are all fitting parameters, W is the channel width, L is the channel length, X nf6 is a fitting parameter;

[0057] S22: Obtain multiple measured electrical characteristic parameters of the metal oxide semiconductor under different finger numbers, different channel widths, and different channel lengths;

[0058] S23: Adjust the fitting parameters so that when the errors between the multi-finger effect correction parameters obtained by simulation under different finger numbers, different channel widths, and different channel lengths and the measured electrical characteristic parameters are all within the set value, determine the value of the corresponding fitting parameter at this time;

[0059] S24: Establish the following multi-finger (MF) effect model:

[0060] Y = K + Y_MF, where K is a constant, and K is the value obtained when performing model fitting when the number of fingers is 1, that is, NF = 1. The value in the embodiment of the present invention can be 0.21. Y is the correction parameter, Y_MF is the multi-finger (MF) effect correction parameter, Y is a certain parameter in the selected BSIM model, and by selecting Y and adding MF to it, the effect correction parameter Y_MF is obtained.

[0061] Preferably, the correction parameters include: the long-channel threshold voltage vth0 without body bias effect, the low-field mobility u0, the first-order coefficient ua of mobility degradation caused by the longitudinal electric field, the second-order coefficient ub of mobility degradation caused by the longitudinal electric field, the channel length dependence coefficient a0 of the body charge effect, the gate voltage dependence coefficient ags of the body charge effect, and / or the carrier saturation velocity vsat. One or several of them can be selected for correction. The long-channel threshold voltage vth0 without body bias effect also includes the threshold voltage with a smaller channel length and the threshold voltage with a smaller channel width. The low-field mobility u0 includes the mobility with a smaller channel length. The carrier saturation velocity vsat includes the carrier saturation velocity with a smaller channel length and the carrier saturation velocity with both a smaller channel length and a smaller channel width. Except for the different model formulas, the other methods in the second embodiment are the same as those in the first embodiment and will not be elaborated here. For example, taking the threshold voltage as an example, the initial sub-model formula is as follows:

[0062]

[0063] where dvth0_MF is the correction parameter for the multi-finger effect of the long-channel threshold voltage vth0 without body bias effect, NF is the number of fingers of the MOS device gate, dvth nf0 , A, dvth nf1 , B, dvth nf2 , C, dvth nf3 , D, dvth nf4 , E, dvth nf5 and F are all fitting parameters, W is the channel width, L is the channel length, dvth nf6 is a fitting parameter.

[0064] In the embodiment of the present invention, the value range of the fitting parameter X nf0 is -1e 12 ~1e 12 , the value range of the fitting parameter A is -1e 12 ~1e 12 , the value range of the fitting parameter X nf1 is -1e 6 ~1e 6 , the value range of the fitting parameter B is -1e 6 ~1e 6 , the value range of the fitting parameter X nf2 is -1e6~1e6, the value range of the fitting parameter C is -1e 6 ~1e 6 , the value range of the fitting parameter X nf3 is -1e -6 ~-1e -10 or 1e -10 ~1e -6, the value range of the fitting parameter D is -1e 6 ~1e 6 , the fitting parameter X nf4 has a value range of -1e -6 ~-1e -10 or 1e -10 ~1e -6 , the value range of the fitting parameter E is -1e 6 ~1e 6 , the fitting parameter X nf5 has a value range of -1e -12 ~-1e -16 or 1e -16 ~1e -12 , the value range of the fitting parameter F is -1e 6 ~1e 6 .

[0065] Please refer to Figure 3 , which is an example with the electrical characteristic parameter being the threshold voltage. Figure 3 In it, the channel width W is 1 micron, the channel length L is 0.15 micron, the abscissa is the finger number NF, and the ordinate is the threshold voltage. It can be seen that the simulation data of the threshold voltage of the existing technology (background technology model) can only increase, while the simulation data of the threshold voltage of the first and second embodiments of the present invention (the present invention model) can increase and also decrease. The simulation data of the first and second embodiments of the present invention is more consistent with the measured data (Silicon Data). Please refer to Figure 4 and Figure 5 , which is an example with the electrical characteristic parameter being the threshold voltage. Figure 4 In it, the channel width W is 6 microns, the channel length L is 0.15 micron, the abscissa is the finger number NF, and the ordinate is the threshold voltage. Figure 5 In it, the channel width W is 6 microns, the channel length L is 10 microns, the abscissa is the finger number NF, and the ordinate is the threshold voltage. It can be seen that the simulation data of the threshold voltage of the existing technology (background technology model) can only increase in different sizes and cannot increase and decrease sometimes as the size changes, while the first and second embodiments of the present invention (the present invention model) simulate the characteristics of MOS devices with different channel widths W and channel lengths L changing with different finger numbers NF. The simulation data of the first and second embodiments of the present invention is more consistent with the measured data (Silicon Data).

[0066] In summary, in the metal oxide semiconductor modeling method provided by the embodiments of the present invention, using the model of the present invention can simulate the measured data with an increasing and decreasing NF effect trend. Moreover, it accurately simulates the characteristics of MOS devices with different channel widths W and channel lengths L changing with different finger numbers NF.

[0067] The above are only the preferred embodiments of the present invention and do not impose any limitation on the present invention. Any person skilled in the art, within the scope of the technical solution of the present invention, makes any form of equivalent substitution or modification and other changes to the technical solution and technical content disclosed by the present invention, which are all within the content of the technical solution of the present invention and still fall within the protection scope of the present invention.

Claims

1. A modeling method for metal oxide semiconductors, characterized in that: include: Establish the initial subcircuit simulation model as follows: Among them, Y_MF is the multi-finger effect correction parameter, NF is the fork index of the MOS device gate, X nf0 , A, X nf1 , B, X nf2 , C, X nf3 , D, X nf4 , E, X nf5 and F are fitting parameters, W is the channel width, L is the channel length, X nf6 is the fitting parameter; Obtain multiple measured electrical characteristic parameters of metal oxide semiconductors at different interdigitations, different channel widths, and different channel lengths; Adjusting the fitting parameters so that when the errors between the multi-finger effect correction parameters obtained by simulation under different fingers, different channel widths and different channel lengths and the measured electrical characteristic parameters are within the set values, determining the values ​​of the fitting parameters corresponding to this time; The following multi-finger effect model is established: Y=K+Y_MF, wherein K is a constant, Y is a correction parameter, and Y_MF is a multi-finger effect correction parameter.

2. The method for modeling a metal oxide semiconductor according to claim 1, characterized in that: The correction parameters include: long channel threshold voltage without liner bias effect, low field mobility, first-order mobility degradation coefficient caused by longitudinal electric field, second-order mobility degradation coefficient caused by longitudinal electric field, channel length dependence coefficient of body charge effect, gate voltage dependence coefficient of body charge effect and / or carrier saturation motion velocity.

3. The method for modeling a metal oxide semiconductor according to claim 1, wherein: Fitting parameter X nf0 The value range is -1e 12 ~1e 12 , the value range of the fitting parameter A is -1e 12 ~1e 12 , fitting parameter X nf1 The value range is -1e 6 ~1e 6 , the value range of the fitting parameter B is -1e 6 ~1e 6 , fitting parameter X nf2 The value range of is -1e6~1e6, and the value range of the fitting parameter C is -1e 6 ~1e 6 , fitting parameter X nf3 The value range is -1e -6 ~-1e -10 or 1e -10 ~1e -6 , the value range of the fitting parameter D is -1e 6 ~1e 6 , fitting parameter X nf4 The value range is -1e -6 ~-1e -10 or 1e -10 ~1e -6 , the value range of the fitting parameter E is -1e 6 ~1e 6 , fitting parameter X nf5 The value range is -1e -12 ~-1e -16 or 1e -16 ~1e -12 , the value range of the fitting parameter F is -1e 6 ~1e 6 .

4. The method for modeling a metal oxide semiconductor according to claim 1, wherein: The value of k includes 0.

21.

5. The method for modeling a metal oxide semiconductor according to claim 1, wherein: The set value includes 0.9% to 1.1%.

6. A modeling method for metal oxide semiconductors, characterized in that: include: Establish the initial subcircuit simulation model as follows: Among them, Y_MF is the multi-finger effect correction parameter, NF is the fork index of the MOS device gate, X nf0 , A, X nf1 , B, X nf2 , C, X nf3 , D, X nf4 , E, X nf5 and F are fitting parameters, W is the channel width, L is the channel length, X nf6 is the fitting parameter; Obtain multiple measured electrical characteristic parameters of metal oxide semiconductors at different fork indices, different channel widths and different channel lengths; Adjusting the fitting parameters so that when the errors between the multi-finger effect correction parameters obtained by simulation under different fingers, different channel widths and different channel lengths and the measured electrical characteristic parameters are within the set values, determining the values ​​of the fitting parameters corresponding to this time; The following multi-finger effect model is established: Y=K+Y_MF, wherein K is a constant, Y is a correction parameter, and Y_MF is a multi-finger effect correction parameter.

7. The method for modeling a metal oxide semiconductor according to claim 6, characterized in that: The correction parameters include: long channel threshold voltage without liner bias effect, low field mobility, first-order mobility degradation coefficient caused by longitudinal electric field, second-order mobility degradation coefficient caused by longitudinal electric field, channel length dependence coefficient of body charge effect, gate voltage dependence coefficient of body charge effect and / or carrier saturation motion velocity.

8. The method for modeling a metal oxide semiconductor according to claim 6, wherein: Fitting parameter X nf0 The value range is -1e 12 ~1e 12 , the value range of the fitting parameter A is -1e 12 ~1e 12 , fitting parameter X nf1 The value range is -1e 6 ~1e 6 , the value range of the fitting parameter B is -1e 6 ~1e 6 , fitting parameter X nf2 The value range of is -1e6~1e6, and the value range of the fitting parameter C is -1e 6 ~1e 6 , fitting parameter X nf3 The value range is -1e -6 ~-1e -10 or 1e -10 ~1e -6 , the value range of the fitting parameter D is -1e 6 ~1e 6 , fitting parameter X nf4 The value range is -1e -6 ~-1e -10 or 1e -10 ~1e -6 , the value range of the fitting parameter E is -1e 6 ~1e 6 , fitting parameter X nf5 The value range is -1e -12 ~-1e -16 or 1e -16 ~1e -12 , the value range of the fitting parameter F is -1e 6 ~1e 6 .

9. The method for modeling a metal oxide semiconductor according to claim 6, wherein: The value of k includes 0.

21.

10. The method for modeling a metal oxide semiconductor according to claim 6, wherein: The set value includes 0.9% to 1.1%.

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