A modeling method of a semiconductor device model and related equipment

Abstract

The application discloses a modeling method of a semiconductor device model and related equipment, relates to the technical field of semiconductors, and can improve the applicable temperature range of an electronic semiconductor device model obtained through modeling. The modeling method of the semiconductor device model comprises the following steps: performing parameter extraction on an existing semiconductor device model according to device high-temperature data obtained through actual testing of a semiconductor device, to obtain a semiconductor device high-temperature model, wherein a test environment temperature range corresponding to the device high-temperature data exceeds an environment temperature range corresponding to the existing semiconductor device model; embedding a sub-threshold leakage temperature model in the semiconductor device high-temperature model to obtain an optimized version of the semiconductor device high-temperature model; and performing temperature parameter extraction on the optimized version of the semiconductor device high-temperature model according to the device high-temperature data, to obtain a final version of the semiconductor device high-temperature model.

Description

Technical Field

[0001] This application relates to the field of semiconductor technology, and in particular to a modeling method and related equipment for semiconductor device models. Background Technology

[0002] Currently, in the aerospace field, electronic devices and sensors operate in high-temperature environments, creating an urgent need for high-temperature resistant devices and circuits. These electronic and sensing devices are typically semiconductor devices, and to accurately describe their high-temperature characteristics, device models suitable for high-temperature environments are essential. However, existing semiconductor device models have limited applicable temperature ranges, thus restricting their application. Summary of the Invention

[0003] This application provides a modeling method and related equipment for semiconductor device models, which can improve the applicable temperature range of the obtained semiconductor device models and thus expand the application scope of semiconductor device models.

[0004] A first aspect of this application provides a method for modeling a semiconductor device model, comprising:

[0005] Based on the high-temperature data of the semiconductor device obtained from actual testing, parameters are extracted from the existing semiconductor device model to obtain a high-temperature model of the semiconductor device. The test environment temperature range corresponding to the high-temperature data of the device exceeds the environment temperature range corresponding to the existing semiconductor device model.

[0006] An optimized version of the high-temperature model of the semiconductor device is obtained by embedding a subthreshold leakage temperature model into the high-temperature model of the semiconductor device.

[0007] Based on the high-temperature data of the device, temperature parameters are extracted from the optimized high-temperature model of the semiconductor device to obtain the final high-temperature model of the semiconductor device.

[0008] In some embodiments, the step of extracting parameters from an existing semiconductor device model based on high-temperature data obtained from actual testing of the semiconductor device to obtain a high-temperature model of the semiconductor device includes:

[0009] Based on the high-temperature data of the semiconductor device obtained from actual testing, the model parameters related to electrical performance in the existing semiconductor device model are extracted to obtain the high-temperature model of the semiconductor device. The model parameters related to electrical performance include model parameters related to temperature.

[0010] In some embodiments, embedding a subthreshold leakage temperature model into the high-temperature model of the semiconductor device to obtain an optimized high-temperature model of the semiconductor device includes:

[0011] By embedding an analytical expression relating subthreshold leakage current parameters to temperature into the high-temperature model of the semiconductor device, the optimized high-temperature model of the semiconductor device is obtained.

[0012] In some implementations, an analytical function relating subthreshold leakage current parameters to temperature is embedded in the high-temperature model of the semiconductor device to obtain the optimized high-temperature model of the semiconductor device, including:

[0013] The subthreshold leakage parameter in the high-temperature model of the semiconductor device is replaced by the analytical function relating the subthreshold leakage parameter to temperature, thereby relating the subthreshold leakage parameter to temperature, resulting in the optimized high-temperature model of the semiconductor device.

[0014] In some implementations, the step of extracting temperature parameters from the optimized high-temperature model of the semiconductor device based on the high-temperature data of the device to obtain the final high-temperature model of the semiconductor device includes:

[0015] Based on the high-temperature data of the device, the temperature parameters in the optimized high-temperature model of the semiconductor device are dynamically fitted so that the error between the simulated value and the actual test value of the device characteristic parameters in the high-temperature model of the semiconductor device is less than the standard error, thereby completing the extraction of the temperature parameters and obtaining the final version of the high-temperature model of the semiconductor device.

[0016] In some implementations, the temperature parameters include: subthreshold leakage current, threshold voltage, mobility, and output current.

[0017] In some embodiments, the test environment temperature range corresponding to the high temperature data of the device is -55°C to 225°C.

[0018] A second aspect of this application provides a modeling apparatus for a semiconductor device model, comprising:

[0019] The model parameter extraction module is used to extract parameters from an existing semiconductor device model based on the high-temperature data of the device obtained from actual testing of the semiconductor device, so as to obtain a high-temperature model of the semiconductor device. The test environment temperature range corresponding to the high-temperature data of the device exceeds the environment temperature range corresponding to the existing semiconductor device model.

[0020] The model building module is used to embed a subthreshold leakage temperature model into the high-temperature model of the semiconductor device to obtain an optimized version of the high-temperature model of the semiconductor device.

[0021] The model parameter extraction module is also used to extract temperature parameters from the optimized semiconductor device high-temperature model based on the device high-temperature data to obtain the final semiconductor device high-temperature model.

[0022] A third aspect of this application provides an electronic device, comprising:

[0023] A memory, wherein a computer program is stored;

[0024] A processor, which implements the modeling method for a semiconductor device model as described in the first aspect when executing the computer program.

[0025] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the modeling method for a semiconductor device model as described in the first aspect.

[0026] The semiconductor device modeling method and related equipment provided in this application extract parameters from existing semiconductor device models based on high-temperature data obtained from actual semiconductor device testing. The resulting high-temperature semiconductor device model is applicable to high-temperature environments, meaning its applicable temperature range exceeds that of existing models. This allows the high-temperature semiconductor device model to more closely approximate the electrical performance of actual electronic devices during simulation, improving its accuracy in high-temperature environments. The subthreshold leakage temperature model can be established based on actually measured high-temperature data. This model reflects the subthreshold leakage performance of semiconductor devices in high-temperature environments. Since the subthreshold leakage temperature model incorporates temperature-related parameters, the optimized high-temperature semiconductor device model embedded in it becomes correlated with ambient temperature parameters. As the ambient temperature changes, the parameters of the optimized model also change, making it more sensitive to ambient temperature. Circuit simulation results using the optimized model closely approximate actual data. By extracting temperature parameters from an optimized high-temperature model of a semiconductor device that incorporates a subthreshold leakage temperature model, the parameters of the optimized high-temperature model can be further refined to obtain a final high-temperature model. This allows the final high-temperature model to be directly correlated with ambient temperature, making it more sensitive to environmental temperatures. Circuit simulation results using the final high-temperature model are closer to real-world data. Attached Figure Description

[0027] Figure 1 A schematic flowchart illustrating a modeling method for a semiconductor device model provided in an embodiment of this application;

[0028] Figure 2A schematic diagram illustrating the fitting results between actual device transfer curve test data and model simulation values ​​provided in this application embodiment;

[0029] Figure 3 This is a schematic diagram illustrating the fitting results between actual device output curve test data and model simulation values, provided in an embodiment of this application.

[0030] Figure 4 This is a schematic diagram illustrating the fitting results between actual device threshold voltage test data and model simulation values ​​provided in an embodiment of this application.

[0031] Figure 5 A schematic diagram illustrating the fitting results between actual device linear region output current test data and model simulation values ​​provided in this application embodiment;

[0032] Figure 6 A schematic diagram illustrating the fitting results between actual device saturation region output current test data and model simulation values ​​provided in this application embodiment;

[0033] Figure 7 This is a schematic diagram illustrating the fitting results between actual device off-state leakage current test data and model simulation values ​​provided in an embodiment of this application.

[0034] Figure 8 A schematic diagram showing the fitting results of actual device off-state leakage current test data and model simulation values ​​provided in another embodiment of this application;

[0035] Figure 9 A schematic structural block diagram of a modeling apparatus for a semiconductor device model provided in this application embodiment;

[0036] Figure 10 A schematic structural block diagram of an electronic device provided in an embodiment of this application;

[0037] Figure 11 This is a schematic structural block diagram of a computer-readable storage medium provided in an embodiment of this application. Detailed Implementation

[0038] To better understand the technical solutions provided in the embodiments of this specification, the technical solutions of the embodiments of this specification will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of this specification and the specific features in the embodiments are detailed descriptions of the technical solutions of the embodiments of this specification, rather than limitations on the technical solutions of this specification. In the absence of conflict, the embodiments of this specification and the technical features in the embodiments can be combined with each other.

[0039] In this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, without necessarily requiring or implying any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. The term "two or more" includes two or more cases.

[0040] Currently, in the aerospace field, electronic devices and sensors operate in high-temperature environments, creating an urgent need for high-temperature resistant devices and circuits. These electronic and sensing devices are typically semiconductor devices, and to accurately describe their high-temperature characteristics, device models suitable for high-temperature environments are essential. However, existing semiconductor device models have limited applicable temperature ranges, thus restricting their application.

[0041] In view of this, embodiments of this application provide a modeling method and related equipment for semiconductor device models, which can improve the applicable temperature range of the semiconductor device models obtained by modeling, thereby expanding the application scope of semiconductor device models.

[0042] A first aspect of this application provides a method for modeling a semiconductor device model. Figure 1 This is a schematic flowchart illustrating a modeling method for a semiconductor device model provided in an embodiment of this application. Figure 1 As shown, the modeling method for semiconductor device models provided in this application includes:

[0043] S100: Based on the high-temperature data of the semiconductor device obtained from actual testing, parameters are extracted from the existing semiconductor device model to obtain a high-temperature model of the semiconductor device. The test environment temperature range corresponding to the high-temperature data of the device exceeds the environment temperature range corresponding to the existing semiconductor device model.

[0044] The semiconductor devices provided in this application can be based on single-crystal silicon technology, specifically bulk silicon or silicon-on-insulator (SiI) technology. This application does not impose specific limitations on these devices. Existing semiconductor device models can be any currently available semiconductor device models. These models primarily represent a collection of electrical performance parameters for a single semiconductor device. These models can be applied to the simulation of circuits, components, instruments, or devices composed of multiple electronic devices without the need to fabricate actual electronic devices. Based on the electrical performance parameters in the semiconductor device model, the functions and performance of circuits, components, instruments, or devices composed of various electronic devices can be simulated. Adjustments can be made to the device connections or device types in the circuit based on the output simulation structure. These are merely illustrative examples and are not intended to limit the specific implementation of this application.

[0045] It should be noted that the high-temperature data of the device obtained in step S100 is test data obtained by conducting electrical performance tests on the physical semiconductor device. The test environment is a high-temperature environment, and the temperature range of this high-temperature environment exceeds the applicable temperature range of the existing semiconductor device model. The actual measured high-temperature data reflects the electrical performance parameters of the semiconductor device in the high-temperature test environment. Based on the actual measured high-temperature data, parameters are extracted from the existing semiconductor device model. This parameter extraction can be understood as the correction of the model parameter values. For example, the corresponding model parameters in the existing semiconductor device can be numerically corrected using the high-temperature test data. The resulting high-temperature model of the semiconductor device can then be applied to high-temperature environments, meaning that the applicable temperature range of the high-temperature model of the semiconductor device exceeds the applicable temperature range of the existing semiconductor device model. This allows the electrical performance of the high-temperature model of the semiconductor device to be closer to the electrical performance of actual electronic devices during simulation, improving the accuracy of the high-temperature model of the semiconductor device in high-temperature environments. Parameter extraction for the existing semiconductor device model does not change the structure of the calculation formulas in the existing semiconductor device model; it only modifies the values ​​in the model parameters. The basis and direction of the modification come from the actual measured high-temperature data. The actual high-temperature data is based on the actual electrical performance data over a wider temperature range. The model parameters in the existing semiconductor device model are corrected, and the resulting high-temperature model of the semiconductor device can also be applied to the simulation of a wider range of ambient temperatures. The high-temperature model of the semiconductor device can also represent the actual electrical performance of the semiconductor device over a wider range of ambient temperatures.

[0046] For example, parameter extraction from an existing semiconductor device model can also be achieved by re-evaluating the coefficients and / or constants in the electrical performance calculation formulas of the existing semiconductor device model based on actually measured high-temperature data, thus obtaining a high-temperature model of the semiconductor device. For instance, vth0 can be re-evaluated from 0.6 to 0.75, with the modification based on the difference between the actually measured high-temperature data and the data in the existing semiconductor device model. This does not alter the architecture of the electrical performance calculation formulas in the existing semiconductor device model; it only modifies the parameter values ​​based on the existing model architecture. This improves the accuracy of the semiconductor device model without requiring a complete model rebuild, resulting in higher model construction efficiency.

[0047] For example, step S100 may include:

[0048] Based on high-temperature data obtained from actual semiconductor device testing, parameters related to electrical performance are extracted from existing semiconductor device models to obtain high-temperature models of semiconductor devices. The main purpose of parameter extraction is to expand the temperature range of semiconductor device models; therefore, extraction can be performed on temperature parameters. Model parameters related to electrical performance include temperature-related model parameters.

[0049] S200: An optimized version of the high-temperature model of semiconductor devices is obtained by embedding a subthreshold leakage temperature model into the high-temperature model of semiconductor devices.

[0050] Because high-temperature environments significantly impact the subthreshold leakage current performance of semiconductor devices, and the ability to correct model parameter values ​​is limited, even after parameter extraction from existing semiconductor device models based on their characteristics, some actual electrical performance test data still differ considerably from the model simulation values, especially the off-state leakage current. Further optimization is needed, primarily focusing on subthreshold leakage current parameters. Further optimization can involve embedding a subthreshold leakage current temperature model into the high-temperature model of the semiconductor device. For example, the subthreshold leakage current temperature model can be established based on actually measured high-temperature data. This model reflects the subthreshold leakage current performance of the semiconductor device in high-temperature environments. Since the subthreshold leakage current temperature model contains temperature-related parameters, the optimized high-temperature model of the semiconductor device embedded in it becomes correlated with the ambient temperature parameters. As the ambient temperature changes, the parameters of the optimized high-temperature model also change accordingly, making the optimized model more sensitive to ambient temperature. Circuit simulation results using the optimized high-temperature model are then closer to actual data.

[0051] In some examples, step S200 may include:

[0052] An optimized version of the high-temperature model of semiconductor devices is obtained by embedding an analytical expression of the relationship between subthreshold leakage current parameters and temperature into the high-temperature model of semiconductor devices.

[0053] In some examples, an optimized version of the high-temperature semiconductor device model is obtained by embedding an analytical function relating the subthreshold leakage current parameter to temperature into the high-temperature model of the semiconductor device, including:

[0054] The subthreshold leakage parameter in the high-temperature model of semiconductor devices is replaced by the analytical function relating the subthreshold leakage parameter to temperature, thus relating the subthreshold leakage parameter to temperature, resulting in an optimized version of the high-temperature model of semiconductor devices.

[0055] For example, embedding the subthreshold leakage temperature model can be understood as replacing the subthreshold leakage parameter in the high-temperature model of the semiconductor device with the subthreshold leakage temperature model. The subthreshold leakage temperature model can be an analytical function relating the subthreshold leakage parameter and temperature. When extracting parameters from an existing semiconductor device model based on high-temperature data, the subthreshold leakage parameter voff in the high-temperature model of the semiconductor device is obtained as a fixed value, independent of temperature. A functional expression relating subthreshold leakage current and temperature, vofft, can be embedded into the original formula for calculating subthreshold leakage current. The original formula still uses voff to represent the subthreshold leakage current. Therefore, the optimized high-temperature model for semiconductor devices obtained by embedding the subthreshold leakage current temperature model can be expressed as: voff = vofft, where vofft = voff0 × (1 + a × (temper + 55)), where temper is the ambient temperature parameter. Temper can be the current ambient temperature, i.e., the temperature of the environment where the semiconductor device is located. voff0 and a are the correlation coefficients between subthreshold leakage current and ambient temperature, which can be used to characterize the influence of ambient temperature on subthreshold leakage current. For example, voff0 = -0.17416 and a = 1.248541E. -3 .

[0056] For example, the code implementation is as follows:

[0057] subcktnmost dgseb nmost w='1u' l='1u'

[0058] param

[0059] +voff0=-0.17416 a=1.248541E-3

[0060] param

[0061] +vofft='voff0*(1+a*(temper+55))'

[0062] +voff = 'vofft'

[0063] ...

[0064] S300: Based on the high-temperature data of the device, extract temperature parameters from the optimized high-temperature model of the semiconductor device to obtain the final high-temperature model of the semiconductor device. Based on the high-temperature data of the device, extract temperature parameters from the optimized high-temperature model of the semiconductor device, which embeds a subthreshold leakage temperature model, to further refine the parameters of the optimized high-temperature model. For example, the extraction of temperature parameters can involve modifying voff0 and a.

[0065] It is important to note that in the aerospace field, semiconductor devices operate in high-temperature environments, creating a pressing need for high-temperature resistant devices and circuits. Compared to bulk silicon, SOI (Silicon-On-Insulator) offers significant advantages in high-temperature applications and has been widely adopted. However, to accurately describe the high-temperature characteristics of SOI devices, a semiconductor device model suitable for high-temperature environments is essential. But for standard SOI processes, manufacturers can only provide semiconductor device models that meet military standards from -55°C to 125°C, which are not suitable for high-temperature environments. Therefore, research on high-temperature models for SOI devices is necessary to establish device models suitable for high-temperature environments for circuit simulation. The high-temperature modeling method for SOI devices proposed in this paper is based on the existing BSIMSOI model; that is, existing semiconductor device models can be used as BSIMSOI models.

[0066] To address the aforementioned issues, the semiconductor device modeling method provided in this application extracts parameters from existing semiconductor device models based on high-temperature data obtained from actual semiconductor device testing. The resulting high-temperature semiconductor device model is applicable to high-temperature environments, meaning its applicable temperature range exceeds that of existing models. This allows the high-temperature semiconductor device model to more closely reflect the electrical performance of actual electronic devices during simulation, improving its accuracy in high-temperature environments. The subthreshold leakage temperature model can be established based on actually measured high-temperature data. This model reflects the subthreshold leakage performance of semiconductor devices in high-temperature environments. Since the subthreshold leakage temperature model incorporates temperature-related parameters, the optimized high-temperature semiconductor device model embedded in it becomes correlated with ambient temperature parameters. As the ambient temperature changes, the parameters of the optimized model also change, making it more sensitive to ambient temperature. Circuit simulation results using the optimized model closely approximate actual data. By extracting temperature parameters from an optimized high-temperature model of a semiconductor device that incorporates a subthreshold leakage temperature model, the parameters of the optimized high-temperature model can be further refined to obtain a final high-temperature model. This allows the final high-temperature model to be directly correlated with ambient temperature, making it more sensitive to environmental temperatures. Circuit simulation results using the final high-temperature model are closer to real-world data.

[0067] In some implementations, temperature parameters are extracted from the optimized high-temperature model of the semiconductor device based on the device's high-temperature data to obtain the final high-temperature model of the semiconductor device, including:

[0068] Based on the high-temperature data of the device, the temperature parameters in the optimized high-temperature model of the semiconductor device are dynamically fitted to ensure that the error between the simulated value and the actual test value of the device characteristic parameters in the high-temperature model of the semiconductor device is less than the standard error, so as to complete the extraction of temperature parameters and obtain the final version of the high-temperature model of the semiconductor device.

[0069] It should be noted that the dynamic fitting process can involve multiple fitting iterations. The fitting process can be understood as the simulation of semiconductor device performance by the semiconductor device model. Dynamic fitting can repeatedly train and correct the polarity of the temperature parameters in the optimized high-temperature semiconductor device model, reducing the error between the simulated values ​​and actual test values ​​of the device characteristic parameters in the high-temperature model. Typically, the fitting can be performed until the error is less than the standard error, resulting in a final high-temperature semiconductor device model that reflects the actual performance of the semiconductor device in a high-temperature environment. For example, the standard error can be an industry-established standard, such as 10%, which is merely illustrative and not intended to limit the scope of this application.

[0070] In some implementations, model parameters may include coefficients and constants in the electrical performance data calculation formulas, including temperature-related model parameters. For example, each parameter can be calculated using a corresponding electrical performance data calculation formula, which may include relevant coefficients and constants, which are the model parameters. For instance, the basic model parameters included in the electrical performance data calculation formulas for device threshold voltage, mobility, and output current include vth0, k2, u0, ua, ub, uc, and vsat, while temperature-related model parameters include kt1, kt2, ute, ua1, ub1, at, and voff and ndiode. vth0, k2, u0, ua, ub, uc, vsat, kt1, kt2, ute, ua1, ub1, at, voff, and ndiode are all names of the model parameters. In existing semiconductor device models, model parameters are set in numerical form.

[0071] In some implementations, the test environment temperature range corresponding to the device's high-temperature data is -55°C to 225°C. Compared to the upper limit of the temperature range of 125°C in the prior art, raising the upper limit of the test environment temperature corresponding to the device's high-temperature data to 225°C can increase the applicable temperature range of the semiconductor device model to 225°C.

[0072] The modeling method for semiconductor device models provided in this application can improve the simulation accuracy of the model at high temperatures and broaden its temperature application range by establishing a functional analytical expression between the subthreshold leakage current parameter and temperature without changing the source code of the semiconductor device model, embedding the subthreshold leakage current temperature into the original model for optimization, and extracting temperature-related parameters.

[0073] For example, taking a MOSFET based on SOI technology as an example, Figure 2 This is a schematic diagram illustrating the fitting results between actual device transfer curve test data and model simulation values, provided as an embodiment of this application. Figure 2As shown, the horizontal axis represents the gate-source voltage vgs of the MOSFET (in V), the vertical axis represents the drain-source output current ids (in A), and the right side represents the ambient temperature T (in °C). The ambient temperature T can represent the actual test environment temperature or the ambient temperature associated with the model. Figure 2 The dotted data represents the actual device transfer curve test data, the continuous curve represents the device transfer curve model simulation value, ids_vgs_T is the test item, which can be understood as the result graph of the drain-source output current of the MOSFET changing with the gate-source voltage and temperature, W / L=1 / 0.18 represents the channel width of the MOSFET as 1μm / 0.18μm, @ represents the separator, Vds / Vps=0.1 / 0 represents the drain-source voltage and body voltage of the MOSFET as 0.1V and 0V respectively, W / L=1 / 0.18@Vds / Vps=0.1 / 0 as a whole represents the test conditions of the ids_vgs_T test item. Figure 2 The MAX value in the bottom right corner, 3.040%, indicates that the maximum model error rate is 3.040%, which is the fitting result between the device transfer curve test data and the model simulation value of the MOSFET.

[0074] For example, Figure 3 This is a schematic diagram illustrating the fitting result between actual device output curve test data and model simulation values, provided as an embodiment of this application. Figure 3 As shown, the horizontal axis vds represents the drain-source voltage (in V). The test conditions for the device output data are Vps / Vgs = 0 / 1.8. The maximum model error rate of the fitting results between the device output curve test data and the simulation value is 3.214%. Figure 2 and Figure 3 These are all schematic diagrams of IV curves (current-voltage curves).

[0075] For example, Figure 4 This diagram illustrates the fitting results between actual device threshold voltage test data and model simulation values, as provided in an embodiment of this application. Figure 4 As shown, the horizontal axis t represents the ambient temperature, and the vertical axis vth represents the threshold voltage of the device. The test conditions are Vps / Vds = 0 / 0.1. The maximum model error rate of the fitting results between the actual device threshold voltage test data and the model simulation value is 4.705%.

[0076] For example, Figure 5 This diagram illustrates the fitting results between actual device linear region output current test data and model simulation values, as provided in an embodiment of this application. Figure 5 As shown, the horizontal axis t represents the ambient temperature, and the vertical axis idlin represents the output current in the linear region of the device. The test conditions are Vds / Vps / Vgs=0.1 / 0 / 1.8. The maximum model error rate of the fitting results between the actual device linear region output current test data and the model simulation value is 2.594%.

[0077] For example, Figure 6 This diagram illustrates the fitting results between actual device saturation region output current test data and model simulation values, as provided in an embodiment of this application. Figure 6 As shown, the horizontal axis t represents the ambient temperature, and the vertical axis idsat represents the output current in the saturation region of the device. The test conditions are Vps / Vgs / Vds=0 / 1.8 / 1.8. The maximum model error rate of the fitting results between the actual device output current in the saturation region test data and the model simulation value is 2.304%.

[0078] For example, Figure 7 This diagram illustrates the fitting results between actual device off-state leakage current test data and model simulation values, as provided in an embodiment of this application. Figure 7 As shown, the horizontal axis t represents the ambient temperature, and the vertical axis ioff represents the device's off-state leakage current. The test conditions are Vds / Vps / Vgs=1.8 / 0 / 0. The maximum model error rate of the fitting results between the actual device off-state leakage current test data and the model simulation value is 64.232%.

[0079] In some implementations, the error rate is set to 10%. The high-temperature model of the semiconductor device is obtained by extracting parameters from an existing semiconductor device model. Figures 2-6 The corresponding model error rates are all less than 10%. Figure 7 If the model error rate corresponding to the device's off-state leakage current is greater than 10%, then further optimization of the relevant parameters of the device's off-state leakage current, namely the subthreshold leakage current parameters, is required.

[0080] For example, Figure 8 This diagram illustrates the fitting results between actual device off-state leakage current test data and model simulation values, as provided in another embodiment of this application. The diagram shows the final high-temperature model of the semiconductor device obtained after embedding a subthreshold leakage temperature model and extracting temperature parameters. The model error rate of the fitting results between the actual device off-state leakage current test data and model simulation values ​​decreased from 64.232% to 6.297%, meeting the standard of less than 10%.

[0081] A second aspect of this application provides a modeling apparatus for semiconductor device models. Figure 9 This is a schematic structural block diagram of a modeling apparatus for a semiconductor device model provided in an embodiment of this application. Figure 9 As shown, the modeling apparatus for semiconductor device models provided in this application embodiment includes:

[0082] The model parameter extraction module 400 is used to extract parameters from an existing semiconductor device model based on the high-temperature data of the device obtained from actual testing of the semiconductor device, and to obtain a high-temperature model of the semiconductor device, wherein the test environment temperature range corresponding to the high-temperature data of the device exceeds the environment temperature range corresponding to the existing semiconductor device model.

[0083] Model building module 500 is used to embed a subthreshold leakage temperature model into a high-temperature model of semiconductor devices to obtain an optimized high-temperature model of semiconductor devices.

[0084] The model parameter extraction module 400 is also used to extract temperature parameters from the optimized high-temperature model of the semiconductor device based on the high-temperature data of the device, so as to obtain the final high-temperature model of the semiconductor device.

[0085] The semiconductor device modeling apparatus provided in this application extracts parameters from existing semiconductor device models based on high-temperature data obtained from actual semiconductor device testing. The resulting high-temperature semiconductor device model is applicable to high-temperature environments, meaning its applicable temperature range exceeds that of existing models. This allows the high-temperature semiconductor device model to more closely resemble the electrical performance of actual electronic devices during simulation, improving its accuracy in high-temperature environments. The subthreshold leakage temperature model can be established based on actually measured high-temperature data. This model reflects the subthreshold leakage performance of semiconductor devices in high-temperature environments. Since the subthreshold leakage temperature model incorporates temperature-related parameters, the optimized high-temperature semiconductor device model embedded in it becomes correlated with ambient temperature parameters. As the ambient temperature changes, the parameters of the optimized model also change, making it more sensitive to ambient temperature. Circuit simulation results using the optimized model closely approximate actual data. By extracting temperature parameters from an optimized high-temperature model of a semiconductor device that incorporates a subthreshold leakage temperature model, the parameters of the optimized high-temperature model can be further refined to obtain a final high-temperature model. This allows the final high-temperature model to be directly correlated with ambient temperature, making it more sensitive to environmental temperatures. Circuit simulation results using the final high-temperature model are closer to real-world data.

[0086] A third aspect of this application provides an electronic device. Figure 10 This is a schematic structural block diagram of an electronic device provided in an embodiment of this application. Figure 10 As shown, the electronic device includes:

[0087] A memory 600, wherein a computer program is stored in the memory 600;

[0088] A processor 700 is configured to implement a modeling method for a semiconductor device model as described in the first aspect when executing the computer program.

[0089] The modeling method for semiconductor devices includes the following steps:

[0090] Based on the high-temperature data of the semiconductor device obtained from actual testing, parameters are extracted from the existing semiconductor device model to obtain a high-temperature model of the semiconductor device. The test environment temperature range corresponding to the high-temperature data of the device exceeds the environment temperature range corresponding to the existing semiconductor device model.

[0091] An optimized version of the high-temperature model of the semiconductor device is obtained by embedding a subthreshold leakage temperature model into the high-temperature model of the semiconductor device.

[0092] Based on the high-temperature data of the device, temperature parameters are extracted from the optimized high-temperature model of the semiconductor device to obtain the final high-temperature model of the semiconductor device.

[0093] A fourth aspect of the embodiments of this application provides a computer-readable storage medium. Figure 11 This is a schematic structural block diagram of a computer-readable storage medium provided for embodiments of this application. Figure 11 As shown, a computer program 800 is stored on the computer-readable storage medium, which, when executed by a processor, implements the modeling method for the semiconductor device model as described in the first aspect.

[0094] The modeling method for semiconductor devices includes the following steps:

[0095] Based on the high-temperature data of the semiconductor device obtained from actual testing, parameters are extracted from the existing semiconductor device model to obtain a high-temperature model of the semiconductor device. The test environment temperature range corresponding to the high-temperature data of the device exceeds the environment temperature range corresponding to the existing semiconductor device model.

[0096] An optimized version of the high-temperature model of the semiconductor device is obtained by embedding a subthreshold leakage temperature model into the high-temperature model of the semiconductor device.

[0097] Based on the high-temperature data of the device, temperature parameters are extracted from the optimized high-temperature model of the semiconductor device to obtain the final high-temperature model of the semiconductor device.

[0098] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0099] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-readable program code.

[0100] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0101] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0102] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0103] This application also provides a computer program product, which includes computer software instructions that, when executed on a processing device, cause the processing device to execute a process of a modeling method for a semiconductor device model.

[0104] A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0105] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0106] In the several embodiments provided in this application, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.

[0107] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0108] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0109] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0110] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

[0111] Although preferred embodiments have been described in this specification, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this specification.

[0112] Obviously, those skilled in the art can make various modifications and variations to this specification without departing from its spirit and scope. Therefore, if such modifications and variations fall within the scope of the claims and their equivalents, this specification is also intended to include such modifications and variations.

Claims

1. A modeling method of a semiconductor device model, characterized by, include: Based on high-temperature data obtained from actual testing of semiconductor devices, parameters are extracted from existing semiconductor device models to obtain a high-temperature model of the semiconductor device. The high-temperature data corresponds to a test environment temperature range that exceeds the environmental temperature range corresponding to the existing semiconductor device model. The high-temperature data is test data obtained by performing electrical performance tests on the actual semiconductor device, reflecting the electrical performance parameters of the semiconductor device in a high-temperature test environment. The parameter extraction involves correcting the model parameter values ​​by using the high-temperature data to numerically correct the corresponding model parameters in the existing semiconductor device. The resulting high-temperature model of the semiconductor device is suitable for high-temperature environments. An optimized version of the high-temperature model of the semiconductor device is obtained by embedding a subthreshold leakage temperature model into the high-temperature model of the semiconductor device. The subthreshold leakage temperature model is an analytical function relating the subthreshold leakage parameters to temperature, where the temperature is the ambient temperature of the semiconductor device. Embedding the subthreshold leakage temperature model into the high-temperature model of the semiconductor device yields an optimized version of the high-temperature model, including: The subthreshold leakage parameter in the high-temperature model of the semiconductor device is replaced by the analytical function relating the subthreshold leakage parameter to temperature, thereby relating the subthreshold leakage parameter to temperature, resulting in the optimized version of the high-temperature model of the semiconductor device. Based on the high-temperature data of the device, temperature parameters are extracted from the optimized high-temperature model of the semiconductor device to obtain the final high-temperature model of the semiconductor device. The step of extracting temperature parameters from the optimized high-temperature model of the semiconductor device based on the high-temperature data of the device to obtain the final high-temperature model of the semiconductor device includes: Based on the high-temperature data of the device, the temperature parameters in the optimized high-temperature model of the semiconductor device are dynamically fitted to ensure that the error between the simulated value and the actual test value of the device characteristic parameters in the high-temperature model of the semiconductor device is less than the standard error, so as to complete the extraction of the temperature parameters and obtain the final version of the high-temperature model of the semiconductor device. The temperature parameters include: subthreshold leakage current parameter, threshold voltage, mobility and output current.

2. The modeling method for semiconductor device models according to claim 1, characterized in that, The process of extracting parameters from existing semiconductor device models based on high-temperature data obtained from actual semiconductor device testing to obtain a high-temperature semiconductor device model includes: Based on the high-temperature data of the semiconductor device obtained from actual testing, the model parameters related to electrical performance in the existing semiconductor device model are extracted to obtain the high-temperature model of the semiconductor device. The model parameters related to electrical performance include model parameters related to temperature.

3. The modeling method for semiconductor device models according to claim 1, characterized in that, The test environment temperature range corresponding to the high temperature data of the device is -55℃ to 225℃.

4. A modeling apparatus of a semiconductor device model, characterized by comprising: include: The model parameter extraction module is used to extract parameters from an existing semiconductor device model based on high-temperature data obtained from actual testing of the semiconductor device, thereby obtaining a high-temperature model of the semiconductor device. The high-temperature data corresponds to a test environment temperature range that exceeds the environmental temperature range corresponding to the existing semiconductor device model. The high-temperature data is test data obtained by performing electrical performance tests on the semiconductor device itself, reflecting the electrical performance parameters of the semiconductor device in a high-temperature test environment. The parameter extraction involves correcting the corresponding model parameters in the existing semiconductor device using the high-temperature data, resulting in a high-temperature model of the semiconductor device suitable for high-temperature environments. The model building module is used to embed a subthreshold leakage temperature model into the high-temperature model of the semiconductor device to obtain an optimized version of the high-temperature model of the semiconductor device. The subthreshold leakage temperature model is an analytical function relating the subthreshold leakage parameters to temperature, where the temperature is the ambient temperature of the semiconductor device. Embedding the subthreshold leakage temperature model into the high-temperature model of the semiconductor device yields an optimized version of the high-temperature model, including: The subthreshold leakage parameter in the high-temperature model of the semiconductor device is replaced by the analytical function relating the subthreshold leakage parameter to temperature, so that the subthreshold leakage parameter is correlated with temperature, thus obtaining the optimized version of the high-temperature model of the semiconductor device. The model parameter extraction module is also used to extract temperature parameters from the optimized semiconductor device high-temperature model based on the device high-temperature data to obtain the final semiconductor device high-temperature model. The step of extracting temperature parameters from the optimized high-temperature model of the semiconductor device based on the high-temperature data of the device to obtain the final high-temperature model of the semiconductor device includes: Based on the high-temperature data of the device, the temperature parameters in the optimized high-temperature model of the semiconductor device are dynamically fitted to ensure that the error between the simulated value and the actual test value of the device characteristic parameters in the high-temperature model of the semiconductor device is less than the standard error, so as to complete the extraction of the temperature parameters and obtain the final version of the high-temperature model of the semiconductor device. The temperature parameters include: subthreshold leakage current parameter, threshold voltage, mobility and output current.

5. An electronic device, comprising: include: A memory, wherein a computer program is stored; A processor, which executes the computer program to implement the modeling method for a semiconductor device model as described in any one of claims 1-3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the modeling method for a semiconductor device model as described in any one of claims 1-3.

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