CN114462343A - GaN HEMT ASM model direct current parameter extraction method - Google Patents
GaN HEMT ASM model direct current parameter extraction method Download PDFInfo
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Abstract
A GaN HEMT ASM model direct current parameter extraction method is characterized by comprising the following steps: 1) process parameters of a given device; 2) extracting relevant parameters of a capacitance-voltage relation curve: extracting relevant parameters through an inverse conducting capacitance-drain voltage curve, an output capacitance-drain voltage curve, an input capacitance-drain voltage curve and a grid capacitance-gate voltage curve; 3) extracting relevant parameters of a current-voltage relation curve: parameter extraction is performed on the critical part drain current drain voltage curve and drain current gate voltage curve and parameter extraction is performed with all drain current drain voltage curves and drain current gate voltage curves. The method for extracting the direct current parameters of the ASM model of the GaN HEMT can reduce the parameter extraction times and improve the direct current parameter extraction efficiency and the parameter extraction accuracy of the ASM model of the GaN HEMT.
Description
Technical Field
The invention relates to the field of integrated circuit automatic design, in particular to an ASM model direct current parameter extraction method of a gallium nitride high electron mobility transistor (GaN HEMT).
Background
Gallium nitride advanced SPICE model (GaN ASM) is considered an industry compact standard model for power GaN and radio frequency GaN, and is currently used primarily in the industry. Besides discussing large-signal modeling, the GaN ASM model realizes accurate modeling on the characteristics of field plate capacitance, trap effect, Kink effect, noise and the like of the GaN HEMT. In a direct current parameter extraction method commonly used by the model, a drain current _ drain voltage (id _ vd) curve and a drain current _ gate voltage (id _ vg) curve are extracted by differentiating the parameters, and actually many parameters influence both the drain current _ drain voltage (id _ vd) curve and the drain current _ gate voltage (id _ vg) curve, and sometimes the drain current _ drain voltage (id _ vd) curve which is adjusted before is disturbed when the drain current _ drain voltage (id _ vd) curve is adjusted, so that only the drain current _ gate voltage (id _ vg) curve can be adjusted again, therefore, repeated extraction is needed for many times, the complexity of parameter extraction is increased, and the parameter extraction efficiency is reduced.
In addition, in the process of using an optimizer to extract automatic parameters, the parameter change trend and interval are judged by calculating the root mean square error (RMS) error rate in most cases, and when all the drain current _ drain voltage (id _ vd) measurement curves and the drain current _ gate voltage (id _ vg) measurement curves are used for extracting parameters by automatic optimization, the small current curve under the small voltage has a large influence on the error rate calculation in the automatic optimization process, so that the parameter change trend and interval selection are influenced, and the accuracy of extracting direct current parameters is reduced.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention aims to provide the method for extracting the direct current parameters of the ASM model of the GaN HEMT, so that the direct current parameter extraction efficiency and the parameter extraction accuracy of the ASM model of the GaN HEMT are improved.
In order to achieve the purpose, the method for extracting the direct current parameters of the ASM model of the GaN HEMT comprises the following steps:
1) process parameters of a given device;
2) extracting relevant parameters of a capacitance-voltage relation curve: extracting relevant parameters through an inverse conducting capacitor drain voltage curve, an output capacitor drain voltage curve, an input capacitor drain voltage (ciss _ vd) curve and a grid capacitor gate voltage curve;
3) extracting relevant parameters of a current-voltage relation curve: parameter extraction is performed on the critical part drain current drain voltage curve and drain current gate voltage curve and parameter extraction is performed with all drain current drain voltage curves and drain current gate voltage curves.
Further, the process parameters include: device length, device width, device gate index, device gate-source length, and device drain-source length.
Further, the step 2) further comprises the step of,
extracting drain-source overlapping capacitance parameters, fringe capacitance parameters, bias voltage parameters and leakage saturation voltage parameters in a capacitance-voltage model from the inverse conducting capacitance-leakage voltage curve;
extracting drain-source capacitance parameters and drain edge capacitance parameters from an input capacitance-drain voltage curve, controlling parameters of values irrelevant to drain-source capacitance under low drain-source voltage, zero drain-source voltage access region capacitance parameters, attenuation parameters under high drain-source voltage and drain built-in potential parameters;
extracting a parameter gate-source overlap capacitance parameter from the input capacitance-drain voltage curve;
extracting parameters AlGaN layer thickness parameters from a grid capacitance _ grid voltage curve, quantum mechanical effect pre-factors and switching parameters in inversion, capacitance voltage curve slope parameters under charge centroid parameters _ inversion QME, and charge centroid parameters _ QME inversion starting point parameters.
Further, the step 3) further comprises extracting parameters having influence on both the drain current _ drain voltage curve and the drain current _ gate voltage curve in the current _ voltage curve related parameter extraction process.
Further, the step 3) further includes, in the current _ voltage curve-related parameter extraction process, firstly, selecting drain current _ drain voltage curves biased to vg ═ vth/2, vth, and vgg, and a drain current _ gate voltage curve biased to vd ═ vdlin and a vthgm _ vd curve to perform parameter extraction, determining a parameter optimization interval, and then using all the curves to perform dc parameter extraction.
Further, the step 3) further comprises,
(1) extracting threshold voltage and sub-threshold swing parameters under a linear condition in a low current region of drain current _ gate voltage;
(2) extracting parameters related to the drain induced barrier lowering effect and the degradation of the sub-threshold region from the drain current _ gate voltage;
(3) extracting parameters related to mobility and vertical field strength dependence in a drain current _ gate high-current region;
(4) from the drain current drain voltage (the relevant parameters of speed saturation and output conductance are extracted;
(5) for drain current drain voltage, drain current gate voltage extracts the source drain contact region mobility.
In order to achieve the above object, the present invention further provides a device for extracting direct current parameters of an ASM model of a GaN HEMT, including a memory and a processor, where the memory stores a program running on the processor, and the processor executes the steps of the method for extracting direct current parameters of an ASM model of a GaN HEMT when running the program.
In order to achieve the above object, the present invention further provides a computer readable storage medium, on which computer instructions are stored, and the computer instructions execute the steps of the method for extracting direct current parameters of an ASM model of a GaN HEMT when the computer instructions are executed.
Compared with the prior art, the direct current parameter extraction method of the ASM model of the GaN HEMT has the following beneficial effects:
(1) considering that the influence of parameters on curves in the parameter extraction process is not single, some direct current parameters can simultaneously influence both a drain current-drain voltage (id _ vd) curve and a drain current-gate voltage (id _ vg) curve, and for the parameters influencing both the drain current-drain voltage (id _ vd) curve and the drain current-gate voltage (id _ vg) curve, the parameters are extracted by adopting a method of simultaneously optimizing the drain current-drain voltage (id _ vd) curve and the drain current-gate voltage (id _ vg) curve, so that the parameter extraction efficiency is improved;
(2) in the process of using an optimizer to extract automatic parameters, the extraction of the parameters related to a current-voltage relation (IV) curve is divided into two steps, firstly, a more key part of a drain current-drain voltage (id _ vd) curve and a drain current-gate voltage (id _ vg) curve are used for extracting the parameters through optimization to determine a parameter approximate interval, and then all the drain current-drain voltage (id _ vd) curves and the drain current-gate voltage (id _ vg) curves are used for extracting the parameters, so that the influence of part of small current curves on the parameter extraction is reduced, and the accuracy of the parameter extraction is improved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a flow chart of an ASM model direct current parameter extraction method of a GaN HEMT according to the invention;
FIG. 2 is a flow chart of GaN ASM model DC parameter extraction in the prior art;
FIG. 3 shows a flow chart of capacitance-voltage relationship (CV) curve parameter extraction;
FIG. 4 shows an overall current-voltage relationship (IV) curve parameter extraction flow chart;
FIG. 5 shows a partial current-voltage relationship (IV) curve parameter extraction flow chart;
FIG. 6 is a graphical representation of measured and simulated values of output capacitance drain voltage (coss _ vd) in accordance with an embodiment of the present invention;
FIG. 7 is a graphical representation of measured and simulated values of input capacitance drain voltage (cis _ vd) in accordance with an embodiment of the present invention;
FIG. 8 is a graphical representation of measured values and simulated values of reverse conducting capacitance drain voltage (crss _ vd) in accordance with an embodiment of the present invention;
fig. 9 is a graphical representation of measured values and simulated values of gate capacitance _ gate voltage (cgg _ vg) in accordance with an embodiment of the present invention.
Fig. 10 is a graph diagram illustrating measured values and simulation values of drain current drain voltage (id _ vd) according to an embodiment of the present invention.
Fig. 11 is a graph diagram illustrating measured values of drain current _ gate voltage (id _ vg) and simulation values according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
In the embodiment of the present invention, the first and second substrates,
vd: a drain voltage;
vg: a gate voltage;
cdg: a gate-drain capacitance;
cds: a drain-source capacitance;
vds: a drain-source voltage;
id: leakage current;
ig: a gate current;
vdlin: a drain voltage corresponding to a linear operating region drain current (idlin);
vth: a threshold voltage;
vthgm: obtaining a threshold voltage by using a gm derivation method;
vgg: a gate supply voltage;
vdd: the drain supply voltage.
Fig. 1 is a flowchart of an ASM model direct-current parameter extraction method for a GaN HEMT according to the present invention, and the details of the ASM model direct-current parameter extraction method for a GaN HEMT of the present invention will be described below with reference to fig. 1.
First, in step 101, the process parameters of the device are given.
In the embodiment of the invention, the process parameters of a given device of the ASM model of the GaN HEMT are obtained. The technological parameters comprise: the device structure comprises the following size parameters of device length (L), device width (W), device gate index (NF), device gate source Length (LSG), device drain source Length (LDG) and the like, wherein the parameters are generally given by a device designer.
In step 102, a capacitance-voltage relationship (CV) -related parameter is extracted.
In the embodiment of the present invention, the first and second substrates,
extracting a drain-source overlap capacitance parameter (cgdo), a fringe capacitance parameter (cfgd), a bias voltage parameter (cgdl) and a leakage saturation voltage parameter (vdsatcv) in a Capacitance Voltage (CV) model from an inverse conducting capacitance-drain voltage (crss-vd) curve;
extracting a drain-source capacitance parameter (cdso), a drain edge capacitance parameter (cfd), a parameter (aj) for controlling a value irrelevant to Cds under low Vds, a zero Vds access area capacitance parameter (cj0), an attenuation parameter (caccd (mz)) under high Vds and a drain built-in potential parameter (vbi) from an input capacitance _ drain voltage (coss _ vd) curve;
in the embodiment of the invention, the low Vds is more than 0 and less than 1/2 Vds; the high Vds is greater than 1/2 Vds.
Extracting a parameter gate-source overlap capacitance parameter (cgso) from an input capacitance-drain voltage (ciss _ vd) curve;
extracting a parameter AlGaN layer thickness parameter (tbar) from a gate capacitance _ gate voltage (cgg _ vg) curve, a quantum mechanical effect pre-factor and switching parameter (adosi) in inversion, a CV curve slope parameter (bdosi) under charge centroid parameter _ inversion QME, and a charge centroid parameter _ QME inversion starting point parameter (qm0 i).
Fig. 3 shows a flow chart of the capacitance-voltage relationship (CV) parameter extraction.
In step 103, the current-voltage curve (IV) related parameter is extracted.
In the embodiment of the invention, the method further comprises the following steps:
(1) the cut-off voltage (voff) and sub-threshold swing parameters under linear conditions are extracted in the low current region of the drain current-gate voltage (id _ vg) curve.
Selecting a logarithmic form of a drain current _ gate voltage (id _ vg) curve when vd is vdlin to extract an off-voltage (voff), a sub-threshold slope parameter (nfactor)
(2) The relevant parameters of drain induced barrier lowering effect (DIBL) and sub-threshold region degradation are extracted from the drain current _ gate voltage (id _ vg) curve.
A drain induced barrier lowering effect parameter (eta0), a drain voltage subthreshold slope variation parameter (cdscdd), a drain induced barrier lowering effect and Vds related parameter (vdscale) are extracted from the vthgm _ Vds curve.
(3) Parameters related to mobility and vertical field strength dependence are extracted in a high current region of a drain current _ gate voltage (id _ vg) curve.
And extracting a low-field mobility parameter (u0), a mobility attenuation coefficient (ua) and a mobility second-order attenuation coefficient (ub) from a drain current _ gate voltage (id _ vg) curve, a drain current first-order derivative _ gate voltage (id '_ vg) curve and a drain current second-order derivative _ gate voltage (id' _ vg) curve trimming parameter leakage induced barrier lowering effect parameter (eta 0).
(4) The relevant parameters of speed saturation and output conductance are extracted from the drain current-drain voltage (id _ vd) curve.
The drain contact resistance (rdc), the source contact resistance (rsc), the two-dimensional electron gas density (n0accs) of the unit area of the source access area, the two-dimensional electron gas density (n0accd) of the unit area of the drain access area, the resistance (rth0), the mobility temperature related parameter (ute), the two-dimensional electron gas density temperature related parameter (kns0) of the access area, the saturation velocity (vsat), the saturation velocity value (vsataccs) of the access area and the velocity saturation parameter (thesat) are extracted from a drain current-drain voltage (id _ vd) curve and a drain current first derivative-drain voltage (id' vd) curve.
(5) For the drain current drain voltage (id _ vd) curve, the drain current gate voltage (id _ vg) curve extracts the source drain contact region mobility.
The parameters source access region mobility (u0accs), drain access region mobility (u0accd) are extracted from the drain current drain voltage (id _ vd) curve and the drain current gate voltage (id _ vg) curve.
Fig. 4 shows an overall current-voltage relationship (IV) curve parameter extraction flow chart.
Considering that the small-voltage and small-current curve has a large influence on the calculation of the error rate in the parameter optimization process in the automatic parameter extraction optimization process, and further influences the parameter range selection in the optimization process, part of the curve is firstly selected to extract the parameters in the IV related parameter extraction process of the process in step 103, so that the parameters are in a reasonable interval, and then all the curves are selected to extract the parameters, and the parameter extraction processes of the two steps improve the accuracy of parameter extraction.
In step 103(2), adding an id _ vd curve biased to vg ═ vth/2, vth and vgg, an id _ vg curve biased to vd ═ vdlin (wherein the id _ vd curve of vg ═ vth/2 only plays a reference role in image observation in the parameter extraction process) and a vthghgm _ vds curve, in the extraction process, firstly, the influence of the self-heating effect is not considered, the influence of other parameters is amplified, the accuracy of the parameters is facilitated, a self-heating module switch (shmod) is set to 0, and a low-field mobility parameter (u0), a drain contact resistance (rdc) and a source contact resistance (rsc) are extracted from a drain current _ gate voltage (id _ vg) curve biased to vd ═ vdlin; a drain induced barrier lowering effect parameter (eta0), a drain voltage subthreshold slope variation parameter (cdscd), a drain induced barrier lowering effect and Vds related parameter (vdscale) are extracted from the vthgm _ Vds curve. Then, considering the self-heating effect, let the self-heating module switch (shmod) be 1, and fine-tune the drain induced barrier lowering effect parameter (eta0), the drain voltage subthreshold slope variation parameter (cdscd), and the drain induced barrier lowering effect and Vds related parameter (vdscale) from the vthgm _ Vds curve.
Adding a drain current drain voltage (id _ vd) curve biased to vg ═ vth/2, vth and vgg in step 103(3), extracting a parameter thermal resistance (rth0), a mobility temperature-related parameter (ute), a saturation velocity temperature-related parameter (at), a mobility attenuation coefficient (ua), a mobility second-order attenuation coefficient (ub), a saturation velocity (vsat) and a channel length modulation coefficient (lambda); the low field mobility parameter (u0), drain contact resistance (rdc), source contact resistance (rsc) is extracted from the drain current _ gate voltage (id _ vg) curve biased at vd ═ vdlin.
After the process is completed, the range interval of the parameters is basically determined, all the drain current _ drain voltage (id _ vd) curves and drain current _ gate voltage (id _ vg) curves are used for fine adjustment of the partial current _ voltage relation (IV) parameters, and parameter extraction is performed from step 103 (4).
To further illustrate the process of the present invention, the following is illustrated with reference to example 1.
Example 1
Taking the measurement data of the GaN HEMT with L0.6 μ, W100 μ, and NF 10 at t 25 ℃ as an example, the dc parameter extraction is performed according to the proposed procedure. The parameter extraction result obtained after the parameter extraction according to the steps is as follows:
drawing corresponding CV curves and IV curves by using the extracted parameter values, and combining the measured values provided by customers to respectively obtain the following curve schematic diagrams:
the resulting plot image of the measured output capacitance drain voltage (coss _ vd) and the simulated value is shown in fig. 6.
The resulting plot image of the measured value of the input capacitance drain voltage (ciss _ vd) and the simulated value is shown in fig. 7.
The resulting plot image of the measured value of the reverse conducting capacitance drain voltage (crss _ vd) and the simulated value is shown in fig. 8.
The resulting graph image of the measured value of gate capacitance _ gate voltage (cgg _ vg) and the simulated value is shown in fig. 9.
The resulting plot image of the measured value of drain current drain voltage (id _ vd) and the simulated value is shown in fig. 10.
The resulting plot image of the measured value of drain current gate voltage (id _ vg) and the simulated value is shown in fig. 11.
Through analysis, the measured values and the simulated value error rates of CV and IV obtained by the proposed direct current parameter extraction process are both 20%, the engineering requirements are met, and the practicability of the process is proved.
Fig. 2 is a flow chart of extracting dc parameters of a GaN ASM model in the prior art, and compared with a conventional ASM model dc parameter extracting flow, the present invention has the following two advantages:
(1) at present, a direct current parameter extraction process is used to extract parameters by differentiating a drain current _ drain voltage (id _ vd) curve from a drain current _ gate voltage (id _ vg) curve, and actually many parameters have an influence on both the drain current _ drain voltage (id _ vd) curve and the drain current _ gate voltage (id _ vg) curve, and sometimes the drain current _ gate voltage (id _ vg) curve that has been adjusted before is disturbed when the drain current _ drain voltage (id _ vd) curve is adjusted, so that only the drain current _ gate voltage (id _ vg) curve can be adjusted again. Therefore, repeated extraction is needed for many times, the complexity of parameter extraction is increased, the parameter extraction efficiency is reduced, parameters influencing both the drain current _ drain voltage (id _ vd) curve and the drain current _ gate voltage (id _ vg) curve are simultaneously considered in the process to extract, the condition that parameter adjustment seriously influences one curve can be prevented, and the parameter extraction efficiency is improved;
(2) in the process of using an optimizer to extract automatic parameters, the trend and the interval of parameter change are judged by calculating RMS error rate under most conditions, and when all drain current _ drain voltage (id _ vd) measurement curves and drain current _ gate voltage (id _ vg) measurement curves are used for extracting parameters in the current direct current parameter extraction process, the small current curve under small voltage has a large influence on the error rate calculation in the automatic optimization process, which has a great influence on the judgment of the parameter change interval of the optimizer, and further has an influence on the parameter change trend and interval selection, thereby reducing the accuracy of parameter extraction. In the process, firstly, a part of curves with large influence on parameters are selected for parameter extraction, a parameter optimization interval is approximately determined, in the process, the influence of the self-heating effect is firstly removed, the influence of other parameters is amplified, the accuracy of the parameters is facilitated, the influence of the self-heating effect is considered, the influence of the overall parameters is considered, and after the range of the overall parameter interval is approximately determined, all drain current _ drain voltage (id _ vd) measurement curves and drain current _ gate voltage (id _ vg) measurement curves are used for direct current parameter extraction.
The invention also provides a device for extracting the direct current parameters of the ASM model of the GaN HEMT, which comprises a memory and a processor, wherein the memory is stored with a program running on the processor, and the processor executes the steps of the method for extracting the direct current parameters of the ASM model of the GaN HEMT when running the program.
The invention further provides a computer-readable storage medium, wherein computer instructions are stored thereon, and when the computer instructions are executed, the steps of the method for extracting direct current parameters of the ASM model of the GaN HEMT are executed.
Those of ordinary skill in the art will understand that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A GaN HEMT ASM model direct current parameter extraction method is characterized by comprising the following steps:
1) process parameters of a given device;
2) extracting relevant parameters of a capacitance-voltage relation curve: extracting relevant parameters through an inverse conducting capacitance-drain voltage curve, an output capacitance-drain voltage curve, an input capacitance-drain voltage curve and a grid capacitance-gate voltage curve;
3) extracting relevant parameters of a current-voltage relation curve: the parameter extraction is performed for the critical part drain current-drain voltage curve and drain current-gate voltage curve and with all drain current-drain voltage curves and drain current-gate voltage curves.
2. The method of claim 1, wherein the process parameters include: device length, device width, device gate index, device gate-source length, and device drain-source length.
3. The ASM model direct current parameter extraction method of GaN HEMT according to claim 1, characterized in that the step 2) further comprises,
extracting drain-source overlapping capacitance parameters, fringe capacitance parameters, bias voltage parameters and leakage saturation voltage parameters in a capacitance-voltage model from the inverse conducting capacitance-leakage voltage curve;
extracting drain-source capacitance parameters and drain edge capacitance parameters from an input capacitance-drain voltage curve, controlling parameters of values irrelevant to drain-source capacitance under low drain-source voltage, zero drain-source voltage access region capacitance parameters, attenuation parameters under high drain-source voltage and drain built-in potential parameters;
extracting a parameter gate-source overlap capacitance parameter from the input capacitance-drain voltage curve;
extracting parameters AlGaN layer thickness parameters from a grid capacitance _ grid voltage curve, quantum mechanical effect pre-factors and switching parameters in inversion, capacitance voltage curve slope parameters under charge centroid parameters _ inversion QME, and charge centroid parameters _ QME inversion starting point parameters.
4. The method of claim 1, wherein the step 3) further comprises extracting parameters having influence on both a drain current-drain voltage curve and a drain current-gate voltage curve in a current-voltage curve-related parameter extraction process.
5. The method for extracting direct current parameters of an ASM model of a GaN HEMT according to claim 1, wherein said step 3) further comprises, during the current-voltage curve-related parameter extraction, first selecting drain current-drain voltage curves biased at vg = vth/2, vth and vgg, drain current-gate voltage curves biased at vd = vdlin and vthgm _ vd curves for parameter extraction, determining parameter optimization intervals, and then using all the curves for direct current parameter extraction.
6. The method for extracting direct current parameters of an ASM model of a GaN HEMT according to claim 1, wherein the step 3) further comprises,
(1) extracting threshold voltage and sub-threshold swing parameters under a linear condition in a low current region of drain current _ gate voltage;
(2) extracting parameters related to the drain induced barrier lowering effect and the degradation of the sub-threshold region from the drain current _ gate voltage;
(3) extracting parameters related to mobility and vertical field strength dependence in a drain current _ gate high-current region;
(4) from the drain current drain voltage (the relevant parameters of speed saturation and output conductance are extracted;
(5) for drain current drain voltage, drain current gate voltage extracts the source drain contact region mobility.
7. An ASM model direct current parameter extraction device for a GaN HEMT, comprising a memory and a processor, wherein the memory stores a program running on the processor, and the processor executes the program to perform the steps of the ASM model direct current parameter extraction method for a GaN HEMT according to any one of claims 1 to 6.
8. A computer readable storage medium having stored thereon computer instructions, wherein the computer instructions when executed perform the steps of the ASM model direct current parameter extraction method for GaN HEMTs of any one of claims 1-6.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH10171855A (en) * | 1996-12-11 | 1998-06-26 | Matsushita Electric Ind Co Ltd | Circuit parameter extraction device and delay calculation method |
| US5825673A (en) * | 1995-11-28 | 1998-10-20 | Ricoh Company, Ltd. | Device, method, and software products for extracting circuit-simulation parameters |
| US6266629B1 (en) * | 1998-10-29 | 2001-07-24 | Raytheon Company | Large signal model for a pseudomorphic heterojunction electron mobility transistor |
| CN104376161A (en) * | 2014-11-12 | 2015-02-25 | 华东师范大学 | Method for building AlGaN/GaN HEMT device direct current model |
| CN105468828A (en) * | 2015-11-19 | 2016-04-06 | 杭州电子科技大学 | Modelling method for surface potential basis intensive model of III-V group HEMT (High Electron Mobility Transistor) |
| CN108416167A (en) * | 2018-03-27 | 2018-08-17 | 成都海威华芯科技有限公司 | A kind of GaN HEMT devices multiple physical field coupling large-signal model method for building up |
| CN109933897A (en) * | 2019-03-12 | 2019-06-25 | 中国科学院微电子研究所 | Modeling method and model of GaN MIS-HEMT large-signal PSPICE model |
-
2022
- 2022-01-28 CN CN202210104833.7A patent/CN114462343B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5825673A (en) * | 1995-11-28 | 1998-10-20 | Ricoh Company, Ltd. | Device, method, and software products for extracting circuit-simulation parameters |
| JPH10171855A (en) * | 1996-12-11 | 1998-06-26 | Matsushita Electric Ind Co Ltd | Circuit parameter extraction device and delay calculation method |
| US6266629B1 (en) * | 1998-10-29 | 2001-07-24 | Raytheon Company | Large signal model for a pseudomorphic heterojunction electron mobility transistor |
| CN104376161A (en) * | 2014-11-12 | 2015-02-25 | 华东师范大学 | Method for building AlGaN/GaN HEMT device direct current model |
| CN105468828A (en) * | 2015-11-19 | 2016-04-06 | 杭州电子科技大学 | Modelling method for surface potential basis intensive model of III-V group HEMT (High Electron Mobility Transistor) |
| CN108416167A (en) * | 2018-03-27 | 2018-08-17 | 成都海威华芯科技有限公司 | A kind of GaN HEMT devices multiple physical field coupling large-signal model method for building up |
| CN109933897A (en) * | 2019-03-12 | 2019-06-25 | 中国科学院微电子研究所 | Modeling method and model of GaN MIS-HEMT large-signal PSPICE model |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115204089A (en) * | 2022-07-12 | 2022-10-18 | 成都华大九天科技有限公司 | Parameter extraction method of GaN HEMT based on ASM model |
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