Search

CN-116305960-B - BSIM-IMG noise model optimization method and device

CN116305960BCN 116305960 BCN116305960 BCN 116305960BCN-116305960-B

Abstract

The application provides a BSIM-IMG noise model optimization method and device, which are applied to the technical field of device reference lifting and modeling. The method comprises the steps of adding channel back interface parameters and carrier distribution parameters of an FDSOI MOSFET device, wherein the channel back interface parameters comprise NOIA, NOIB, NOIC2 and interface trap parameters, the carrier distribution parameters comprise carrier distribution peaks, and optimizing a BSIM-IMG noise model according to the channel back interface parameters and the carrier distribution parameters to obtain an optimized BSIM-IMG noise model. Thus, the back gate voltage affects the channel back interface parameter and carrier distribution parameter, which affect the magnitude of the 1/f noise. Based on channel back interface parameters and carrier distribution parameters, the BSIM-IMG noise model is optimized, namely, the noise influence of back gate voltage on channel back interface and carrier distribution is introduced, the influence of back gate voltage on 1/f noise is completely considered, and the optimized BSIM-IMG noise model improves model simulation accuracy and can accurately reflect the influence of back gate voltage on noise.

Inventors

  • LI ZIHAN
  • BU JIANHUI
  • ZHANG XINYI
  • WANG KEWEI
  • LI BO

Assignees

  • 中国科学院微电子研究所

Dates

Publication Date
20260505
Application Date
20230322

Claims (8)

  1. 1. A method for optimizing a BSIM-IMG noise model, the method comprising: adding channel back interface parameters and carrier distribution parameters of an FDSOI MOSFET device, wherein the channel back interface parameters comprise NOIA trap density parameters, NOIB trap density parameters, NOIC trap density parameters and interface trap parameters, and the carrier distribution parameters comprise carrier distribution peaks; optimizing the BSIM-IMG noise model according to the channel back interface parameter and the carrier distribution parameter to obtain an optimized BSIM-IMG noise model; Optimizing the BSIM-IMG noise model according to the channel back interface parameter and the carrier distribution parameter to obtain an optimized BSIM-IMG noise model, comprising: Calculating noise current power spectral density S id according to the NOIA trap density parameter, the NOIB trap density parameter, the NOIC trap density parameter, the interface trap parameter and the carrier distribution peak value to obtain an optimized BSIM-IMG noise model, wherein the noise current power spectral density S id is used for representing the size of a 1/f noise parameter; ; ; ; ; ; ; ; ; Wherein k is Boltzmann constant, T is temperature, q is meta-charge, For the drain-source current, In order for the mobility to be effective, Represents the tunneling coefficient, f is the frequency, L is the channel length, For oxide capacitance, R1 characterizes the effect of the channel front interface on the 1/f noise parameter, R2 characterizes the effect of the channel back interface on the 1/f noise parameter, FN1, FN2, 、 For the calculation of intermediate variables of the process, NOIA, NOIB, NOIC is the 1/f noise parameter in the existing model, In order to achieve a source-side charge density, Is the drain charge density; As the amount of front gate charge, To achieve a carrier ratio near the channel back interface, As a total number of carriers in the channel, VBG0 is a parameter of a carrier distribution peak value in a channel, namely a back gate voltage regulation parameter, VBG is back gate voltage, Is an interface trap capacitance; for the BOX layer capacitance, the capacitance of the BOX layer, Is a back interface trap parameter.
  2. 2. The method according to claim 1, wherein the method further comprises: a noise voltage power spectral density is determined based on the noise current power spectral density.
  3. 3. The method according to claim 1, wherein the method further comprises: Extracting I-V characteristic parameters of the optimized BSIM-IMG noise model by using silicon device modeling software; And determining to complete I-V characteristic fitting according to the I-V characteristic parameters.
  4. 4. The method of claim 1, wherein the FDSOI MOSFET device is 22nm.
  5. 5. A BSIM-IMG noise model optimization apparatus, the apparatus comprising: the adding module is used for adding channel back interface parameters and carrier distribution parameters of the FDSOI MOSFET device, wherein the channel back interface parameters comprise NOIA trap density parameters, NOIB trap density parameters, NOIC trap density parameters and interface trap parameters, and the carrier distribution parameters comprise carrier distribution peaks; the optimization module is used for optimizing the BSIM-IMG noise model according to the channel back interface parameter and the carrier distribution parameter to obtain an optimized BSIM-IMG noise model; The optimization module is specifically configured to calculate noise current power spectral density S id according to the NOIA trap density parameter, the NOIB trap density parameter, the NOIC trap density parameter, the interface trap parameter, and the carrier distribution peak value, and obtain an optimized BSIM-IMG noise model, where the noise current power spectral density S id is used to characterize the magnitude of a 1/f noise parameter; ; ; ; ; ; ; ; ; Wherein k is Boltzmann constant, T is temperature, q is meta-charge, For the drain-source current, In order for the mobility to be effective, Represents the tunneling coefficient, f is the frequency, L is the channel length, For oxide capacitance, R1 characterizes the effect of the channel front interface on the 1/f noise parameter, R2 characterizes the effect of the channel back interface on the 1/f noise parameter, FN1, FN2, 、 For the calculation of intermediate variables of the process, NOIA, NOIB, NOIC is the 1/f noise parameter in the existing model, In order to achieve a source-side charge density, Is the drain charge density; As the amount of front gate charge, To achieve a carrier ratio near the channel back interface, As a total number of carriers in the channel, VBG0 is a parameter of a carrier distribution peak value in a channel, namely a back gate voltage regulation parameter, VBG is back gate voltage, Is an interface trap capacitance; for the BOX layer capacitance, the capacitance of the BOX layer, Is a back interface trap parameter.
  6. 6. The apparatus of claim 5, wherein the apparatus further comprises: And the determining module is used for determining the noise voltage power spectral density based on the noise current power spectral density.
  7. 7. The apparatus of claim 5, wherein the apparatus further comprises: the extraction module is used for extracting I-V characteristic parameters of the optimized BSIM-IMG noise model by using silicon device modeling software; and the determining module is also used for determining to complete I-V characteristic fitting according to the I-V characteristic parameters.
  8. 8. A computer readable storage medium storing program code or instructions which, when run on a computer, cause the computer to perform the method of any one of claims 1-4 above.

Description

BSIM-IMG noise model optimization method and device Technical Field The application relates to the technical field of component lifting and modeling, in particular to a BSIM-IMG noise model optimization method and device. Background With the shrinking characteristics of the core MOSFET (Metal-Oxide-Semiconductor Field-Effect Transistor) devices of integrated circuits, conventional bulk silicon devices have reached physical limits. Compared with the traditional MOSFET device, the FDSOI (Fully Depleted Silicon-On-Insulator silicon-On-Insulator) MOSFET device has the advantages of smaller leakage current, adjustable voltage threshold value and the like, and has good application prospect. The Model of the FDSOI MOSFET device is BSIM-IMG (Berkeley Short-CHANNEL IGFET Model-INDEPENDENT MULTI-Gate), and the influence of low-frequency noise on the simulation result of the Model becomes non-negligible as the device size becomes smaller. At present, a BSIM-IMG noise model is subjected to model simulation based on that 1/f noise monotonically increases along with the increase of back gate voltage, and the problem of low simulation accuracy of the BSIM-IMG noise model exists. Disclosure of Invention In view of the above, the application provides a BSIM-IMG noise model optimization method and device, and the optimized BSIM-IMG noise model considers the influence of back gate voltage on 1/f noise, so that the model simulation accuracy can be effectively improved. In order to solve the problems, the technical scheme provided by the application is as follows: in a first aspect, the application provides a BSIM-IMG noise model optimization method, which comprises the steps of adding channel back interface parameters and carrier distribution parameters of an FDSOI MOSFET device, wherein the channel back interface parameters comprise NOIA < 2 > trap density parameters, NOIB < 2 > trap density parameters, NOIC < 2 > trap density parameters and interface trap parameters, the carrier distribution parameters comprise carrier distribution peak values, and optimizing a BSIM-IMG noise model according to the channel back interface parameters and the carrier distribution parameters to obtain an optimized BSIM-IMG noise model. Based on the scheme provided by the embodiment, the back gate voltage influences channel back interface parameters and carrier distribution parameters, and further influences the size of 1/f noise, the BSIM-IMG noise model is optimized based on the channel back interface parameters and the carrier distribution parameters, the optimized BSIM-IMG noise model can simulate 1/f noise more accurately, and simulation accuracy of the BSIM-IMG noise model is improved. In one possible implementation manner, the optimizing the BSIM-IMG noise model according to the channel back interface parameter and the carrier distribution parameter to obtain an optimized BSIM-IMG noise model includes: and calculating noise current power spectral density according to the NOIA trap density parameter, the NOIB trap density parameter, the NOIC trap density parameter, the interface trap parameter and the carrier distribution peak value to obtain an optimized BSIM-IMG noise model, wherein the noise current power spectral density is used for representing the 1/f noise parameter. In one possible implementation, the method further includes: a noise voltage power spectral density is determined based on the noise current power spectral density. In one possible implementation, before the adding the channel back interface parameter and the carrier distribution parameter of the FDSOI MOSFET device, the method further includes: Extracting I-V characteristic parameters of the optimized BSIM-IMG noise model by using silicon device modeling software; And determining to complete I-V characteristic fitting according to the I-V characteristic parameters. In one possible implementation, the FDSOI MOSFET device is 22nm. In a second aspect, the present application provides a BSIM-IMG noise model optimization apparatus, the apparatus comprising: The adding module is used for adding channel back interface parameters and carrier distribution parameters of the FDSOI MOSFET device, wherein the channel back interface parameters comprise NOIA trap density parameters, NOIB trap density parameters, NOIC trap density parameters and interface trap parameters, and the carrier distribution parameters comprise carrier distribution peaks; And the optimization module is used for optimizing the BSIM-IMG noise model based on the channel back interface parameter and the carrier distribution parameter to obtain an optimized BSIM-IMG noise model. In one possible implementation manner, the optimization module is specifically configured to calculate a noise current power spectrum density according to the NOIA trap density parameter, the NOIB trap density parameter, the NOIC trap density parameter, the interface trap parameter and the carrier distribution peak value, so as to obtain an