CN-121978875-A - Photoetching simulation and calibration method and system for process window

CN121978875ACN 121978875 ACN121978875 ACN 121978875ACN-121978875-A

Abstract

The invention discloses a photoetching simulation and calibration method and a photoetching simulation and calibration system for a process window, which belong to the technical field of photoetching simulation and calibration, and the technical scheme is characterized in that the basic parameters and actual measurement physical parameters of a photoetching process are obtained to obtain a standardized process physical parameter data set; according to the standard process physical parameter data set and a preset formula, a multi-physical effect coupling simulation model is obtained, according to the multi-physical effect coupling simulation model and the mass production dynamic original data, a dynamic parameter fluctuation self-adaptive model is obtained, according to the dynamic parameter fluctuation self-adaptive model and the multi-physical effect coupling simulation model, an actual measurement data set is obtained, according to the actual measurement data set and the dynamic parameter fluctuation self-adaptive model, the optimal parameter combination of the photoetching process is obtained.

Inventors

HUANG JIHUI
Yue Shaosheng
Lou Yihan

Assignees

弈芯科技(杭州)有限公司

Dates

Publication Date: 20260505
Application Date: 20260407

Claims (10)

1. A process window oriented lithography simulation and calibration method, comprising: obtaining basic parameters and actual measurement physical parameters of a photoetching process to obtain a standardized process physical parameter data set; obtaining a multi-physical effect coupling simulation model according to the standardized process physical parameter data set and a preset formula, wherein the preset formula comprises a Maxwell equation set and a Hopkins model; according to the multi-physical effect coupling simulation model and the mass production dynamic original data, a dynamic parameter fluctuation self-adaptive model is obtained; Obtaining an actual measurement data set according to the dynamic parameter fluctuation self-adaptive model and the multi-physical effect coupling simulation model; and obtaining the optimal parameter combination of the photoetching process according to the actually measured data set and the dynamic parameter fluctuation self-adaptive model.
2. The method for lithography simulation and calibration for a process window according to claim 1, wherein the obtaining a multi-physical effect coupling simulation model according to the standardized process physical parameter data set and a preset formula comprises: Obtaining real light field distribution containing inherent light field attributes according to the standardized technological physical parameter data set and the preset formula; Obtaining multi-field coupling distribution data according to the real light field distribution containing the inherent attribute of the light field and different process conditions; And encrypting according to the multi-field coupling distribution data and the self-adaptive finite element grid to obtain the multi-physical effect coupling simulation model.
3. The method for lithography simulation and calibration for a process window according to claim 2, wherein said obtaining a real light field distribution including light field inherent properties from said standardized process physical parameter dataset and said predetermined formula comprises: Constructing a light field transmission model under partial coherent illumination according to the standardized technological physical parameter data set and the Hopkins model to obtain partial coherent characteristic distribution of the light field; obtaining vector electromagnetic field distribution according to the standardized process physical parameter data set and the Maxwell equation set; And obtaining the real light field distribution containing the inherent property of the light field according to the coherence property distribution and the vector electromagnetic field distribution.
4. A process window oriented lithography simulation and calibration method according to claim 3, wherein said obtaining said multi-physical effect coupling simulation model from said multi-field coupling distribution data and adaptive finite element mesh encryption comprises: Encrypting according to the multi-field coupling distribution data and the self-adaptive finite element grid to obtain a self-adaptive finite element grid model; obtaining a replacement grid model according to the self-adaptive finite element grid model and the actually measured physical parameters; and obtaining the multi-physical effect coupling simulation model according to the replacement grid model and the multi-field coupling distribution data.
5. The method for lithography simulation and calibration for a process window according to claim 1, wherein the obtaining a dynamic parameter fluctuation adaptive model according to the multi-physical effect coupling simulation model and the mass production dynamic raw data comprises: obtaining a parameter fluctuation statistical feature set according to the mass production dynamic original data and the cross-correlation analysis; Training a gradient regression model according to the multi-physical effect coupling simulation model and the parameter fluctuation statistical feature set to obtain a mapping model; and obtaining the dynamic parameter fluctuation self-adaptive model according to the mapping model and a preset expansion mechanism.
6. The process window oriented lithography simulation and calibration method of claim 5, wherein said obtaining an actual measurement dataset from said dynamic parameter fluctuation adaptive model and said multi-physical effect coupling simulation model comprises: obtaining a sampling area dividing map according to the dynamic parameter fluctuation self-adaptive model and the multi-physical effect coupling simulation model; Performing layered sampling according to the sampling region division map to obtain an original measurement data set; Obtaining a complement measurement data set according to the original measurement data set and the Kriging interpolation formula; And performing self-adaptive filtering according to the complement measurement data set to obtain the actual measurement data set.
7. The method for lithography simulation and calibration for a process window according to claim 1, wherein said obtaining a lithography process optimal parameter combination from said measured dataset and said dynamic parameter fluctuation adaptive model comprises: Obtaining a calibrated dynamic parameter fluctuation self-adaptive simulation model according to the actual measurement data set and the dynamic parameter fluctuation self-adaptive model; Obtaining a pareto optimal solution set according to the calibrated dynamic parameter fluctuation self-adaptive simulation model and a process window optimization element set; And obtaining the optimal parameter combination of the photoetching process according to the pareto optimal solution set and the dynamic parameter fluctuation self-adaptive model.
8. The process window oriented lithography simulation and calibration method of claim 7, wherein said obtaining a calibrated dynamic parameter fluctuation adaptive simulation model from said measured dataset and said dynamic parameter fluctuation adaptive model comprises: Obtaining a quality simulation value and an actual measurement value according to the actual measurement data set and the dynamic parameter fluctuation self-adaptive model; Extracting diffraction integral coefficients and acid reaction rate constants in the dynamic parameter fluctuation adaptive model according to the quality simulation value and the actual measurement value to obtain a core coefficient set to be corrected of the model; And obtaining the calibrated dynamic parameter fluctuation self-adaptive simulation model according to the core coefficient set to be corrected of the model and the dynamic parameter fluctuation self-adaptive model.
9. The process window oriented lithography simulation and calibration method of claim 7, wherein said obtaining said lithography process optimal parameter combination from said pareto optimal solution set and said dynamic parameter fluctuation adaptive model comprises: obtaining an initial parameter combination according to the process window area and the defect rate in the pareto optimal solution set; Obtaining an imaging quality index value according to the initial parameter combination and the dynamic parameter fluctuation self-adaptive model; And obtaining the optimal parameter combination of the photoetching process according to the imaging quality index value and the hard constraint corresponding to the process window optimization element set.
10. A process window oriented lithography simulation and calibration system, comprising: The acquisition module is used for acquiring the basic parameters and the actually measured physical parameters of the photoetching process to obtain a standardized process physical parameter data set; The simulation module is used for obtaining a multi-physical effect coupling simulation model according to the standardized process physical parameter data set and a preset formula, wherein the preset formula comprises a Maxwell equation set and a Hopkins model; the dynamic adjustment module is used for obtaining a dynamic parameter fluctuation self-adaptive model according to the multi-physical effect coupling simulation model and the mass production dynamic original data; The data generation module is used for obtaining an actual measurement data set according to the dynamic parameter fluctuation self-adaptive model and the multi-physical effect coupling simulation model; And the calibration module is used for obtaining the optimal parameter combination of the photoetching process according to the actual measurement data set and the dynamic parameter fluctuation self-adaptive model.

Description

Photoetching simulation and calibration method and system for process window Technical Field The invention relates to the technical field of lithography simulation and calibration, in particular to a lithography simulation and calibration method and system for a process window. Background As semiconductor manufacturing process nodes continue to evolve toward advanced processes, photolithography processes have become a key element in chip patterning, and the robustness of the process window has become a key indicator in determining chip yield and reliability. The process window represents the allowable fluctuation range of core process parameters such as exposure dose, focal length, glue coating thickness and the like under the premise of meeting imaging quality hard constraints such as critical dimension, line edge roughness, edge placement error and the like, the wider the window is, the higher the tolerance of the process to mass production fluctuation is, the stronger the mass production stability is, the current traditional photoetching simulation and calibration method is mainly a static nominal model, the dynamic fluctuation and cooperative change of dimension parameters of equipment, process and wafer in mass production are difficult to adapt, the robustness verification of the process window is insufficient, the complex scenes such as extreme fluctuation, cooperative fluctuation, long-term drift and the like in mass production are difficult to be covered, and the optimized process parameters are easy to have yield fluctuation in actual mass production, so the prior art has the defects. Disclosure of Invention Aiming at the defects existing in the prior art, the invention aims to provide a photoetching simulation and calibration method and a photoetching simulation and calibration system for a process window, which are used for obtaining a dynamic parameter fluctuation self-adaptive model by producing dynamic original data on the basis of a multi-physical effect coupling simulation model, and optimizing the optimal parameter combination of the photoetching process by using the actual measurement data set-beam dynamic parameter fluctuation self-adaptive model, so that the final optimal parameter set of the photoetching process is properly matched with the requirement of robustness of the product parameter fluctuation. In order to achieve the above purpose, the present invention provides the following technical solutions: the invention provides a photoetching simulation and calibration method facing a process window, which comprises the following steps: obtaining basic parameters and actual measurement physical parameters of a photoetching process to obtain a standardized process physical parameter data set; obtaining a multi-physical effect coupling simulation model according to the standardized process physical parameter data set and a preset formula, wherein the preset formula comprises a Maxwell equation set and a Hopkins model; according to the multi-physical effect coupling simulation model and the mass production dynamic original data, a dynamic parameter fluctuation self-adaptive model is obtained; Obtaining an actual measurement data set according to the dynamic parameter fluctuation self-adaptive model and the multi-physical effect coupling simulation model; and obtaining the optimal parameter combination of the photoetching process according to the actually measured data set and the dynamic parameter fluctuation self-adaptive model. As a further improvement of the present invention, the obtaining a multi-physical effect coupling simulation model according to the standardized process physical parameter data set and a preset formula includes: According to the standardized technological physical parameter data set and the preset formula, the real light field distribution of the inherent light field attribute is contained; Obtaining multi-field coupling distribution data according to the real light field distribution containing the inherent attribute of the light field and different process conditions; And encrypting according to the multi-field coupling distribution data and the self-adaptive finite element grid to obtain the multi-physical effect coupling simulation model. As a further improvement of the present invention, the obtaining, according to the standardized process physical parameter data set and the preset formula, a real light field distribution including inherent light field attributes includes: Constructing a light field transmission model under partial coherent illumination according to the standardized technological physical parameter data set and the Hopkins model to obtain partial coherent characteristic distribution of the light field; obtaining vector electromagnetic field distribution according to the standardized process physical parameter data set and the Maxwell equation set; And obtaining the real light field distribution containing the inherent property of the light f