Metrology and process control for semiconductor manufacturing

Patent metadata

Field	Value
Publication number	US-12236364-B2
Application number	US-202318369221-A
Country	US
Kind code	B2
Filing date	Sep 18, 2023
Priority date	Jun 14, 2018
Publication date	Feb 25, 2025
Grant date	Feb 25, 2025

Abstract

A semiconductor metrology system including a spectrum acquisition tool for collecting, using a first measurement protocol, baseline scatterometric spectra on first semiconductor wafer targets, and for various sources of spectral variability, variability sets of scatterometric spectra on second semiconductor wafer targets, the variability sets embodying the spectral variability, a reference metrology tool for collecting, using a second measurement protocol, parameter values of the first semiconductor wafer targets, and a training unit for training, using the collected spectra and values, a prediction model using machine learning and minimizing an associated loss function incorporating spectral variability terms, the prediction model for predicting values for production semiconductor wafer targets based on their spectra.

First claim

What is claimed is:

1. A high-volume manufacturing semiconductor process control metrology system comprising:
a plurality of spectrum acquisition integrated metrology (IM) tools configured to collect, in accordance with a first measurement protocol, a baseline set of scatterometric spectra;
at least one reference metrology tool configured to provide, in accordance with a second measurement protocol, values of predefined parameters of semiconductor wafer targets;
at least one web server layer connectable to said integrated metrology tools and said at least one reference metrology tool;
a big data layer configured for storing and processing data in a scalable and distributed manner; and
a training unit configured to create a training set of the data from the collected sets of spectra and said values of the predefined parameters.

2. The high-volume manufacturing semiconductor process control metrology system according to claim 1 , wherein said training unit configured to create said training set of the data from the collected sets of spectra and said values of the predefined parameters, use one or more generative models to increase the size of the training set of the data, and use the training set of the data to train a prediction model using machine learning.

3. The high-volume manufacturing semiconductor process control metrology system according to claim 2 , wherein any of the one or more generative models employs a predefined probability function that provides a probability distribution of the data in the training set, and generates new data examples using the predefined probability function, thereby increasing the size of the training set of the data.

4. The high-volume manufacturing semiconductor process control metrology system according to claim 3 , wherein the predefined probability function is explicitly stated.

5. The high-volume manufacturing semiconductor process control metrology system according to claim 2 , wherein any of the one or more generative models employs a predefined algorithm to determine statistics of the data in the training set and generating new data examples having the same statistics, thereby increasing the size of the training set of data.

6. The high-volume manufacturing semiconductor process control metrology system according to claim 5 , wherein any of the one or more generative models is a variational autoencoder.

7. The high-volume manufacturing semiconductor process control metrology system according to claim 5 , wherein any of the one or more generative models employs a generative adversarial network.

8. The high-volume manufacturing semiconductor process control metrology system according to claim 2 , further comprising inserting into the prediction model any information and constraints between different features of any of the one or more generative models that reflect underlying physics of the semiconductor wafer targets.

9. The high-volume manufacturing semiconductor process control metrology system according to claim 1 , wherein the predefined parameters relate to any of physical and chemical characteristics, material properties, electrical properties, and geometric properties of structures at the semiconductor wafer targets.

10. The high-volume manufacturing semiconductor process control metrology system according to claim 1 , wherein the at least one reference metrology tool is any of a Spectral Ellipsometer (SE), a Spectral Reflectometer (SR), a Polarized Spectral Reflectometer, and an Optical Critical Dimension (OCD) metrology tool.

11. The high-volume manufacturing semiconductor process control metrology system according to claim 1 , wherein the at least one reference metrology tool is any of a Critical Dimension Scanning Electron Microscope (CD-SEM), an Atomic Force Microscope (AFM), a cross-section Tunneling Electron Microscope (TEM), an electric metrology tool, a Critical Dimension Atomic Force Microscope (CD-AFM), an X-RAY metrology tool.

12. The high-volume manufacturing semiconductor process control metrology system according to claim 1 , wherein said integrated metrology (IM) tools configured as a normal incidence channel integrated tool.

13. The high-volume manufacturing semiconductor process control metrology system according to claim 10 , wherein said integrated metrology (IM) tools configured as a normal incidence channel integrated tool.

14. The high-volume manufacturing semiconductor process control metrology system according to claim 1 , wherein said integrated metrology (IM) tools are integrated with CMP tools.

15. The high-volume manufacturing semiconductor process control metrology system according to claim 14 , wherein said at least one reference metrology tool comprises multichannel Optical Critical Dimension (OCD) metrology tool.

16. The high-volume manufacturing semiconductor process control metrology system according to claim 1 , wherein said at least one reference metrology tool comprises multichannel Optical Critical Dimension (OCD) metrology tool.

17. The high-volume manufacturing semiconductor process control metrology system according to claim 1 , wherein said at least one reference metrology tool obtains the values of the predefined parameters of the semiconductor wafer targets using RCWA interpretation.

18. The high-volume manufacturing semiconductor process control metrology system according to claim 1 , wherein the first measurement protocol and the second measurement protocol differ in any of numbers of channels, illumination angles, targets, and signals acquired from the same target.

Assignees

• Nova Ltd

Inventors

• Rothstein Eitan
• Rubinovich Ilya
• Tal Noam
• Bringoltz Barak
• Kim Yongha
• Broitman Ariel
• Cohen Oded
• Rabinovich Eylon
• Zaharoni Tal
• Yogev Shay
• Kandel Daniel

Classifications

• H10P74/238

  comprising acting in response to an ongoing measurement without interruption of processing, e.g. endpoint detection or in-situ thickness measurement · CPC title

• H10P72/53

  using optical controlling means · CPC title

• G03F7/70616 Primary

  Monitoring the printed patterns · CPC title

• G03F7/705 Primary

  Modelling or simulating from physical phenomena up to complete wafer processes or whole workflow in wafer productions · CPC title

• G01B2210/56

  Measuring geometric parameters of semiconductor structures, e.g. profile, critical dimensions or trench depth · CPC title