# US 10,502,692 B2 · Automated metrology system selection

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- Number: US 10,502,692 B2
- Document ID: US10502692B2
- Status: Granted
- Kind: B2
- Application number: 15/166,897
- Filed: 2016-05-27
- Published: 2017-01-26
- Granted: 2019-12-10
- Earliest claimed: 2015-07-24
- Assignees: KLA-Tencor Corporation
- Applicants: KLA-Tencor Corporation
- Inventors: Meng Cao; Lie-Quan Lee; Qiang Zhao; Heyin Li; Mengmeng Ye
- Web page: https://patentgrep.com/patent/US10502692B2

## CPC

- G01N 21/9501: {Semiconductor wafers (manufacturing processes per se of semiconductor devices implementing a measuring step H10P74/20)}
- G01N 21/211: {Ellipsometry (optical thickness measurement G01B11/06)}
- G03F 7/70625: {Dimensions, e.g. line width, critical dimension [CD], profile, sidewall angle or edge roughness}
- G03F 7/70633: {Overlay, i.e. relative alignment between patterns printed by separate exposures in different layers, or in the same layer in multiple exposures or stitching}
- G01B 21/04: by measuring coordinates of points
- G01B 2210/56: Measuring geometric parameters of semiconductor structures, e.g. profile, critical dimensions or trench depth
- G01N 2021/213: {Spectrometric ellipsometry}
- G03F 7/705: {Modelling or simulating from physical phenomena up to complete wafer processes or whole workflow in wafer productions}
- G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q)
- G03F: PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR; (phototypographic composing devices B41B; photosensitive materials or processes for photographic purposes G03C; electrophotography, sensitive layers or processes therefor G03G)
- G01B: MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS

## Abstract

Methods and systems for evaluating and ranking the measurement efficacy of multiple sets of measurement system combinations and recipes for a particular metrology application are presented herein. Measurement efficacy is based on estimates of measurement precision, measurement accuracy, correlation to a reference measurement, measurement time, or any combination thereof. The automated the selection of measurement system combinations and recipes reduces time to measurement and improves measurement results. Measurement efficacy is quantified by a set of measurement performance metrics associated with each measurement system and recipe. In one example, the sets of measurement system combinations and recipes most capable of measuring the desired parameter of interest are presented to the user in rank order based on corresponding values of one or more measurement performance metrics. A user is able to select the appropriate measurement system combination in an objective, quantitative manner.

## Claims

### Claim 1

A metrology system comprising:
one or more computer systems configured to:
receive a measurement model indicative of a measurement of a parameter of interest by a metrology system at a plurality of measurement scenarios, wherein each of the plurality of measurement scenarios includes different values of an angle of incidence, azimuth angle, illumination wavelength, polarization state, or any combination thereof;
determine a subset of the plurality of measurement scenarios that increases a reliability and sensitivity of the measurement to the parameter of interest;
determine a set of Design of Experiments (DOE) measurement data associated with a simulation of the measurement for a range of known values of the parameter of interest and the subset of the plurality of measurement scenarios;
estimate values of the parameter of interest by solving a measurement model on the set of DOE measurement data corresponding to each of the known values of the parameter of interest;
determine one or more indications of a difference between the known values of the parameter of interest and the estimated values of the parameter of interest;
determine one or more measurement performance metrics indicative of the measurement performance of one or more of the subset of the plurality of measurement scenarios based on the indications of the difference between the known values and the estimated values of the parameter of interest;
communicate the measurement performance metrics to a user;
receive an indication of a selection of a measurement scenario by the user;
generate a measurement system configuration based on the selection; and
an illumination source configured to provide an amount of illumination light to one or more metrology targets in accordance with the measurement system configuration; and
a detector configured to receive an amount of collected light from the one or more metrology targets in response to the amount of illumination light in accordance with the measurement system configuration.

### Claim 2 (depends on 1)

The metrology system of claim 1, wherein the determining the subset of the plurality of measurement scenarios that increases the reliability and sensitivity of the measurement involves eliminating one or more measurement scenarios that result in a discontinuity in a measurement signal response for one or more values of the parameter of interest.

### Claim 3 (depends on 1)

The metrology system of claim 1, wherein the determining the subset of the plurality of measurement scenarios that increases the reliability and sensitivity of the measurement involves eliminating one or more measurement scenarios that result in a discontinuity of a derivative of a measurement signal response for one or more values of the parameter of interest.

### Claim 4 (depends on 1)

The metrology system of claim 1, wherein the determining the subset of the plurality of measurement scenarios that increases the reliability and sensitivity of the measurement involves fitting a polynomial function to a first derivative of a measurement signal response with respect to a parameter of interest at a set of wavelengths, and excluding measurement signals corresponding to a particular wavelength range if a quality of fit is less than a predetermined threshold value over the particular wavelength range.

### Claim 5 (depends on 1)

The metrology system of claim 1, wherein the one or more measurement performance metrics comprise an overall R-score value that is a weighted sum of R-score values associated with each known value of the parameter of interest.

### Claim 6 (depends on 1)

The metrology system of claim 1, wherein the one or more measurement performance metrics comprise an overall measurability value that is a product of measurability values associated with each known value of the parameter of interest.

### Claim 7 (depends on 5)

The metrology system of claim 5, wherein the one or more measurement performance metrics comprise an overall T-score value that is a weighted sum of T-score values associated with each known value of the parameter of interest, wherein each of the T-score values is a product of the R-score value corresponding to each measurement scenario of the one or more of the subset of the plurality of measurement scenarios and a corresponding indication of a measurement time associated with each measurement scenario.

### Claim 8 (depends on 1)

The metrology system of claim 1, wherein the illumination source and the detector are elements of any of a spectroscopic ellipsometer, a spectroscopic reflectometer, a single wavelength ellipsometer, and a beam profile reflectometer.

### Claim 9

An automated measurability ranking tool comprising computer-readable instructions stored on a non-transitory, computer-readable medium, the computer-readable instructions comprising:
code for causing a computing system to receive a measurement model indicative of a measurement of a parameter of interest by a metrology system at a plurality of measurement scenarios, wherein each of the plurality of measurement scenarios includes different values of an angle of incidence, azimuth angle, illumination wavelength, polarization state, or any combination thereof;
code for causing the computing system to determine a subset of the plurality of measurement scenarios that increases a reliability and sensitivity of the measurement to the parameter of interest;
code for causing the computing system to determine a set of Design of Experiments (DOE) measurement data associated with a simulation of the measurement for a range of known values of the parameter of interest and the subset of the plurality of measurement scenarios;
code for causing the computing system to estimate values of the parameter of interest by solving a measurement model on the set of DOE measurement data corresponding to each of the known values of the parameter of interest;
code for causing the computing system to determine one or more indications of a difference between the known values of the parameter of interest and the estimated values of the parameter of interest;
code for causing the computing system to determine one or more measurement performance metrics indicative of the measurement performance of one or more of the subset of the plurality of measurement scenarios based on the indications of the difference between the known values and the estimated values of the parameter of interest;
code for causing the computing system to communicate the measurement performance metrics to a user;
code for causing the computing system to receive an indication of a selection of a measurement scenario by the user;
code for causing the computing system to generate a measurement system configuration based on the selection; and
code for causing the computing system to perform a measurement based on the measurement system configuration.

### Claim 10 (depends on 9)

The automated measurability ranking tool of claim 9, wherein the determining the subset of the plurality of measurement scenarios that increases the reliability and sensitivity of the measurement involves eliminating one or more measurement scenarios that result in a discontinuity in a measurement signal response for one or more values of the parameter of interest.

### Claim 11 (depends on 9)

The automated measurability ranking tool of claim 9, wherein the determining the subset of the plurality of measurement scenarios that increases the reliability and sensitivity of the measurement involves eliminating one or more measurement scenarios that result in a discontinuity of a derivative of measurement signal response for one or more values of the parameter of interest.

### Claim 12 (depends on 9)

The automated measurability ranking tool of claim 9, wherein the determining the subset of the plurality of measurement scenarios that increases the reliability and sensitivity of the measurement involves fitting a polynomial function to a first derivative of a measurement signal response with respect to a parameter of interest at a set of wavelengths, and excluding measurement signals corresponding to a particular wavelength range if a quality of fit is less than a predetermined threshold value over the particular wavelength range.

### Claim 13 (depends on 9)

The automated measurability ranking tool of claim 9, wherein the one or more measurement performance metrics comprise an overall R-score value that is a weighted sum of R-score values associated with each known value of the parameter of interest.

### Claim 14 (depends on 9)

The automated measurability ranking tool of claim 9, wherein the one or more measurement performance metrics comprise an overall measurability value that is a product of measurability values associated with each known value of the parameter of interest.

### Claim 15 (depends on 13)

The automated measurability ranking tool of claim 13, wherein the one or more measurement performance metrics comprise an overall T-score value that is a weighted sum of T-score values associated with each known value of the parameter of interest, wherein each of the T-score values is a product of the R-score value corresponding to each measurement scenario of the one or more of the subset of the plurality of measurement scenarios and a corresponding indication of a measurement time associated with each measurement scenario.

### Claim 16

A method comprising:
receiving a measurement model indicative of a measurement of a parameter of interest by a metrology system at a plurality of measurement scenarios, wherein each of the plurality of measurement scenarios includes different values of an angle of incidence, azimuth angle, illumination wavelength, polarization state, or any combination thereof;
determining a subset of the plurality of measurement scenarios that increases a reliability and sensitivity of the measurement to the parameter of interest;
determining a set of Design of Experiments (DOE) measurement data associated with a simulation of the measurement for a range of known values of the parameter of interest and the subset of the plurality of measurement scenarios;
estimating values of the parameter of interest by solving a measurement model on the set of DOE measurement data corresponding to each of the known values of the parameter of interest;
determining one or more indications of a difference between the known values of the parameter of interest and the estimated values of the parameter of interest;
determining one or more measurement performance metrics indicative of the measurement performance of one or more of the subset of the plurality of measurement scenarios based on the indications of the difference between the known values and the estimated values of the parameter of interest;
communicating the measurement performance metrics to a user;
receiving an indication of a selection of a measurement scenario by the user;
generating a measurement system configuration based on the selection; and
performing a measurement based on the measurement system configuration.

### Claim 17 (depends on 16)

The method of claim 16, wherein the determining the subset of the plurality of measurement scenarios that increases the reliability and sensitivity of the measurement involves eliminating one or more measurement scenarios that result in a discontinuity in a measurement signal response for one or more values of the parameter of interest.

### Claim 18 (depends on 16)

The method of claim 16, wherein the determining the subset of the plurality of measurement scenarios that increases the reliability and sensitivity of the measurement involves eliminating one or more measurement scenarios that result in a discontinuity of a derivative of measurement signal response for one or more values of the parameter of interest.

### Claim 19 (depends on 16)

The method of claim 16, wherein the one or more measurement performance metrics comprise an overall R-score value that is a weighted sum of R-score values associated with each known value of the parameter of interest.

### Claim 20 (depends on 16)

The method of claim 16, wherein the one or more measurement performance metrics comprise an overall measurability value that is a product of measurability values associated with each known value of the parameter of interest.

### Claim 21 (depends on 19)

The method of claim 19, wherein the one or more measurement performance metrics comprise an overall T-score value that is a weighted sum of T-score values associated with each known value of the parameter of interest, wherein each of the T-score values is a product of the R-score value corresponding to each measurement scenario of the one or more of the subset of the plurality of measurement scenarios and a corresponding indication of a measurement time associated with each measurement scenario.

### Claim 22 (depends on 16)

The method of claim 16, wherein the metrology system is any of a spectroscopic ellipsometer, a spectroscopic reflectometer, a single wavelength ellipsometer, and a beam profile reflectometer.