# US 11,307,240 B2 · Analysis method for semiconductor device

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- Number: US 11,307,240 B2
- Document ID: US11307240B2
- Status: Granted
- Kind: B2
- Application number: 16/828,991
- Filed: 2020-03-25
- Published: 2020-10-01
- Granted: 2022-04-19
- Earliest claimed: 2020-03-25
- Assignees: Shanghai Huali Integrated Circuit Mfg. Co. Ltd.
- Applicants: Shanghai Huali Integrated Circuit Mfg. Co., Ltd.
- Inventors: Ping-Hsun Su
- Web page: https://patentgrep.com/patent/US11307240B2

## CPC

- G01R 31/2621: {for testing field effect transistors, i.e. FET's}
- G06F 17/40: Data acquisition and logging (for input to computer G06F3/00)
- H10P 74/203: {Structural properties, e.g. testing or measuring thicknesses, line widths, warpage, bond strengths or physical defects}
- H10P 74/23: {characterised by multiple measurements, corrections, marking or sorting processes}
- Y02P 90/02: Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
- G01R: MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES (indicating correct tuning of resonant circuits H03J3/12)
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- H10P: GENERIC PROCESSES OR APPARATUS FOR THE MANUFACTURE OR TREATMENT OF DEVICES COVERED BY CLASS H10
- Y02P: CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS

## Abstract

The present disclosure provides an analysis method for a semiconductor device for analyzing a plurality of process parameters for manufacturing a HKMG fin field effect transistor. The analysis method specifically includes: establishing a plurality of process parameter models by grouping the plurality of process parameters in pairs; performing sensitivity analysis on each of the process parameter models; extracting a plurality of key process parameter models from the plurality of process parameter models based on the results of the sensitivity analysis; and performing data mining on the plurality of key process parameter models to determine a plurality of key process parameters and their correlations among the plurality of key process parameters. According to the analysis method provided by the present disclosure, related process parameters are highlighted by data mining and grouping, and the source of process parameter changes is explained. It is possible to adjust the process.

## Claims

### Claim 1

An analysis method for a semiconductor device for analyzing a plurality of process parameters for manufacturing an HKMG fin field effect transistor, wherein the analysis method comprises:
establishing a plurality of process parameter models by grouping the plurality of process parameters in pairs;
performing sensitivity analysis on each of the process parameter models;
extracting a plurality of key process parameter models from the plurality of process parameter models based on results of the sensitivity analysis; and
performing data mining on the plurality of key process parameter models to determine correlations among a plurality of key process parameters of the plurality of process parameters; and
determining one or more source process parameters and one or more subsequent process parameters in accordance with a sequence of manufacturing process, the one or more source process parameters being associated with the one or more subsequent process parameters;
wherein the plurality of key process parameters comprises a bottom-fin width, a fin height, a gate-spacer-1 thickness, a gate-spacer-2 thickness, an S/D depth, an S/D proximity, an HK/IL thickness, a gate height, and/or the gate length.

### Claim 2 (depends on 1)

The analysis method of claim 1, wherein performing the sensitivity analysis further comprises:
calculating a covariance of each of the process parameter models; and
calculating a correlation coefficient of each of the process parameter models based on the covariance.

### Claim 3 (depends on 2)

The analysis method of claim 2, wherein extracting the plurality of key process parameter models further comprises:
extracting from the plurality of process parameter models a process parameter model whose absolute value of the correlation coefficient is greater than a preset threshold as a key process parameter model.

### Claim 4 (depends on 2)

The analysis method of claim 2, wherein the performing the data mining further comprises:
performing the data mining based on correlation coefficients of the plurality of key process parameter models to determine correlations among the key process parameters.

### Claim 5 (depends on 4)

The analysis method of claim 4, wherein performing the data mining based on correlation coefficients of the plurality of key process parameter models further comprises:
establishing a correlation coefficient matrix of the plurality of key process parameter models by using the correlation coefficients of the plurality of key process parameter models as matrix elements; and
determining the correlations among the key process parameters based on the correlation coefficient matrix.

### Claim 6 (depends on 5)

The analysis method of claim 5, wherein determining the correlations among the key process parameters based on the correlation coefficient matrix further comprises:
performing agglomerative hierarchical clustering based on the correlation coefficient matrix.

### Claim 7 (depends on 5)

The analysis method of claim 5, wherein the correlation coefficient is a Pearson correlation coefficient, and the correlation coefficient matrix is a Pearson correlation coefficient matrix.

### Claim 8 (depends on 1)

The analysis method of claim 1, wherein establishing the plurality of process parameter models further comprises:
obtaining a plurality of specific values for each of the process parameters; and
establishing the plurality of process parameter models based on the plurality of process parameters and respective corresponding plurality of specific values.

### Claim 9 (depends on 1)

The analysis method of claim 1, wherein the analysis method further comprises:
determining source process parameters based on the correlations among the key process parameters; and
adjusting the source process parameters to optimize the plurality of process parameters.

### Claim 10 (depends on 1)

A computer apparatus comprising a memory, a processor and a computer program stored on the memory and operable on the processor, wherein the processor executes the computer program to perform the steps of the analysis method according to claim 1.

### Claim 11

An analysis method for a semiconductor device for analyzing a plurality of process parameters for manufacturing an HKMG fin field-effect transistor, wherein the analysis method comprises:
defining the plurality of process parameters and obtaining a structural size distribution of the HKMG fin field-effect transistor based on online testing;
establishing a plurality of process parameter models by grouping the plurality of process parameters in pairs;
performing sensitivity analysis on each of the process parameter models;
extracting a plurality of key process parameter models from the plurality of process parameter models based on results of the sensitivity analysis; and
performing data mining on the plurality of key process parameter models to determine correlations among a plurality of key process parameters of the plurality of process parameters; and
determining one or more source process parameters and one or more subsequent process parameters in accordance with a sequence of manufacturing process, the one or more source process parameters being associated with the one or more subsequent process parameters.

### Claim 12 (depends on 11)

The analysis method of claim 11, wherein the plurality of key process parameters comprises a bottom-fin width, a fin height, a gate-spacer-1 thickness, a gate-spacer-2 thickness, an S/D depth, an S/D proximity, an HK/IL thickness, a gate height, and/or the gate length.

### Claim 13 (depends on 12)

The analysis method of claim 12, wherein the bottom-fin width is associated with the fin height.

### Claim 14 (depends on 12)

The analysis method of claim 12, wherein the gate-spacer-1 thickness is associated with the gate-spacer-2 thickness.