Wafer Calibration Data Generation for Localization Accuracy
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Solution Overview
Problem
Semiconductor manufacturing processes face challenges in achieving high localization accuracy for pattern analysis on wafers due to temporal physical effects and imperfections such as mechanical vibrations, thermal fluctuations, and misalignments, which affect the precision of inspection and metrology systems.
Innovation Solution
A computer-implemented method and system for generating calibration data that involves identifying targets in an image frame, computing their displacements relative to reference data, determining coordinate transformation parameters, and using these parameters to create displacement mappings, which account for global shifts, linear scaling, and rotations to improve localization accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a movable stage is used to translate the inspected sample relative to the imaging apparatus to cover large areas, then the field-of-view coverage is improved, but mechanical vibrations and thermal fluctuations cause misalignment and reduce localization accuracy
Solution Approach 1:
The system performs preliminary calibration by identifying targets in both the image frame and reference data, computing their displacements, and determining coordinate transformation parameters before actual inspection. This preliminary action establishes a displacement mapping that compensates for mechanical vibrations and thermal fluctuations during subsequent large-area scanning operations
Solution Approach 2:
The system continuously monitors target positions in the image frame against reference data, computes displacements in real-time, and updates coordinate transformation parameters to compensate for ongoing mechanical vibrations and thermal drift. This feedback loop maintains localization accuracy despite stage movement and environmental changes
2Manufacturing precision
If design rules shrink to analyze smaller structures, then the resolution is improved, but temporal physical effects and imperfections adversely impact localization accuracy more significantly
Solution Approach 1:
The system introduces targets as intermediary reference objects that are easily detectable and serve as mediators between the imaging system and the small structures being inspected. By tracking target displacements and computing coordinate transformation parameters, the system creates a reference framework that maintains localization accuracy even when analyzing sub-micron features affected by thermal and mechanical perturbations
3Productivity
If the stage moves at high speed to increase throughput, then productivity is improved, but mechanical vibrations and acceleration induce additional errors in localization
Solution Approach 1:
The system implements real-time feedback by continuously identifying targets, computing displacements, and updating coordinate transformation parameters during high-speed scanning. This allows the system to compensate for vibrations and acceleration errors that occur during rapid stage movement, maintaining localization accuracy while achieving high throughput
Data Source
AI summary
Disclosed herein is a computer-implemented method for generating calibration data usable for analysis of a sample. The method includes: (i) identifying targets in an image frame pertaining to a scanned area of a sample; (ii) computing displacements of the targets relative to positions thereof as given by, or derived from, reference data of the scanned area; (iii) based at least on the computed target displacements, determining values of coordinate transformation parameters (CTPs) relating coordinates of the image frame to coordinates of the scanned area as given by, or derived from, the reference data; and (iv) using at least the CTPs to obtain displacements of multiple segments in the image frame, thereby generating a displacement mapping of the image frame or at least a part thereof.