Dosage-controlled voltage contrast inspection in charged-particle beam systems and methods thereof

IL330823APending Publication Date: 2026-09-01ASML NETHERLANDS BV
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Patent Information

Application Number
IL330823
Authority / Receiving Office
IL · IL
Patent Type
Applications
Current Assignee / Owner
Priority Date
2024-01-29
Filing Date
2025-01-06
Publication Date
2026-09-01

AI Technical Summary

Technical Problem

Existing voltage contrast inspection techniques in charged-particle beam systems suffer from low defect sensitivity, particularly in detecting high-resistance defects, and are inadequate in classifying defect types, impacting defect capture rate and inspection throughput in complex integrated circuit manufacturing.

Method used

A method involving incremental dosage of charged particles to switch the polarity of a sample region, forming inspection images based on gray level values to detect and classify defects, using a charged-particle beam apparatus.

Benefits of technology

Enhances defect detection sensitivity and classification accuracy, allowing for precise identification of defect types and locations in layered or stacked structures, improving inspection efficiency and throughput.

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Abstract

Systems and methods (400; 700) of detecting a defect (638) in a sample (250) using a charged-particle beam apparatus are disclosed. A method (400; 700) for inspecting a sample (250) using a charged-particle beam apparatus includes causing a region of the sample (250) comprising a plurality of features (632) to be charged to a first polarity, causing the region to switch from the first polarity to a second polarity at a switching condition, the switching condition comprising a switching dosage of primary charged particles, forming an inspection image of the region from signal charged particles generated upon interaction of the switching dosage of primary charged particles with the plurality of features (632), and determining whether a feature (632) of the plurality of features (632) is defective based on a gray level value of the feature (632) in the inspection image.
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