Measuring local CD uniformity using scatterometry and machine learning

US12165023B2 · kind B2 · utility

Assignees

• NOVA LTD. · IL
• International Business Machines Corporation · US

Inventors

• Dexin Kong · Guilderland, US
• Daniel Schmidt · Niskayuna, US
• Aron Cepler · Albany, US
• Marjorie Cheng · Armonk, US
• Roy Koret · Albany, US
• Igor Turovets · Mevaseret Tsiyon, IL

Key dates

• Filing date: Feb 23, 2021
• Grant date: Dec 10, 2024
• Expiry date: Feb 23, 2041

Classification

• Technology area (CPC G): Physics
• CPC primary: G01J3/28
• WIPO field: Measurement
• WIPO sector: Instruments

Abstract

A method, a system, and a non-transitory computer readable medium for measuring a local critical dimension uniformity of an array of two-dimensional structural elements, the method may include obtaining an acquired optical spectrometry spectrum of the array; feeding the acquired optical spectrometry spectrum of the array to a trained machine learning process, wherein the trained machine learning process is trained to map an optical spectrometry spectrum to an average critical dimension (CD) and a local critical dimension uniformity (LCDU); and outputting, by the trained machine learning process, the average CD and the LCDU of the array.