Reducing substrate surface scratching using machine learning

US11835927B2 · kind B2 · utility

Assignee

• Applied Materials, Inc. · US

Inventors

• Kartik Shah · Saratoga, US
• Satish Radhakrishnan · San Jose, US
• Karthik Ramanathan · Survanagiri, IN
• Karthikeyan Balaraman · Kanchinakote, IN
• Adolph Miller Allen · Oakland, US
• Xinyuan Chong · Santa Clara, US
• Mitrabhanu Sahu · San Jose, US
• Wenjing Xu · San Jose, US
• Michael S. Jackson · Sunnyvale, US
• Weize Hu · Sunnyvale, US
• Feng Chen · San Jose, US

Key dates

• Filing date: Dec 19, 2022
• Grant date: Dec 5, 2023
• Expiry date: Dec 19, 2042

Classification

• Technology area (CPC G): Physics
• CPC primary: G05B2219/45031
• WIPO field: Semiconductors
• WIPO sector: Electrical engineering

Abstract

Process recipe data associated a process to be performed for a substrate at a process chamber is provided as input to a trained machine learning model. A set of process recipe settings for the process that minimizes scratching on one or more surfaces of the substrate is determined based on one or more outputs of the machine learning model. The process is performed for the substrate at the process chamber in accordance with the determined set of process recipe settings.