Applied Materials had 102 patents in artificial intelligence during Q4 2023. The patents filed by Applied Materials Inc in Q4 2023 focus on various aspects of semiconductor manufacturing processes. These include methods to relieve stress on substrates in 3D stacked electronic assemblies, utilizing deep learning models for accurate alignment of patterned layers in lithography processes, optimizing inspection recipes for semiconductor specimens using machine learning models, diagnosing and correcting alignment issues in processing chambers using non-contact sensors, and adjusting operating parameters of semiconductor processing stations to improve thickness uniformity of deposited materials. GlobalData’s report on Applied Materials gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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Applied Materials grant share with artificial intelligence as a theme is 30% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Substrate frame design for three-dimensional stacked electronic assemblies (Patent ID: US20230420351A1)
The patent filed by Applied Materials Inc. describes a method and system for reducing stress on substrates in a 3D stacked electronic assembly by dividing the substrate frame into sections separated by spaces. These separations allow for expansion and contraction of the substrates in response to environmental conditions, with the spaces strategically placed to align with areas of maximal warpage caused by the placement of IC packages. By reducing stress on the substrates, the system aims to improve the overall reliability and performance of the electronic assembly.
The claims outline the specific components and configurations of the 3D stacked electronic assembly, including the printed circuit board, package substrate, IC packages, and substrate frame. The method of assembly involves mounting IC packages to a substrate, connecting a substrate frame between substrates, and identifying areas of warpage on the substrate. The system also includes a machine-learning model to determine optimal locations for the spaces between frame sections based on the placement of IC packages. Overall, the patent focuses on addressing the challenges of stress and warpage in 3D stacked electronic assemblies through innovative design and placement strategies.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
