Entegris had eight patents in 3D printing during Q2 2024. Entegris Inc’s patents filed in Q2 2024 focus on a feedstock composition with inorganic particles of varying sizes and a binder composition for forming shaped bodies with low porosity. Additionally, the patents describe porous sintered bodies and methods for making them using additive manufacturing techniques. GlobalData’s report on Entegris gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Entegris had no grants in 3D printing as a theme in Q2 2024.
Recent Patents
Application: Particle compositions and related methods and uses to form sintered silicon carbide bodies (Patent ID: US20240139993A1)
The patent filed by Entegris Inc. describes a feedstock composition for forming shaped bodies and low porosity inorganic sintered bodies. The composition includes inorganic particles with a multi-modal particle size distribution, consisting of irregular fine particles and coarse particles with specific average diameters. The binder composition solidifies to form a body with the inorganic particles. The method involves forming a shaped body by using the feedstock composition and solidified binder, with the option of additive manufacturing for shaping the precursor body.
The composition's inorganic particles have a packing density of at least 60 percent, with specific standard deviations for fine and coarse particle size distributions. The feedstock composition includes a specific weight percentage of fine and coarse particles, typically silicon carbide particles. The method further details the formation of low porosity inorganic sintered bodies by heating the precursor body to fuse the particles together. The resulting sintered body has a porosity below 5 percent and comprises a high percentage of silicon carbide, with a packing density of at least 60 percent. Overall, the patent outlines a precise composition and method for creating shaped bodies and low porosity inorganic sintered bodies using a unique feedstock composition.
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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.
