LAYERED THREE-WAY CONVERSION (TWC) CATALYST AND METHOD OF MANUFACURING THE CATALYST

    公开(公告)号:US20220055021A1

    公开(公告)日:2022-02-24

    申请号:US17309658

    申请日:2019-12-12

    Abstract: The presently claimed invention provides a layered three-way catalyst composition for purification of exhaust gases from internal combustion engines; said catalyst comprises a first layer comprising i) palladium supported on at least one alumina component and at least one oxygen storage component; and ii) barium oxide; wherein said first layer is essentially free of strontium, and a second layer comprising: i) rhodium supported on at least one zirconia component and/or alumina component; ii) strontium oxide and/or barium oxide; and iii) optionally, palladium supported on at least one alumina component. The presently claimed invention also provides a process for preparing the layered three-way catalyst composition which involves a technique such as incipient wetness impregnation technique(A); co-precipitation technique (B); or co-impregnation technique(C). The process includes preparing a first layer; preparing a second layer; and depositing the second layer on the first layer followed by calcination. The presently claimed invention further provides a a layered three-way catalytic article in which the three-way catalyst composition is deposited on a substrate in a layered fashion and its preparation.

    SYSTEMS, METHODS, AND COMPUTER-READABLE MEDIA FOR CHARACTERIZING MICROSPHERIC MATERIAL

    公开(公告)号:US20250014366A1

    公开(公告)日:2025-01-09

    申请号:US18577618

    申请日:2022-07-13

    Abstract: Methods, systems, and computer readable media are disclosed for characterizing the porosity of a microspheric material, training a classifier model for classifying spatially-contiguous image regions of backscatter electron scanning electron microscopy (BSE-SEM) images of a microspheric material according to the particle composition of the image regions, and characterizing the elemental composition of a microspheric material. The methods include: receiving image data representative of a microscopic images of a sample microspheric material; segmenting the image data into a plurality of spatially-contiguous image regions; classifying, by a trained machine-learning model, each of the plurality of spatially-contiguous image regions; and characterizing the microspheric material. The disclosure also relates to compositions for use as an FCC catalyst comprising microspheres which comprise alumina and/or clay and/or a zeolite.

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