Abstract: Described are compositions (e.g., slurries) useful in methods for chemical-mechanical processing (e.g. polishing or planarizing) a surface of a substrate that contains tungsten, the slurries containing abrasive particles, metal cation catalyst, phosphorus-containing zwitterionic compound, and optional ingredients such as oxidizer; also described are methods and substrates used or processed on combination with the compositions.

Abstract: Described are compositions (e.g., slurries) useful in methods for chemical-mechanical processing (e.g. polishing or planarizing) a surface of a substrate that contains tungsten, the slurries containing abrasive particles, metal cation catalyst, phosphorus-containing zwitterionic compound, and optional ingredients such as oxidizer; also described are methods and substrates used or processed on combination with the compositions.

Abstract: A method for near real time patterns identification, in one example embodiment, comprises receiving a data stream containing information associated with a transaction and participants of the transaction and receiving an Artificial Intelligence (AI) algorithm trained to score data in the data stream. The method may further comprise receiving metadata associated with the historical information, comparing the data stream to the metadata by measuring differences between variables included in the historical metadata and the data stream. The method may further comprise modifying the data stream to suit the AI algorithm when the differences between variables are below predetermined threshold values and retraining the AI algorithm based on the data stream when the differences between the variables are greater than the predetermined threshold values. The method may further comprise feeding the data stream to the AI algorithm to classify the variables in the data stream.

Abstract: A method for near real time patterns identification, in one example embodiment, comprises receiving a data stream containing information associated with a transaction and participants of the transaction and receiving an Artificial Intelligence (AI) algorithm trained to score data in the data stream. The method may further comprise receiving metadata associated with the historical information, comparing the data stream to the metadata by measuring differences between variables included in the historical metadata and the data stream. The method may further comprise modifying the data stream to suit the AI algorithm when the differences between variables are below predetermined threshold values and retraining the AI algorithm based on the data stream when the differences between the variables are greater than the predetermined threshold values. The method may further comprise feeding the data stream to the AI algorithm to classify the variables in the data stream.