METHOD FOR FABRICATING ELECTRODE BASED ON LIQUID METAL

    公开(公告)号:US20230292582A1

    公开(公告)日:2023-09-14

    申请号:US17795154

    申请日:2021-07-27

    CPC classification number: H01L51/0022 H01L51/0023 H01L2251/301

    Abstract: The present invention relates to a liquid metal based fabrication method, and the method for fabricating an electrode based on a liquid metal, according to the present invention, comprises the steps of: preparing a first substrate having a self-assembled monolayer (SAM) on one surface thereof; and printing a liquid metal in a predetermined pattern to be in contact with the surface of the self-assembled monolayer by using a printing device including a needle from which the liquid metal is discharged, and a controller for controlling the movement of the needle, thereby forming a liquid metal electrode.

    METHOD OF OBTAINING AND IMPUTING MISSING DATA AND MEASUREMENT SYSTEM USING THE SAME

    公开(公告)号:US20230214371A1

    公开(公告)日:2023-07-06

    申请号:US18149991

    申请日:2023-01-04

    CPC classification number: G06F16/215 G06F16/2462

    Abstract: A method of obtaining and imputing missing data and a measurement system having the same are disclosed. The method. includes obtaining measurement values of measurement variables, among z variables corresponding to z components of a measurement object, wherein z is a natural number greater than 1, and the z variables of the measurement object include measurement variables and missing variables which are not measured, and the measurement variables are of an amount less than z; generating missing data having the measurement variables with the measurement values and the missing variables with missing values in the z components, wherein each of the missing values is predetermined value indicating that a missing variable has not been measured; generating k pieces of final imputation data having k final imputation values, by using the missing data, wherein k is a natural number greater than 1, each of the k final imputation values are in the z components, sing the missing data includes performing multiple imputations on the missing data; and generating average data having average component values in the z components, wherein each of the average component values in a component is an average value of the k final imputation values of the k pieces of final imputation data in the component, and selecting, in each of the z components, a next measurement variable, wherein a difference value between a final imputation values and an average component value, of the next measurement variable, is larger than a difference value of the missing variables.

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