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公开(公告)号:US20220113632A1
公开(公告)日:2022-04-14
申请号:US17431226
申请日:2020-02-07
Applicant: ASML NETHERLANDS B.V.
Abstract: A method for gauge selection for use in calibrating a process model associated with a patterning process. The method involves obtaining a set of initial gauges having one or more properties (e.g., gauge name, weight, dose, focus, model error, etc.) associated with the patterning process; and selecting a subset of initial gauges from the set of initial gauges, the selecting the subset of initial gauges including determining a first subset of gauges from the set of initial gauges based on a first property parameter of the one or more properties, the first subset of gauges being configured to calibrate a process model (e.g., optics model, resist mode., etc.).
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公开(公告)号:US20210048751A1
公开(公告)日:2021-02-18
申请号:US16977137
申请日:2019-03-07
Applicant: ASML NETHERLANDS B.V.
Inventor: Hongfei SHI , Jinze WANG , Pengcheng YANG , Lei WANG , Mu FENG
IPC: G03F7/20
Abstract: A method for accelerating calibration of a fabrication process model, the method including performing one or more iterations of: defining one or more fabrication process model terms; receiving predetermined information related to the one or more fabrication process model terms; generating a fabrication process model based on the predetermined information, the fabrication process model configured to generate one or more predictions related to a metrology gauge; determining whether a prediction related to a dimension of a gauge is within a predetermined threshold of the gauge as measured on a post-fabrication process substrate; and responsive to the prediction not breaching the predetermined threshold, optimizing the one or more fabrication process terms such that the prediction related to the dimension of the gauge is within the predetermined threshold of the gauge as measured on the post-fabrication process substrate.
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公开(公告)号:US20220276563A1
公开(公告)日:2022-09-01
申请号:US17625125
申请日:2020-06-15
Applicant: ASML NETHERLANDS B.V.
Inventor: Lei WANG , Yi- Yin CHEN , Mu FENG , Qian ZHAO
Abstract: Systems and methods for reducing prediction uncertainty in a prediction model associated with a patterning process are described. These may be used in calibrating a process model associated with the patterning process, for example. Reducing the uncertainty in the prediction model may include determining a prediction uncertainty parameter based on prediction data. The prediction data may be determined using the prediction model. The prediction model may have been calibrated with calibration data. The prediction uncertainty parameter may be associated with variation in the prediction data. Reducing the uncertainty in the prediction model may include selecting a subset of process data based on the prediction uncertainty parameter; and recalibrating the prediction model using the calibration data and the selected subset of the process data.
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