Kla Tencor Corporation

Hari Pathangi Sriraman

Arun Lobo

Sivaprrasath Meenakshisundaram

A defect in an image of a semiconductor wafer can be classified as an initial defect type based on the pixels in the image. Critical dimension uniformity parameters associated with the defect type can be retrieved from an electronic data storage unit. A level of defectivity of the defect can be quantified based on the critical dimension uniformity parameters. Defects also can be classified based on critical dimension attributes, topography attributes, or contrast attributes to determine a final defect type.

Defect detection, classification, and process window control using scanning electron microscope metrology

Methods and systems for quantifying and correcting for non-uniformities in images used for metrology operations are disclosed. A metrology area image of a wafer and a design clip may be used. The metrology area image may be a scanning electron microscope image. The design clip may be the design clip of the wafer or a synthesized design clip. Tool distortions, including electron beam distortions, can be quantified and corrected. The design clip can be applied to the metrology area image to obtain a synthesized image such that one or more process change variations are suppressed and one or more tool distortions are enhanced.

Compensating for scanning electron microscope beam distortion-induced metrology error using design

A sample analysis system includes a scanning electron microscope, an optical and/or eBeam inspection system, and an optical metrology system. The system further includes at least one controller. The controller is configured to receive a first plurality of selected regions of interest of the sample; generate a first critical dimension uniformity map based on a first inspection performed by the scanning electron microscope at the first selected regions of interest; determine a second plurality of selected regions of interest based on the first critical dimension uniformity map; generate a second critical dimension uniformity map based on a second inspection performed by the optical and/or eBeam inspection system at the second selected regions of interest; and determine one or more process tool control parameters based on inspection results and on overlay measurements performed on the sample by the optical metrology system.

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Chennai, India

Hari Pathangi Sriraman