Artificial intelligence-enabled preparation end-pointing
AssigneeFEI Company
InventorsThomas Gary Miller, John F. Flanagan, IV, Brian Routh, JR., Richard Young, Brad Larson, Aditee Shrotre
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Abstract
Methods and systems for implementing artificial intelligence enabled preparation end-pointing are disclosed. An example method at least includes obtaining an image of a surface of a sample, the sample including a plurality of features, analyzing the image to determine whether an end point has been reached, the end point based on a feature of interest out of the plurality of features observable in the image, and based on the end point not being reached, removing a layer of material from the surface of the sample.
Claims22
A method comprising:
- obtaining, by a charged particle beam, an image of a surface of a sample, the sample including a plurality of features;
- analyzing, by a machine learning system, the image to determine whether an end point has been reached, the end point based on a feature of interest out of the plurality of features observable in the image;
- and
- based on the end point not being reached, removing a layer of material from the surface of the sample.
A charged particle microscope system for processing samples, the system comprising:
- an ion column to provide a focused ion beam;
- an electron column to provide an electron beam;
- and
- a controller including code that, when executed, causes the charged particle microscope to:
- obtain, by the electron beam, an image of a surface of a sample, the sample including a plurality of features;
- analyze, by a machine learning system, the image to determine whether an end point has been reached, the end point based on a feature of interest out of the plurality of features observable in the image;
- based on the end point not being reached, milling, by the focused ion beam, the surface of the sample to remove a layer of material;
- and
- based on the end point being reached, cease material removal.
Dependencies are inferred from the claim text.