Abstract:
X-ray imaging and classification of volume defects within a three-dimensional structure includes identifying one or more volume defects within a three-dimensional structure of a sample and acquiring, with a transmission-mode x-ray diffraction imaging tool, one or more coherent diffraction images of the one or more identified volume defects. The process includes classifying the one or more volume defects within a volume of the three-dimensional structure based on the one or more coherent diffraction images, and training an additional optical or electron-based inspection tool based on the one or more classified defects.
Abstract:
Disclosed are methods and apparatus for inspecting a vertical semiconductor stack of a plurality of layers is disclosed. The method includes (a) on a confocal tool, repeatedly focusing an illumination beam at a plurality of focus planes at a plurality of different depths of a first vertical stack, wherein a defect is located at an unknown one of the different depths and the illumination beam has a wavelength range between about 700 nm and about 950 nm, (b) generating a plurality of in-focus images for the different depths based on in-focus output light detected from the first vertical stack at the different depths, wherein out-of-focus output light is inhibited from reaching the detector of the confocal system and inhibited from contributing to generation of the in-focus images, and (c) determining which one of the different depths at which the defect is located in the first vertical stack based on the in-focus images.
Abstract:
Disclosed are methods and apparatus for inspecting a vertical memory stack. On an inspection tool, incident light having a first wavelength range is used to detect defects on a surface of the vertical memory stack. On the inspection tool, incident light having a second wavelength range is used to detect defects on both the surface and throughout a depth of the vertical memory stack. The defects detected using the first and second wavelength range are compared to detect defects only throughout the depth of the vertical memory stack, excluding defects on the surface, as well as to detect defects only on the surface.
Abstract:
Disclosed are methods and apparatus for inspecting semiconductor samples. On an inspection tool, a plurality of different wavelength ranges is selected for different layers of interest of one or more semiconductor samples based on whether such different layers of interest have an absorber type material present within or near such different layers of interest. On the inspection tool, at least one incident beam is directed at the different wavelength ranges towards the different layers of interest and, in response, output signals or images are obtained for each of the different layers of interest. The output signals or images from each of the different layers of interest are analyzed to detect defects in such different layers of interest.
Abstract:
Disclosed are methods and apparatus for inspecting a vertical semiconductor stack of a plurality of layers is disclosed. The method includes (a) on a confocal tool, repeatedly focusing an illumination beam at a plurality of focus planes at a plurality of different depths of a first vertical stack, wherein a defect is located at an unknown one of the different depths and the illumination beam has a wavelength range between about 700 nm and about 950 nm, (b) generating a plurality of in-focus images for the different depths based on in-focus output light detected from the first vertical stack at the different depths, wherein out-of-focus output light is inhibited from reaching the detector of the confocal system and inhibited from contributing to generation of the in-focus images, and (c) determining which one of the different depths at which the defect is located in the first vertical stack based on the in-focus images.
Abstract:
Disclosed are methods and apparatus for inspecting semiconductor samples. On an inspection tool, a plurality of different wavelength ranges is selected for different layers of interest of one or more semiconductor samples based on whether such different layers of interest have an absorber type material present within or near such different layers of interest. On the inspection tool, at least one incident beam is directed at the different wavelength ranges towards the different layers of interest and, in response, output signals or images are obtained for each of the different layers of interest. The output signals or images from each of the different layers of interest are analyzed to detect defects in such different layers of interest.
Abstract:
Various embodiments for using three-dimensional representations for defect-related applications are provided. One computer-implemented method for determining one or more inspection parameters for a wafer inspection recipe includes generating a three-dimensional representation of one or more layers of a wafer based on design data. The method also includes determining one or more inspection parameters for a wafer inspection recipe based on the three-dimensional representation.
Abstract:
Disclosed are methods and apparatus for inspecting a vertical memory stack. On an inspection tool, incident light having a first wavelength range is used to detect defects on a surface of the vertical memory stack. On the inspection tool, incident light having a second wavelength range is used to detect defects on both the surface and throughout a depth of the vertical memory stack. The defects detected using the first and second wavelength range are compared to detect defects only throughout the depth of the vertical memory stack, excluding defects on the surface, as well as to detect defects only on the surface.
Abstract:
Multi-spectral defect inspection for 3D wafers is provided. One system configured to detect defects in one or more structures formed on a wafer includes an illumination subsystem configured to direct light in discrete spectral bands to the one or more structures formed on the wafer. At least some of the discrete spectral bands are in the near infrared (NIR) wavelength range. Each of the discrete spectral bands has a bandpass that is less than 100 nm. The system also includes a detection subsystem configured to generate output responsive to light in the discrete spectral bands reflected from the one or more structures. In addition, the system includes a computer subsystem configured to detect defects in the one or more structures on the wafer using the output.
Abstract:
X-ray imaging and classification of volume defects within a three-dimensional structure includes identifying one or more volume defects within a three-dimensional structure of a sample and acquiring, with a transmission-mode x-ray diffraction imaging tool, one or more coherent diffraction images of the one or more identified volume defects. The process includes classifying the one or more volume defects within a volume of the three-dimensional structure based on the one or more coherent diffraction images, and training an additional optical or electron-based inspection tool based on the one or more classified defects.