Abstract: A thickness prediction network learning method includes measuring spectrums of optical characteristics of a plurality of semiconductor structures each including a substrate and first and second semiconductor material layers alternately stacked thereon to generate sets of spectrum measurement data, measuring thicknesses of the first and second semiconductor material layers to generate sets of thickness data, training a simulation network using the sets of spectrum measurement data and the sets of thickness data, generating sets of spectrum simulation data of spectrums of the optical characteristics of a plurality of virtual semiconductor structures based on thicknesses of first and second virtual semiconductor material layers using the simulation network, each of the first and second virtual semiconductor layers including the same material as the first and second semiconductor material layers, respectively; and training a thickness prediction network by using the sets of spectrum measurement data and the sets

Abstract: A method of manufacturing a semiconductor device includes forming a plurality of overlay molds on a semiconductor structure by developing a photoresist material layer of the semiconductor structure, the semiconductor structure including a first layer having a plurality of overlay marks, the plurality of overlay molds at least partially overlapping at least some of the plurality of overlay marks; and measuring one or more overlays by radiating a light having a wavelength band onto the semiconductor structure, each of the one or more overlays indicating an amount of consistency of the first layer and a second layer of the semiconductor structure, the wavelength band being set based on the plurality of overlay marks and the plurality of overlay molds, the second layer being between the first layer and the photoresist material layer.

Abstract: Provided are a method of inspecting a surface and a method of manufacturing a semiconductor device. The methods include preparing a substrate, selecting a spatial resolution of a first optical device by setting a magnification of an imaging optical system, emitting multi-wavelength light toward a first measurement area of the substrate and obtaining first wavelength-specific images, generating first spectrum data based on the first wavelength-specific images, generating first spectrum data of respective pixels based on the first wavelength-specific images, and extracting a spectrum of at least one first inspection area having a range of the first measurement area or less from the first spectrum data, and analyzing the spectrum. The first optical device includes a light source, an objective lens, a detector, and an imaging optical system. The obtaining first wavelength-specific images includes using the imaging optical system and the detector.

Abstract: Provided is a hyperspectral imaging (HSI)-based inspection apparatus capable of quickly and stably performing two-dimensional (2D) HSI for an inspection object, and accordingly, capable of quickly and accurately inspecting the inspection object. The HSI-based inspection apparatus includes: a stage on which an inspection object is arranged; an optical system configured to allow light to be incident on the inspection object and emit the light reflected from the inspection object; a scan mirror configured to reflect the emitted light from the optical system while rotating; and a hyperspectral camera configured to obtain an image having a wavelength direction and a line direction as two axes for light reflected from the scan mirror, wherein, by using the rotation of the scan mirror, the hyperspectral camera is configured to perform the 2D HSI for the inspection object.

Abstract: A semiconductor pattern detecting apparatus is provided.

Abstract: A method for nondestructive measurement of an underlying layer thickness includes irradiating, with a pump laser pulse, a sample to induce generation of an acoustic wave in the sample such that the acoustic wave propagates through the sample over time, where the sample includes a substrate, an underlying layer on the substrate, and an overlying layer on the underlying layer and the underlying layer is isolated from an exterior of the sample by at least the overlying layer, irradiating the sample with a probe laser pulse after irradiating the sample with the pump laser pulse, determining a reflectance variation of the sample over time, based on monitoring a variation of a reflection of the probe laser pulse from the sample over time, to generate a first graph showing a variation of reflectance of the sample over time, and determining a thickness of the underlying layer based on the first graph.

Abstract: Provided is a method of inspecting a pattern defect. The method includes: applying a voltage to an object to be inspected and measuring an inspection signal generated in a pattern of the object to be inspected due to the voltage applied to the object to be inspected over time; generating an intensity image showing a relationship between an intensity of the inspection signal measured in the pattern and a time by processing the inspection signal; and detecting a pattern defect position by comparing the intensity image with a comparative intensity image.

Abstract: Provided are a multilayer structure inspection apparatus and method of inspecting a multilayer structure in a sample without damaging the sample, the multilayer structure inspection apparatus being configured to measure both of reflectance and dispersion without damaging the sample, wherein the reflectance and dispersion are variables which are changed sensitively to a change in a repetitive pattern of the multilayer structure, by measuring values thereof, a structural change of the sample between before and after a process is inspected with high accuracy.

Abstract: An apparatus for X-ray inspection is provided. The apparatus includes: a stage on which an inspection target is loaded, the stage including a first surface and an opposite second surface; an X-ray generator disposed on or over the first surface of the inspection target and configured to irradiate the inspection target with incident X-rays; and a detection system disposed on or under the second surface of the inspection target and configured to detect first transmitted X-rays transmitted through the inspection target. The detection unit includes a first lens system and a second lens system. The first transmitted X-rays pass through one of the first lens system and the second lens system. The second lens system includes a micro zone plate.

Abstract: A method for nondestructive measurement of an underlying layer thickness includes irradiating, with a pump laser pulse, a sample to induce generation of an acoustic wave in the sample such that the acoustic wave propagates through the sample over time, where the sample includes a substrate, an underlying layer on the substrate, and an overlying layer on the underlying layer and the underlying layer is isolated from an exterior of the sample by at least the overlying layer, irradiating the sample with a probe laser pulse after irradiating the sample with the pump laser pulse, determining a reflectance variation of the sample over time, based on monitoring a variation of a reflection of the probe laser pulse from the sample over time, to generate a first graph showing a variation of reflectance of the sample over time, and determining a thickness of the underlying layer based on the first graph.

Abstract: Provided are a method of inspecting a surface and a method of manufacturing a semiconductor device. The methods include preparing a substrate, selecting a spatial resolution of a first optical device by setting a magnification of an imaging optical system, emitting multi-wavelength light toward a first measurement area of the substrate and obtaining first wavelength-specific images, generating first spectrum data based on the first wavelength-specific images, generating first spectrum data of respective pixels based on the first wavelength-specific images, and extracting a spectrum of at least one first inspection area having a range of the first measurement area or less from the first spectrum data, and analyzing the spectrum. The first optical device includes a light source, an objective lens, a detector, and an imaging optical system. The obtaining first wavelength-specific images includes using the imaging optical system and the detector.

Abstract: A method of manufacturing a semiconductor device includes forming a plurality of overlay molds on a semiconductor structure by developing a photoresist material layer of the semiconductor structure, the semiconductor structure including a first layer having a plurality of overlay marks, the plurality of overlay molds at least partially overlapping at least some of the plurality of overlay marks; and measuring one or more overlays by radiating a light having a wavelength band onto the semiconductor structure, each of the one or more overlays indicating an amount of consistency of the first layer and a second layer of the semiconductor structure, the wavelength band being set based on the plurality of overlay marks and the plurality of overlay molds, the second layer being between the first layer and the photoresist material layer.

Abstract: A thickness prediction network learning method includes measuring spectrums of optical characteristics of a plurality of semiconductor structures each including a substrate and first and second semiconductor material layers alternately stacked thereon to generate sets of spectrum measurement data, measuring thicknesses of the first and second semiconductor material layers to generate sets of thickness data, training a simulation network using the sets of spectrum measurement data and the sets of thickness data, generating sets of spectrum simulation data of spectrums of the optical characteristics of a plurality of virtual semiconductor structures based on thicknesses of first and second virtual semiconductor material layers using the simulation network, each of the first and second virtual semiconductor layers including the same material as the first and second semiconductor material layers, respectively; and training a thickness prediction network by using the sets of spectrum measurement data and the sets

Abstract: A semiconductor pattern detecting apparatus is provided.

Abstract: Provided is a hyperspectral imaging (HSI)-based inspection apparatus capable of quickly and stably performing two-dimensional (2D) HSI for an inspection object, and accordingly, capable of quickly and accurately inspecting the inspection object. The HSI-based inspection apparatus includes: a stage on which an inspection object is arranged; an optical system configured to allow light to be incident on the inspection object and emit the light reflected from the inspection object; a scan mirror configured to reflect the emitted light from the optical system while rotating; and a hyperspectral camera configured to obtain an image having a wavelength direction and a line direction as two axes for light reflected from the scan mirror, wherein, by using the rotation of the scan mirror, the hyperspectral camera is configured to perform the 2D HSI for the inspection object.

Abstract: A substrate inspection apparatus includes a light irradiating unit irradiating first light to an inspection target on a stage, a light detecting unit detecting second light reflected by the inspection target, a spectrum generator generating a first spectrum from the second light, a noise filter module removing a noise signal from the first spectrum to generate a second spectrum, a spectrum analyzer determining a first calibration parameter and a first calibration value thereof from the second spectrum, and a hardware controller adjusting at least one of the stage, the light irradiating unit and the light detecting unit using the first calibration parameter and the first calibration value.

Abstract: In a defect inspection method, first and second inspection conditions having a first sensitivity of detection signal and having a second sensitivity of a detection signal for a defect of interest (DOI), respectively, are determined. The first and second sensitivities are different. First and second images of the same detection region on a substrate surface under the first and second inspection conditions respectively, are obtained. The first and second images are matched to detect a defect in the detection region.

Abstract: A method of inspecting a semiconductor device including setting a target place on a wafer, the target place including a deep trench, forming a first cut surface by performing first milling on the target place in a first direction, obtaining first image data of the first cut surface, forming a second cut surface by performing second milling on the target place in a second direction opposite to the first direction, obtaining second image data of the second cut surface, obtaining a plurality of first critical dimension (CD) values for the deep trench from the first image data, obtaining a plurality of second CD values for the deep trench from the second image data, analyzing a degree of bending of the deep trench based on the first CD values and the second CD values, and providing the semiconductor device meeting a condition based on results of the analyzing may be provided.

Abstract: An optical measuring method includes generating a Bessel beam, filtering the Bessel beam to generate a focused Bessel beam, vertically irradiating the focused Bessel beam onto a substrate in which an opening is formed, and detecting light reflected from the substrate to obtain an image of a bottom surface of the opening.

Abstract: A method of manufacturing a semiconductor device comprising: obtaining a raw light signal by selecting a predetermined wavelength band of light reflected from a wafer on which a plurality of patterns are formed; converting the raw light signal into a frequency domain; obtaining a first detection signal having a first frequency band from the raw light signal converted into the frequency domain; obtaining a second detection signal having a second frequency band from the raw light signal converted into the frequency domain, the second frequency band being different from the first frequency band; obtaining a representative value using the first detection signal, the representative value representing a profile of the plurality of patterns; and obtaining a distribution value using the second detection signal, the distribution value representing a profile of the plurality of patterns using the second detection signal.