Samsung Electronics Co., Ltd.

Korea Advanced Institute of Science and Technology

Yu-sin Yang

Chung-sam Jun

Sang-kil Lee

Woo-seok Ko

Chung-Sam Jun

Sang-Mun Chon

Jong-An Kim

Young-hoon Sohn

Moon-Shik Kang

Ji-Hye Kim

Ji-Young Shin

Sun-Yong Choi

Min-Kook Kim

Sung-yoon Ryu

Byung-Sug Lee

Yun-jung Jee

Byeong-hwan Jeon

Souk Kim

Tae-Min Eom

Hyung-Suk Cho

Kwan-Woo Ryu

Gil-woo Song

Young-Hoon Sohn

Ki-Suk Chung

Yong-Deok Jeong

Sung-Yoon Ryu

Seong-Jin Yun

Tae-Sung Kim

Chang-Hoon Choi

Young-Nam Kim

Chi-hoon Lee

Won-Don Joo

Moon-Kyung Kim

Yun-Jung Jee

Young-Jee Yoon

Hyung-Su Son

Joung-Soo Kim

Sue-Jin Cho

Park-Song Kim

Joon-Seo Song

Min-Ho Rim

Jung-Hwan Kim

Jin-Woo Lee

Hyun-woo Kim

Kwang-soo Kim

Young-Hwan Kim

Seong-jin Kim

Sung-Ho Jang

Sang Don Jang

Jung-Soo Kim

Yasuhiro Hidaka

Byeong Hwan Jeon

Tae-Kyoung Kim

Myung-Sub Lee

Tae-joong Kim

Young-kyu Park

Kye-Weon Kim

Hyoung-jo Jeon

Chung Sam Jun

Tae-Heung Ahn

Kang-woong Ko

Ji-Hae Kim

Masahiro Horie

Yoo-Seok Jang

Kwang-il Shin

Min-chul Yoon

Woo-Seok Ko

Kyoung-hwan Lee

Ye-eun Park

Mi-Sung Lee

Su-il Cho

Hyun-su Kwak

Jung-won Kim

Sang-kyeong Han

Tae-min Eom

Kyoung-Woo Kim

Young-ho Kwon

Duck-mahn Oh

Bang-Won Kim

Jong-an Kim

Si-hyeon Choi

Ho-Jeong Kwak

Jeong-hoi Kim

Baek-man Sung

Chae-ho Shin

Jae-youn Wi

Kyung-Suk Song

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 of spectrum simulation data.

Thickness prediction network learning method, semiconductor device manufacturing method, and semiconductor material deposition equipment

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.

Methods of manufacturing semiconductor device

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.

Method of inspecting surface and method of manufacturing semiconductor device

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.

Inspecting apparatus based on hyperspectral imaging

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.

Methods for nondestructive measurements of thickness of underlying layers

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.

Method of inspecting pattern defect

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.

Defect inspection method and defect inspection apparatus

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.

Optical measuring method and apparatus, and method of manufacturing semiconductor device using the same

A method of inspecting a wafer may include: loading of a wafer onto a stage, the wafer having a plurality of dies thereon; positioning of the wafer such that a plurality of electron beam columns on the wafer respectively face a partial region of each of the plurality of dies on the wafer; scanning the respective partial regions of each of the plurality of dies by using the electron beam columns; and combining a plurality of partial images that are obtained by scanning the partial regions to provide a die image.

Method of inspecting wafer using electron beam

A surface inspecting method includes: irradiating an incident light beam of a first polarized state on a target object, the incident light beam comprising parallel light and having a cross-sectional area: measuring a second polarized state of a reflected light beam reflected from the target object; and performing inspection on an entire area of the target object on which the incident light beam is irradiated, based on a variation between the first polarized state and the second polarized state.

Surface inspecting method

An optical transformation module includes a light generator generating a parallel light beam to be incident onto a surface of an inspection object and changing a wavelength of the parallel light beam, and a rotating grating positioned on a path of the parallel light beam and rotatable by a predetermined rotation angle such that the parallel light beam is transformed according to the wavelength of the parallel light beam and the rotation angle of the rotating grating to have a desired incidence angle and a desired incidence position onto the surface of the inspection object.

Optical transformation module and optical measurement system, and method of manufacturing a semiconductor device using optical transformation module and optical measurement system

An apparatus and method of forming an epitaxial layer are provided. The apparatus includes a process chamber in which an epitaxial process is performed to form epitaxial layer on a substrate. A first supplier supplies source gases for the epitaxial layer into the process chamber. A second supplier supplies dopants into the process chamber. A detector detects a composition ratio of the epitaxial layer and a concentration of the dopants in the epitaxial layer during the epitaxial growth process. And a controller controls a mass flow of at least one of the source gases and a mass flow of the dopants in-line with the epitaxial growth process. Accordingly, the layer thickness of the epitaxial layer can be accurately controlled in real time in line with the epitaxial process.

Apparatus for forming a thin layer and method of forming a thin layer on a substrate using the same

A broadband light source includes a first electrodeless lamp to generate first broadband light from plasma, a first elliptical reflector having first and second focuses, the first elliptical reflector enclosing a rear portion of the first electrodeless lamp positioned at the first focus of the first elliptical reflector such that the first broadband light is reflected from the first elliptical reflector toward a light collector as a collective light, a symmetrically curved reflector having a third focus, the symmetrically curved reflector positioned such that the third focus is coincident with one of the first and second focuses, and a laser irradiator to provide a laser beam to the first electrodeless lamp.

Broadband light source and optical inspector having the same

Spectral ellipsometry measurement systems are provided including a polarizer that rotates at a first angle and adjusts a polarizing direction of incident light of a measurement sample; a compensator that rotates at a second angle, different from the first angle, and adjusts a phase difference of the incident light; an analyzer that rotates at a third angle and adjusts a polarizing direction of light reflected on the measurement sample; a detector that detects a spectral image from the reflected light; a controller that controls one of the polarizer, the compensator, and the analyzer according to polarizer-compensator-analyzer (PCA) angle sets including the first to third angles; and a processor that receives, from the detector, a first spectral image corresponding to a first PCA angle set and a first wavelength and a second spectral image corresponding to a second PCA angle set and a second wavelength, different from the first wavelength, and generates a polarizer-compensator-analyzer rotating (PCAR) spectral matrix using the first and second spectral images.

Spectral ellipsometry measurement and data analysis device and related systems and methods

Growing community of inventors

Seoul, South Korea

Yu-sin Yang