Patent classifications
G01N2223/6116
ELECTRON BEAM DETECTION APPARATUS FOR SEMICONDUCTOR DEVICE AND ELECTRON BEAM DETECTION ASSEMBLY
An electron beam detection apparatus for a semiconductor device and an electron beam detection assembly are disclosed, the electron beam detection apparatus including a stage, which is configured to carry and hold the semiconductor device at a top surface of the stage, and is translatable in two directions orthogonal to each other, an aiming device, configured to determine a position of the semiconductor device in a coordinate system of the electron beam detection apparatus by capturing an image of the semiconductor device, the aiming device provided with a first field of view and a first optical axis, and an electron beam detection device, configured to detect an emergent electron beam exiting the semiconductor device by projecting an electron beam to the semiconductor device, the electron beam detection device provided with a second field of view and a second optical axis which is not consistent with the first optical axis.
Overlay Measurement System and Overlay Measurement Device
The present invention enables an overlay error between processors to be measured from a pattern image, the SN ratio of which is low. To this end, the present invention forms a secondary electron image 200 from a detection signal of a secondary electron detector 107, forms a reflected electron image 210 from a detection signal of a reflected electron detector 109, creates a SUMLINE profile 701 that is obtained by adding luminance information in the reflected electron image along the longitudinal direction of a line pattern, and calculates an overlay error of a sample by using position information about an upper layer pattern detected from the secondary electron image and position information about a lower layer pattern that is detected by using an estimation line pattern 801 estimated on the basis of the SUMLINE profile from the reflected electron image.
Time-dependent defect inspection apparatus
An improved charged particle beam inspection apparatus, and more particularly, a particle beam inspection apparatus for detecting a thin device structure defect is disclosed. An improved charged particle beam inspection apparatus may include a charged particle beam source to direct charged particles to a location of a wafer under inspection over a time sequence. The improved charged particle beam apparatus may further include a controller configured to sample multiple images of the area of the wafer at difference times over the time sequence. The multiple images may be compared to detect a voltage contrast difference or changes to identify a thin device structure defect.
Method and system for virtually executing an operation of an energy dispersive X-ray spectrometry (EDS) system in real-time production line
Provided is a method for virtually executing an operation of an energy dispersive x-ray spectrometry (EDS) system in real time production line by analyzing a defect included in a material undergoing inspection based on computer vision, the method including receiving a scanning electron microscope (SEM) image of the material including the defect, extracting an image-feature from the SEM image of the material, classifying the extracted image-feature under a predetermined label, predicting, based on the classified image-feature, an element associated with the defect included in the material and a shape of the predicted element, and grading the defect included in the material based on comparing the predicted element with a predetermined criteria.
METHOD FOR MEASURING A SAMPLE AND MICROSCOPE IMPLEMENTING THE METHOD
The present invention relates to a method for measuring a sample with a microscope, the method comprising scanning the sample using a focusing plane having a first angle with respect to a top surface of the sample and computing a confidence distance based on the first angle. The method further comprises selecting at least one among a plurality of alignment markers on the sample for performing a lateral alignment of the scanning step and/or for performing a lateral alignment of an output of the scanning step. In particular, the at least one alignment marker selected at the selecting step is chosen among the alignment markers placed within the confidence distance from an intersection of the focusing plane with the top surface.
IMAGE PICKUP DEVICE AND IMAGE GENERATION METHOD
An image pickup device includes a disk with an aperture formed with an aperture through which X-rays can transmit, a vacuum suction ring having an inner peripheral ring and an outer peripheral ring having different heights, and fixes a position of the aperture with respect to a subject. Further, the image pickup device includes a rotation stage that holds the subject and the disk with an aperture fixed by the vacuum suction ring, and can rotate at a desired angle about a rotation axis along a direction perpendicular to a surface of the subject, and a one-dimensional detector in which line-shaped pixels are disposed at a predetermined pixel pitch. Further, the image pickup device includes an imaging mirror that forms an image of X-rays transmitted through the subject and the aperture on the one-dimensional detector, and a control analysis unit that corrects coordinates of an image intensity profile detected by the one-dimensional detector, and reconstructs an image of the subject from the image intensity profile after the correction.
Offcut angle determination using electron channeling patterns
Methods and apparatus determine offcut angle of a crystalline sample using electron channeling patterns (ECPs), wherein backscattered electron intensity exhibits angular variation dependent on crystal orientation. A zone axis normal to a given crystal plane follows a circle as the sample is azimuthally rotated. On an ECP image presented with tilt angles as axes, the radius of the circle is the offcut angle of the sample. Large offcut angles are determined by a tilt technique that brings the zone axis into the ECP field of view. ECPs are produced with a scanning electron beam and a monolithic backscattered electron detector; or alternatively with a stationary electron beam and a pixelated electron backscatter diffraction detector. Applications include strain engineering, process monitoring, detecting spatial variations, and incoming wafer inspection. Methods are 40× faster than X-ray diffraction. 0.01-0.1° accuracy enables semiconductor applications.
METHOD OF INSPECTING A SAMPLE, AND MULTI-ELECTRON BEAM INSPECTION SYSTEM
A method for inspecting a sample with a multi-electron beam inspection system (100) is described. The method includes: placing the sample on a movable stage (110) extending in an X-Y-plane; generating a plurality of electron beams (105) propagating toward the sample; focusing the plurality of electron beams on the sample at a plurality of probe positions (106) in a two-dimensional array; scanning the sample surface by moving the movable stage in a predetermined scanning pattern while maintaining the plurality of electron beams stationary; and detecting signal electrons emitted from the sample during the movement of the movable stage for inspecting the sample. Further, a multi-electron beam inspection system (100) for inspecting a sample according to the above method is described.
METHOD FOR DRY-ETCHING SEMICONDUCTOR SUBSTRATE AND METHOD FOR DRY-ETCHING SILICON OXIDE FILM
A method for dry-etching a semiconductor substrate having an oxide film, including: evaluating a film quality of the oxide film and determining a time for performing the dry-etching on a basis of results of the evaluation in advance. This provides a method for controlling the etching amount of an oxide film accurately and suppressing over-etching and insufficient etching without influence from variation in the film quality of the oxide film when dry-etching the oxide film on the surface of the semiconductor substrate.
System and method for detecting contamination of thin-films
A thin-film deposition system deposits a thin-film on a wafer. A radiation source irradiates the wafer with excitation light. An emissions sensor detects an emission spectrum from the wafer responsive to the excitation light. A machine learning based analysis model analyzes the spectrum and detects contamination of the thin-film based on the spectrum.