A method for increasing Signal-to-Noise-Ratio (SNR) of defect detection in inspection of wafers or masks, the method including receiving a current image, receiving a reference image, receiving an indication for existence of a defect in the current image, producing a difference image between the current image and the reference image, performing singular value decomposition (SVD) on the difference image, removing one or more lower-valued singular values from a diagonal middle matrix produced by the SVD, thereby producing a reduced middle matrix, and producing an improved-SNR difference image by reconstructing the difference image using the reduced middle matrix. Related apparatus and methods are also described.
A method and system for optimizing a metrology algorithm used by an inspection tool for inspecting predetermined sites of a semiconductor wafer during fabrication so as to allow repetitive and consistent inspection for multiple sites of the wafer by both a single inspection tool of a given type using the metrology algorithm and also across a fleet of different inspection tools of the same type using the metrology algorithm. An aggregate loss function is computed from a sum of component loss functions. In one aspect, each component loss function is amplified by a non-linear function that applies a positive gain for in-range measurements and for out-of-range measurements, applies a steep penalty that swamps any cumulative gains associated with other component loss functions. In another aspect, distribution-based metrics are used to measure similarity between two distributions of measurements for multiple locations across two different tools.
G03F 7/00 - Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printed surfacesMaterials therefor, e.g. comprising photoresistsApparatus specially adapted therefor
3.
REGISTRATION BETWEEN AN INSPECTION IMAGE AND A DESIGN IMAGE
There are provided systems and methods comprising obtaining an inspection image of a semiconductor specimen, and a design image, wherein the design image is informative of design elements, determining data Dpitch informative of a periodic distance between design elements of the design image, which are associated with a shape meeting a similarity criterion, and using the data Dpitch to obtain registration data between the design image and the inspection image.
A system for training a model representing elements in the input space, each having N dimensions and being associated with images of a semiconductor specimen, to a latent space representing an equal number of elements each having M (M≤N) dimensions. The system includes a processor configured to obtain a desired probability function for transformation of the elements in the input space cluster(s) s of elements in the latent space. Then, using the desired probability function to repeatedly transform, until a specified criterion is met, elements in the input space to equal elements in the latent space in compliance with an actual probability function that is indicative of an actual allocation of the elements to the cluster(s). Lastly, determining a training loss value L associated with the elements in the latent space and testing if the training loss value L meets the specified criterion.
There is provided a system and method of a method of mask inspection, comprising: obtaining a plurality of aerial images of a mask; generating a plurality of image coresets corresponding to the aerial images, comprising, for each given aerial image: applying a printing threshold on the given aerial image to obtain a binary image representative of printable features thereof; extracting a contour for each feature of interest (FOI) from the printable features, and generating a descriptor characterizing the contour, giving rise to a group of contours associated with respective descriptors; and creating an image coreset for the group of contours based on the respective descriptors thereof, the image coreset comprising one or more families, each comprising at least one representative contour representing one or more similar contours of a respective type from the group of contours. The plurality of image coresets can be merged to obtain a mask coreset.
A method for training a machine learning process, the method includes obtaining signatures of substrate patterns of a training related substrate; finding first signatures of reference patterns that are similar to the signatures of the substrate patterns, the reference patterns are associated with defects previously defined as defects of interest, the finding is executed regardless of one or more parameters that impact a generation of the first reference signatures; populating a defects of interest dataset with second signatures of the reference patterns that convey more information about the defects previously defined as defects of interest than the first signatures of the reference patterns; populating another dataset with additional signatures; and training, in a supervised manner, the machine learning process to find defects of interest, wherein the training includes feeding the defects of interest dataset and the other dataset to the machine learning process.
There are provided systems and methods comprising obtaining image data informative of a cavity in a semiconductor specimen, wherein the cavity is associated with at least one sidewall, using the image data to determine one or more attributes of at least one area of the image data, wherein the area is informative of at least one of at least part of the sidewall, or one or more elements coupled to the sidewall, and using the one or more attributes to determine data indicative of whether the sidewall is undercut.
G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 20/70 - Labelling scene content, e.g. deriving syntactic or semantic representations
8.
NONDESTRUCTIVE ESTIMATION OF STRUCTURAL PROPERTIES OF A SPECIMEN VIA X-RAY MODELLING BASED ON GROUND TRUTH MEASUREMENTS
Disclosed herein is a system for non-destructive characterization of specimens. The system includes an electron beam (e-beam) source for projecting e-beams at one or more e-beam landing energies on a specimen; an X-ray detector for sensing X-rays emitted from the specimen, thereby obtaining measurement data; and a processing circuitry. The processing circuitry is configured to: (i) extract from the measurement data key features specified by a vector {right arrow over (ƒ)}key; and (ii) estimate values {right arrow over (p)} of one or more structural parameters characterizing the specimen, based on {right arrow over (ƒ)}key and a set of vectors of key features {{right arrow over (ƒ)}n}n=1N of ground truth (GT) reference specimens. Each of the {right arrow over (ƒ)}n is a product of measurements of emission of X-rays from a reference specimen due to impinging thereof with e-beams at each of the one or more landing energies.
There are provided systems and methods comprising obtaining an inspection image of a semiconductor specimen and a second image, applying a distance transform operation to at least part of the second image, or to at least part of an image derived from the second image, thereby obtaining at least one transform image, applying a distance transform operation to at least part of the inspection image, or to at least part of an image derived from the inspection image, thereby obtaining a transformed inspection image, performing a matching operation using data informative of the at least one transform image and data informative of the transformed inspection image, thereby obtaining matching data, and using the matching data to identify an area of the inspection image which matches the second image according to a matching criterion.
There is provided a system and method of examination of a semiconductor specimen. The method includes obtaining a group of defect candidates associated with respective inspection locations represented in an inspection coordinate system; using a trained machine learning (ML) model to provide, for each defect candidate, a probability of the defect candidate being a defect of interest (DOI), and ranking the group of defect candidates to an ordered list according to respective probabilities thereof, in response to a part of the ordered list of defect candidates being reviewed by a review tool in accordance with an order thereof, receiving a predefined number of DOIs associated with respective review locations represented in a review coordinate system; and calculating an offset between the review coordinate system and the inspection coordinate system based on respective inspection and review locations associated with the predefined number of DOIs.
There is provided a system and a method comprising obtaining data Dcontour informative of a contour of an element of a semiconductor specimen acquired by an examination tool, using the data Dcontour to generate a signal informative of a curvature of the contour of the element, determining at least one of data Dperiodicity informative of a periodicity of the signal, or data Ddiscontinuities informative of a number of discontinuities in the signal, wherein each discontinuity is informative of a transition between a convex portion of the contour and a concave portion of the contour, and using at least one of the data Dperiodicity or the data Ddiscontinuities to determine data informative of correct manufacturing of the element.
There are provided systems and methods comprising obtaining an acquisition signal informative of a semiconductor specimen comprising at least a first layer located at a first depth and a second layer located at a second depth, wherein the acquisition signal has been acquired by an electron beam examination system operative to scan the specimen with an electron beam associated with a landing energy enabling generating, in at least one of the acquisition signal or in a signal derived from the acquisition signal, a first pattern informative of a lateral edge of the first layer, and a second pattern informative of a lateral edge of the second layer, wherein the second pattern differs from the first pattern, and using at least one of the acquisition signal or the signal derived from the acquisition signal, to determine properties of at least one of the first layer or the second layer.
G01N 23/2251 - Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups , or by measuring secondary emission from the material using electron or ion microprobes using incident electron beams, e.g. scanning electron microscopy [SEM]
G01B 15/00 - Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons
13.
NONDESTRUCTIVE ESTIMATION OF STRUCTURAL PROPERTIES OF A SPECIMEN VIA X-RAY MODELLING BASED ON SIMULATIONS AND GROUND TRUTH MEASUREMENTS
A system for non-destructive characterization of specimens that includes an electron beam (e-beam) source for projecting e-beams at one or more e-beam landing energies on a specimen; an X-ray detector for sensing X-rays emitted from the specimen, thereby obtaining measurement data; and processing circuitry configured to: (i) extract from the measurement data key features specified by a vector {right arrow over (f)}key; and (ii) estimate values {right arrow over (p)} of one or more structural parameters, characterizing the specimen, based on {right arrow over (f)}key and a set of vectors of ground truth (GT) and simulated key features {{right arrow over (f)}n}n=1N. Each of the {right arrow over (f)}n is a product of GT measurements or of computer simulations of emission of X-rays from a respective GT or simulated specimen due to impinging thereof with e-beams at each of the one or more landing energies.
G01N 23/2252 - Measuring emitted X-rays, e.g. electron probe microanalysis [EPMA]
G01N 23/083 - Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups , or by transmitting the radiation through the material and measuring the absorption the radiation being X-rays
G01N 23/223 - Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups , or by measuring secondary emission from the material by irradiating the sample with X-rays or gamma-rays and by measuring X-ray fluorescence
14.
IDENTIFICATION OF AN ARRAY IN A SEMICONDUCTOR SPECIMEN
There is provided a method and a system configured obtain an image of a semiconductor specimen including one or more arrays, each including repetitive structural elements, and one or more regions, each region at least partially surrounding a corresponding array and including features different from the repetitive structural elements, wherein the PMC is configured to, during run-time scanning of the semiconductor specimen, perform a correlation analysis between pixel intensity of the image and pixel intensity of a reference image informative of at least one of the repetitive structural elements, to obtain a correlation matrix, use the correlation matrix to distinguish between one or more first areas of the image corresponding to the one or more arrays and one or more second areas of the image corresponding the one or more regions, and output data informative of the one or more first areas of the image.
G06V 10/762 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using clustering, e.g. of similar faces in social networks
G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
15.
3D METROLOGY FROM 3D DATACUBE CREATED FROM STACK OF REGISTERED IMAGES OBTAINED DURING DELAYERING OF THE SAMPLE
A method of evaluating a region of interest of a sample including: positioning the sample within in a vacuum chamber of an evaluation tool that includes a scanning electron microscope (SEM) column and a focused ion beam (FIB) column; acquiring a plurality of two-dimensional images of the region of interest by alternating a sequence of delayering the region of interest with a charged particle beam from the FIB column and imaging a surface of the region of interest with the SEM column; generating an initial three-dimensional data cube representing the region of interest by stacking the plurality of two-dimensional images on top of each other in an order in which they were acquired; identifying distortions within the initial three-dimensional data cube; and creating an updated three-dimensional data cube that includes corrections for the identified distortions.
An optical inspection system for inspection of a mask or a wafer, the system including an objective for collecting light coming from an object being inspected, a relay component placed on an optical path between the objective and an imaging component, for collecting light from the objective, and relaying the collected light to the imaging component, wherein the optical inspection system further includes a mirror placed on the optical path between the objective and the relay module, for changing a direction of the optical path at an angle away from an optical axis of the objective and into an optical axis of the relay component, the relay component includes reflecting surfaces arranged such that the collected light passes back and forth within the relay component three times. Related apparatus and methods are also described.
There is provided a system and method of examination of a semiconductor specimen. The semiconductor specimen comprises at least a surface layer and a under layer. The method includes obtaining a secondary electron (SE) image and a backscattered electron (BSE) image of the specimen acquired by an electron beam tool, wherein the BSE image possesses one or more image artifacts caused by one or more structural features on the surface layer; processing the SE image to generate a feature mask comprising a set of segments representative of the one or more structural features; and generating a corrected BSE image based on the BSE image and the feature mask, wherein the corrected BSE image possesses suppressed image artifacts with respect to the one or more image artifacts in the BSE image.
There is provided a system and method of defect examination on a semiconductor specimen. The method comprises obtaining an input image indicative of difference between an inspection image of the specimen and a corresponding reference image; and processing the input image using a trained machine learning (ML) system, to generate an output image representative of a defect map indicative of distribution of defect of interest (DOI) candidates in the input image. The ML system comprises a plurality of ML models operatively connected therebetween and previously trained together to perform defect detection on the input image based on Fourier transform. The output image is usable for further defect examination.
There is provided a system and method of defect detection on a semiconductor specimen based on template matching or machine learning (ML). Template matching is performed between a set of template patches and a set of runtime images, by selectively performing at least two of the following: matching a defect template patch in an inspection image, matching a reference template patch in a reference image, or matching a difference template patch in a difference image, so as to provide likelihood of target of interest (TOI) presence in the inspection image. The ML-based approach includes feeding an inspection patch and a reference patch together to a trained ML model, to generate a feature vector representative of a given TOI candidate, and evaluating the feature vector of the given TOI candidate to provide a likelihood of the given TOI candidate being a TOI or non-TOI.
Disclosed herein is a computerized system for metrology of structures. The system includes an optical setup and a computational module. The optical setup is configured to: (i) project on a profiled structure at least one optical pump beam, which is configured to be absorbed by the profiled structure, so as to induce vibrations of the profiled structure and a corresponding change in a reflection coefficient of the profiled structure; (ii) while the profiled structure is vibrating, project on the profiled structure at least one probe beam; and (iii) sense at least one light beam, returned from the profiled structure, thereby obtaining at least one measured signal. The computational module is configured to process the at least one measured signal to determine one or more structural parameters of the profiled structure.
There are provided systems and methods comprising obtaining a set of images of at least one element of a semiconductor specimen, wherein the set of images has been acquired by an electron beam examination tool operative to transmit an electron beam towards the semiconductor specimen through a device of the electron beam examination tool, wherein each given image of the set of images has been acquired by the electron beam examination tool with a different focal point of the electron beam than for acquisition of one or more other images of the set of images, determining data informative of a displacement of the at least one element in the set of images, and using the data and a model informative of electron beam deflection to determine data usable to move the electron beam to a required position of the electron beam in the device.
A wafer inspection system, that includes (a) a scanner configured to scan, while following a dynamic scan plan, a set of tiles that are associated with a region of interest of a die of a wafer to provide a set of tiles scanning results; (b) a comparison circuit configured to compare the set of tiles scanning results to reference items to provide a set of comparison results, at least some of the reference items were generated based on one or more other sets of tiles scanning results generated by scanning one or more other sets of tiles associated with one or more other regions of interest; and (c) a decision circuit configured to determine, based on the set of comparison result, a state of the region of interest; and generate new reference items based on at least some of the set of tiles scanning results.
The presently disclosed subject matter includes a novel computer-implemented method and computer system for the classification of tabular data using a new neural network classifier model (also referred to herein as “Tabular Neural Network Classifier” or TNNC). The disclosed method and system are characterized by improved accuracy and efficiency, as compared to other existing tabular data classification techniques such as Random Forests, XGBoost, etc. The inventor found that the TNNC exhibits in general a better TP to FP ratio in the classification output and a shorter processing time, as compared to existing tabular data classification techniques.
There are provided systems and methods comprising obtaining a first inspection image informative of a first area of a specimen acquired by an examination tool, feeding at least the first inspection image to a machine learning algorithm configured to determine, for each given pixel of a plurality of pixels of the first inspection image, or for each given group of pixels of a plurality of groups of pixels of the first inspection image, one or more given parameters of a given model informative of pixel intensity distribution, for said each given pixel or given group of pixels, using at least some of the one or more given parameters, or the given model associated with the one or more given parameters, and measured pixel intensity of the given pixel or group of pixels, to determine whether a defect is present in the given pixel or in the given group of pixels.
A vacuum chuck for supporting a sample, the vacuum chuck comprising: a support plate having an upper planar support surface sized and shaped to retain a sample disposed thereon; one or more vacuum lines formed within the support plate; a plurality of cavities formed within the support plate, wherein each cavity is fluidly coupled to a vacuum line in the one or more vacuum lines and includes an aperture at an upper surface of the planar support surface; and a plurality of vacuum pad plungers corresponding in number to the plurality of cavities, wherein each vacuum pad plunger is disposed in a unique one of the cavities and comprises a plunger body having a vacuum channel extending through its length and a biasing mechanism, wherein the plunger body is moveable between an up position in which a portion of the plunger body extends through the aperture of its respective cavity protruding above the upper planar support surface and a down position in which the plunger body is retracted into the cavity, and wherein the biasing mechanism biases the plunger body in the up position.
G01N 21/95 - Investigating the presence of flaws, defects or contamination characterised by the material or shape of the object to be examined
G01N 21/88 - Investigating the presence of flaws, defects or contamination
H01L 21/66 - Testing or measuring during manufacture or treatment
H01L 21/683 - Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereofApparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components for supporting or gripping
H01L 21/687 - Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereofApparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components for supporting or gripping using mechanical means, e.g. chucks, clamps or pinches
26.
METHODS AND SYSTEMS FOR OBTAINING A 3D PROFILE OF A SAMPLE
A method for obtaining a 3D profile of a sample comprising: receiving a first and second sets of data relating to first and second groups of structural parameters from first and second metrology tools, wherein the first and second groups of structural parameters have at least one structural parameter in common; analyzing the first set of data to obtain values for the first group of structural parameters; analyzing the second set of data to obtain values for the second group of structural paraments, wherein values obtained from the analysis of the first set of data for at least some of the common structural features are used to constrain the analysis of the second set of data; and generating a 3D profile of the sample by combining values obtained in the analyses of the first and second sets of data.
A systems for in-depth profiling of patterned wafer samples including a pump pulse and plurality of probe pulses each having a different wavelength (λl-λn), and an optical setup configured to combine the plurality of probe pulses, such that they simultaneously reach the same target region of the sample and to separate the plurality of probe pulses upon their reflection from the sample, such that each of the plurality of probe pulses is detected by a separate detector.
Embodiments of the present disclosure relate to metrology using joint angle and wavelength scattering. For example, a system can include a light source configured to generate light, a wavelength selection subsystem configured to select at least one wavelength of the light to be directed as a light beam to a sample having periodic structures, and a diffraction detection subsystem to detect a diffracted light beam from the sample, The light beam incident on the sample has a direction of illumination and angular spread selected to separate incident angles and wavelengths in a diffraction pattern to be obtained from the sample. The periodic structures have a periodicity for simultaneously obtaining multi-angle and multi-wavelength information from the diffracted light beam.
G01N 21/88 - Investigating the presence of flaws, defects or contamination
G01B 11/00 - Measuring arrangements characterised by the use of optical techniques
G02B 26/08 - Optical devices or arrangements for the control of light using movable or deformable optical elements for controlling the direction of light
A vacuum chuck for supporting a sample, the vacuum chuck comprising: a support plate having an upper planar support surface sized and shaped to retain a sample disposed thereon; one or more vacuum lines formed within the support plate; a plurality of cavities formed within the support plate, wherein each cavity is fluidly coupled to a vacuum line in the one or more vacuum lines and includes an aperture at an upper surface of the planar support surface; and a plurality of vacuum pad plungers corresponding in number to the plurality of cavities, wherein each vacuum pad plunger is disposed in a unique one of the cavities and comprises a plunger body having a vacuum channel extending through its length and a biasing mechanism, wherein the plunger body is moveable between an up position in which a portion of the plunger body extends through the aperture of its respective cavity protruding above the upper planar support surface and a down position in which the plunger body is retracted into the cavity, and wherein the biasing mechanism biases the plunger body in the up position.
Disclosed herein is a system for non-destructive characterization of specimens. The system includes an electron beam (e-beam) source for projecting e-beams at one or more e-beam landing energies on a specimen; an X-ray detector for sensing X-rays emitted from the specimen, thereby obtaining measurement data; and a processing circuitry. The processing circuitry is configured to: (i) extract from the measurement data key features specified by a vector {right arrow over (f)}key; and (ii) determine values {right arrow over (p)} of one or more structural parameters, characterizing the specimen, based on {right arrow over (f)}key and a set of vectors of simulated key features {{right arrow over (f)}n}n=1N. Each of the {right arrow over (f)}n is a product of a computer simulation of emission of X-rays from a respective simulated specimen due to impinging thereof with e-beams at each of the one or more landing energies.
G01N 23/2252 - Measuring emitted X-rays, e.g. electron probe microanalysis [EPMA]
G01B 15/02 - Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons for measuring thickness
G01B 15/04 - Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons for measuring contours or curvatures
31.
MEASURING CONTAMINATION ACCUMULATED ON A SEMICONDUCTOR SPECIMEN
A system for monitoring an extent of contamination affecting a critical dimension of a specimen as measured by an examination tool. The system incudes a processor operatively connected to the examination tool. The processor is configured to obtain a plurality of measurement cycles, each including measurements of a critical dimension (CD) of patterns of the specimen when accommodated within a chamber of the examination tool. The measurement cycles are made at discrete time intervals, such that successive measurement cycles are subjected to a change in the CD measurements. The processor is further configured to determine the extent of contamination as a function of a gradient of a straight-line approximating of the CD measurements.
H01L 21/00 - Processes or apparatus specially adapted for the manufacture or treatment of semiconductor or solid-state devices, or of parts thereof
H01L 21/67 - Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereofApparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components
There are provided systems and methods of calibration of an examination tool comprising at least one given optical device associated with a given moveable element, at least one of a position or an orientation of the given moveable element having to be calibrated, the system being configured to obtain a data set comprising values for one or more given parameters characterizing light transmitted by the at least one given optical device for different values of the position or of the orientation of the given moveable element, one or more required values for the one or more given parameters, and use the data set and the one or more required values to determine data informative of at least one of a calibrated position or a calibrated orientation of the given moveable element, enabling the one or more parameters to have values matching the one or more required values.
There is provided a system and method of defect examination on a semiconductor specimen. The method comprises: obtaining an inspection dataset informative of a group of defect candidates and attributes thereof resulting from examining the specimen by an inspection tool; classifying, by a classifier, the group of defect candidates into a plurality of defect classes such that each defect candidate is associated with a respective defect class; and ranking, by a decision model, the group of defect candidates into a total order using a sorting rule. Each defect candidate is associated with a distinct ranking in the total order representative of the likelihood of the defect candidate being a defect of interest (DOI). The decision model is previously trained to learn the sorting rule pertaining to the plurality of defect classes associated with the group of defect candidates and a series of attributes in the inspection data.
Disclosed herein is a method for non-destructive depth-profiling including projecting a pulsed pump beam into a specimen, projecting a pulsed probe beam thereinto, and sensing light returned therefrom to obtain a measured signal. Each probe pulse is configured to undergo Brillouin scattering off a primary acoustic pulse induced by the directly preceding pump pulse, so as to be scattered there off at a respective depth within the specimen. The method further includes executing an optimization algorithm configured to receive as inputs the measured signal, and/or a processed signal obtained therefrom, and output values of structural parameter(s) characterizing the specimen through minimization of a cost function indicative of a difference between the measured signal and a simulated signal obtained using a forward model simulating the scattering of a pulsed probe beam off at least the primary acoustic pulses.
The present disclosure relates to a method of providing a light signal separation unit in an optical reflective microscope system, said optical reflective microscope system comprising an objective lens arrangement configured to collect light reflected off a plurality of field points on an object and to onwardly transmit a light beam formed from the collected light and said light signal separation unit having a reflective surface with a central transmissive region formed therein, wherein said central transmissive region is arranged to allow therethrough a central portion of said light beam transmitted from said objective lens arrangement while said reflective surface is arranged to reflect a peripheral portion of said light beam transmitted from said objective lens arrangement. The method comprises determining an axial position at which to position said light signal separation unit. The axial position being a position along an optical axis of said objective lens arrangement, contiguous to an exit pupil of said objective lens arrangement, at which beam deformation of said light beam is substantially minimal; determining a dimension of a cross section of said light beam at said axial position; and determining a dimension of said central transmissive region based on said dimension of said cross section of said light beam and said lateral displacement at said axial position.
The present disclosure relates to a method of designing an objective lens arrangement for an optical microscope system, said objective lens arrangement being configured, in use, to collect light from a plurality of field points on an object and to onwardly transmit a light beam formed from the collected light, the method comprising: (a) providing an objective lens; (b) tracing, for the plurality of field points, a light cone from each field point through said objective lens arrangement; (c) determining a marginal ray and a chief ray for said light cone from each field point exiting said objective lens arrangement and monitoring said marginal ray relative to said chief ray for each light cone exiting said objective lens arrangement; (d) determining an exit pupil contour for said objective lens arrangement respective of each field point and monitoring an overlap of exit pupil contours respective of said plurality of field points; (e) determining an exit pupil magnification with respect to an entrance pupil of said objective lens arrangement for each field point and monitoring a deviation in said exit pupil magnification respective of said plurality of field points; (f) adjusting one or more physical parameters of said objective lens arrangement; and (g) repeating one or more of (b) to (f) until said marginal ray relative to said chief ray for each light cone exiting said objective lens arrangement are substantially parallel, said overlapping is substantially maximised, and said deviation in said exit pupil magnification is substantially minimised.
Disclosed are method and system for calibrating a tilt angle of an electron beam of a backscattered scanning electron microscope including scanning a bare wafer at a plurality of electron beam tilt and azimuth angles, thereby obtaining a calibration map representing a crystal orientation of the bare wafer, selecting a tilt angle and defining an expected diffraction pattern associated with the tilt angle, based on the calibration map; scanning a patterned wafer at the selected tilt angle, comparing the diffraction pattern of the image obtained from the scanning of the patterned wafer at the selected tilt angle with the expected diffraction pattern; correcting the tilt angle of the electron beam of the BSEM tool, such that the diffraction pattern of the image obtained during scanning of the patterned wafer will align with the expected diffraction pattern.
G01N 23/2251 - Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups , or by measuring secondary emission from the material using electron or ion microprobes using incident electron beams, e.g. scanning electron microscopy [SEM]
H01J 37/22 - Optical or photographic arrangements associated with the tube
H01J 37/244 - DetectorsAssociated components or circuits therefor
H01J 37/28 - Electron or ion microscopesElectron- or ion-diffraction tubes with scanning beams
A support unit for supporting a supported element, including (a) a spherical joint, (b) a pressure applying unit that is configured to maintain contact between a spherical outer surface and a base, (c) a position control unit that is configured to contact the spherical joint positioning element at multiple contact points and to set values of a first angle of rotation and a second angle of rotation of the spherical outer surface. The spherical joint is located above the position control unit. A distance between a fixed center of rotation and a point on the spherical outer surface is smaller than (b) a distance between the fixed center of rotation and any contact point of the multiple contact points.
There is provided a system and method of defect examination on a semiconductor specimen. The method comprises obtaining a runtime image of the semiconductor specimen; generating a reference image based on the runtime image using a machine learning (ML) model; and performing defect examination on the runtime image using the generated reference image. The ML model is previously trained alternately between two training modes using a training set: a stochastic mode where the ML model is configured to generate a predicted reference image with a stochastic pattern variation (PV) from a PV distribution, and a deterministic mode where the ML model is configured to generate a predicted reference image with a predetermined PV selected from the PV distribution, the PV distribution being learnt by the ML model based on PVs observed across the training set.
A substrate alignment system that includes (i) an illumination unit that is configured to illuminate an illuminated region that comprises an entire edge of a substrate; (ii) a sensing unit having a field of view that covers the entire edge of the substrate even when the substrate is misaligned, the sensing unit includes a sensor that is preceded by a fish eye lens, the sensor is configured to generate detection signals of the entire edge of the substrate; and (iii) a processing circuit that is configured to process the detection signals and determine whether the substrate is misaligned. A determining that the substrate is misaligned triggers an execution of one or more misalignment correction operation for aligning the substrate.
H01L 21/68 - Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereofApparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components for positioning, orientation or alignment
G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
H01L 21/67 - Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereofApparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components
H04N 23/56 - Cameras or camera modules comprising electronic image sensorsControl thereof provided with illuminating means
An apparatus that includes an end effector for handling and transporting wafers, the end effector including: a base portion having a first end adapted to be attached to a robot; a wafer support platform having a surface to support a wafer, a slidable joint coupling the base portion to the wafer support platform; and a sensor configured to detect when the wafer support platform slides relative to the base portion beyond a predetermined distance.
An apparatus that includes an end effector for handling and transporting wafers, the end effector including: a base portion having a first end adapted to be attached to a robot; a wafer support platform having a surface to support a wafer; a slidable joint coupling the base portion to the wafer support platform; and a sensor configured to detect when the wafer support platform slides relative to the base portion beyond a predetermined distance.
H01L 21/687 - Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereofApparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components for supporting or gripping using mechanical means, e.g. chucks, clamps or pinches
H01L 21/677 - Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereofApparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components for conveying, e.g. between different work stations
A system for scanning a surface including: an illumination system providing inspection light for illumination of a field of view (FOV) on an inspection object to produce a reflected light beam from the inspection object; an objective lens arrangement, located between the illumination system and the surface; a light separator: having a reflective surface arranged: to direct the inspection light towards the FOV; and to receive and change a direction of brightfield light comprising a central portion of the reflected light beam; and sized and shaped to allow therearound darkfield light comprising a peripheral portion of the reflected light beam; a holder configured to provide mechanical support to the light separator, having a first portion attached to the light separator and a second portion extending away from the light separator.
A method of determining a depth of a feature formed in a first region of a sample, by: positioning a test structure with known dimensions in a processing chamber having a charged particle column tilted at a first tilt angle and first rotational angle; determining the first tilt angle and first rotational angle by: taking an image of the test structure with the charged particle column tilted at the first tilt angle and the first rotational angle, measuring, based on the image, distances between multiple edges of the test structure aligned with each other along a vector, determining ratios between the measured distances, and determining a calculated tilt angle and a calculated rotational angle of charged particle column from the ratios and the known dimensions of the structure; transferring the test structure out of the processing chamber and positioning the sample in the processing chamber such that the first region is under a field of view of the charged particle column; taking a first image of the feature with the column tilted at the first tilt angle and first rotational angle and taking a second image of the feature with the column is tilted at a second tilt angle, different than the first tilt angle, and a second rotational angle; and using stereoscopic measurement techniques to determine the depth of the feature based on the first and second images and the calculated tilt angle and calculated rotational angle.
A method of determining a depth of a feature formed in a first region of a sample, by: positioning a test structure with known dimensions in a processing chamber having a charged particle column tilted at a first tilt angle and first rotational angle; determining the first tilt angle and first rotational angle by: taking an image of the test structure with the charged particle column tilted at the first tilt angle and the first rotational angle, measuring, based on the image, distances between multiple edges of the test structure aligned with each other along a vector, determining ratios between the measured distances, and determining a calculated tilt angle and a calculated rotational angle of charged particle column from the ratios and the known dimensions of the structure; transferring the test structure out of the processing chamber and positioning the sample in the processing chamber such that the first region is under a field of view of the charged particle column; taking a first image of the feature with the column tilted at the first tilt angle and first rotational angle and taking a second image of the feature with the column is tilted at a second tilt angle, different than the first tilt angle, and a second rotational angle; and using stereoscopic measurement techniques to determine the depth of the feature based on the first and second images and the calculated tilt angle and calculated rotational angle.
H01J 37/22 - Optical or photographic arrangements associated with the tube
H01J 37/244 - DetectorsAssociated components or circuits therefor
H01J 37/26 - Electron or ion microscopesElectron- or ion-diffraction tubes
H01J 37/28 - Electron or ion microscopesElectron- or ion-diffraction tubes with scanning beams
H01J 37/20 - Means for supporting or positioning the object or the materialMeans for adjusting diaphragms or lenses associated with the support
G01N 23/04 - Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups , or by transmitting the radiation through the material and forming images of the material
G01N 23/2251 - Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups , or by measuring secondary emission from the material using electron or ion microprobes using incident electron beams, e.g. scanning electron microscopy [SEM]
A pulse stretcher unit, and a respecting inspection system are disclosed. The pulse stretcher unit comprises a selected number of beam splitters arranged along a selected main path and comprising an input beam splitter, an output beam splitter and one or more intermediate beam splitters, and an arrangement of light reflecting surfaces defining a selected number of n auxiliary paths extending between said selected number of beam splitters. Wherein said selected number of beam splitters direct input beam between said selected main path and said selected number of auxiliary paths for splitting an input pulse into a series of pulses having generally equal amplitude. And wherein lengths of said auxiliary paths follow approximately a series of the form L/2k for k=0, 1, 2, where L is a selected length of an auxiliary path.
A system for examining a semiconductor specimen that includes a plurality of layers at respective different depths, and a plurality of holes. Each hole has a top portion at the surface of the specimen, and a bottom portion accommodated in one of the layers. The system includes a processing and memory circuitry (PMC) configured to provide an inspection image indicative of the holes, and process a hole image in the inspection image, without using a shape characterizing model. The processing includes segmenting the inspection image and determining data indicative of a contour of the top portion of the hole, and further segmenting the inspection image and determining data indicative of a contour of a shape enclosed within the contour of the top of the hole.
G06V 10/46 - Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]Salient regional features
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
48.
OPTIMIZATION OF A METROLOGY ALGORITHM FOR EXAMINATION OF SEMICONDUCTOR SPECIMENS
There is provided a metrology system and method. The method includes obtaining a set of tool parameters selected from multiple tool parameters characterizing the examination tool, varying a value of each tool parameter from the set a number of times, giving rise to a plurality of tool settings corresponding to a plurality of combinations of varying values of the set of tool parameters, configuring an examination tool with each given tool setting of the plurality of tool settings; and in response to receiving, from the examination tool, a plurality of sets of images corresponding to the plurality of tool settings and representing expected tool variations over time in a single tool or between different tools, optimizing a metrology algorithm using the plurality of sets of images so as to meet at least one metrology metric including tool matching.
A substrate safety system that includes (i) a control unit that is configured to trigger a substrate recovery related procedure; (ii) a sensing unit that is configured to generate, during an execution of the substrate recovery related procedure, sensed information that is indicative of one or more regions that are associated with a substrate handling station of a substrate evaluation system; (iii) an AI processing unit that is configured to apply an AI process on the sensed information to determine a recovery related status of the substrate; and (iv) a response unit that is configured to respond to the recovery related status of the substrate.
There is provided a system and method of semiconductor specimen examination. The method includes obtaining a plurality of images of a semiconductor specimen acquired by an examination tool; processing the plurality of images using a first machine learning (ML) model for defect detection, thereby obtaining, from the plurality of images, a set of images labeled with detected defects, wherein the first ML model is previously trained using a first training set comprising a subset of synthetic defective images each containing one or more synthetic defects, and a subset of nominal images; and training a second ML model using a second training set comprising at least part of the set of images labeled with detected defects, wherein the second ML model, upon being trained, is usable for defect detection with improved detection performance with respect to the first ML model.
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 10/70 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning
G06V 20/70 - Labelling scene content, e.g. deriving syntactic or semantic representations
A system for discharging a region of a sample, the system includes (i) illumination optics that is configured to discharge the region by illuminating the region of the sample with a laser pulse during an illumination iteration; and (ii) a timing circuit that is configured to trigger the illumination iteration to occur at a timing that is based on one or more timing constraints associated with a scanning of the region by an electron beam.
There is provided a system and method of examining a defect buried in a semiconductor specimen. The method comprises: scanning the semiconductor specimen using an electron beam with a given landing energy (LE); generating image data by collecting backscattered electrons (BSEs) emitted from the specimen at a specific escape energy (EE), wherein the specific EE is selected from a series of EEs corresponding to the given LE based on a relationship representative of expected measurements obtained at the series of EEs for different expected depths of the defect in the specimen; obtaining a measurement related to the defect based on the image data; and estimating an actual depth of the defect in the specimen based on the measurement and the relationship.
Disclosed herein is a system for non-destructive tomography of specimens. The system includes a scanning electron microscope (SEM) and a processor(s). The SEM is configured to obtain a sinogram of a tested specimen, parameterized by a vector {right arrow over (s)}, by projecting e-beams on the tested specimen, at each of a plurality of projection directions and offsets, and. for each e-beam, measuring a respective intensity of electrons returned from the tested specimen, The processor(s) is configured to obtain a tomographic map, pertaining to the tested specimen, by determining values indicative of components of a vector {right arrow over (t)} defined by an equation W{right arrow over (t)}={right arrow over (s)}. W is a matrix with components wij specifying a contribution of a j-th voxel in a nominal specimen to an i-th element of a nominal sinogram of the nominal specimen. The matrix W accounts for e-beam expansion and attenuation with depth within the nominal specimen.
Multiple electron beam optics that includes a detection unit that comprises an array of sensors, and a cross talk reduction unit. For each sensor of multiple sensors of the array of sensors: (i) the sensor includes an aperture and a sensing region that is configured to sense relevant backscattered electrons, the relevant backscattered electrons are emitted from the sample as a result of an illumination of the sample with a primary electron beam that is associated with the sensor and passed through the aperture; and (ii) the crosstalk reduction unit is configured to at least partially prevent a detection, by the sensor, of cross talk backscattered electrons, the cross talk backscattered electrons are emitted from the sample as result of an illumination of the sample by one or more primary beams not associated with the sensor.
An electron beam spot shape reconstruction unit that includes a processing circuit and a memory unit. The processing circuit is configured to reconstruct a shape of an electron beam spot by (i) obtaining multiple groups of images of circular targets of a sample, wherein different groups of images of the multiple groups of images are associated with different polar angles; (ii) processing at least two of the multiple groups of images to determine first-axis edge width information and second-axis edge width information; and (iii) reconstructing the electron beam spot shape based on the first-axis edge width information and second-axis edge width information.
A positioning system that includes (a) a linear motor that includes a movable magnetic unit and a coil stator, the coil stator includes a group of coil stator segments; wherein the mechanical support unit is mechanically coupled to the movable magnetic unit; (b) a mechanical support element for supporting a sample within a vacuum chamber; (c) a power supply that is configured to independently supply power to different coil stator segments of the coil stator segments to induce a movement of the movable magnetic unit in relation to the coil stator, along a axis; (d) a heat reduction element that is configured to reduce a temperature of the coil stator; and (e) a controller that is configured to control the movement of the movable magnetic unit by controlling the supply of power to the different coil stator segments.
A method and a system for illuminating a substrate, the system may include an acousto-optic device (AOD); and an etendue expanding optical module. The AOD may include a surface having an illuminated region; wherein the illuminated region is configured to receive a collimated input beam while being fed with a control signal that causes the illuminated region to output illuminated region output beams that are collimated and exhibit deflection angles that scan, during a scan period, a deflection angular range. The etendue expanding optical module is configured to convert the illuminated region output beams to collimated output beams that impinge on an output aperture; wherein a collimated output beam has a width that exceeds a width of an illuminated region output beam; and wherein the etendue expanding optical module comprises a Dammann grating that is configured to output diffraction patterns, each diffraction pattern comprises diffraction orders that cover a continuous angular range.
A method of delayering a sample that includes a second layer formed under a first layer, where the first and second layers are different materials or different texture, the method including: acquiring a plurality of gray scale images of the region of interest in an iterative process by alternating a sequence of delayering the region of interest with a first charged particle beam and imaging a surface of the region of interest with a second charged particle beam; after each iteration of acquiring a gray scale image, calculating an entropy of the acquired gray scale image and calculating a second derivative of the entropy; determining whether a transition from the first layer to the second layer occurred based on the second derivative of the entropy; and if it is determined that a transition from the first layer to the second layer did not occur, proceeding with a next iteration of acquiring a plurality of gray scale images, and if it is determined that a transition from the first layer to the second layer did occurred, end pointing the delayering process.
A method of delayering a sample that includes a second layer formed under a first layer, where the first and second layers are different materials or different texture, the method including: acquiring a plurality of gray scale images of the region of interest in an iterative process by alternating a sequence of delayering the region of interest with a first charged particle beam and imaging a surface of the region of interest with a second charged particle beam; after each iteration of acquiring a gray scale image, calculating an entropy of the acquired gray scale image and calculating a second derivative of the entropy; determining whether a transition from the first layer to the second layer occurred based on the second derivative of the entropy; and if it is determined that a transition from the first layer to the second layer did not occur, proceeding with a next iteration of acquiring a plurality of gray scale images, and if it is determined that a transition from the first layer to the second layer did occurred, end pointing the delayering process.
H01J 37/28 - Electron or ion microscopesElectron- or ion-diffraction tubes with scanning beams
H01J 37/20 - Means for supporting or positioning the object or the materialMeans for adjusting diaphragms or lenses associated with the support
H01J 37/22 - Optical or photographic arrangements associated with the tube
G01N 23/04 - Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups , or by transmitting the radiation through the material and forming images of the material
60.
FLOW FOR HIGH RESOLUTION STEREOSCOPIC MEASUREMENTS
A method of determining a depth of a hole milled into a first region of a sample, comprising: positioning the sample in a processing chamber having a charged particle beam column; milling a hole in the first region of the sample using a charged particle beam generated by the charged particle beam column; identifying a first registration mark at an upper level of the milled hole; identifying a second registration mark at a lower level of the milled hole; taking a first set of images at a first tilt angle, the first set of images including a first image taken with a field of view that captures the first registration mark but not the second registration mark, and a second image taken with a field of view that captures the second registration mark but not the first registration mark; taking a second set of images at a second tilt angle, different than the first tilt angle, the second set of images including a third image taken with a field of view that captures the first registration mark but not the second registration mark, and a fourth image taken with a field of view that captures the second registration mark but not the first registration mark; using stereoscopic measurement techniques to determine the depth of the hole based on the first and second sets of images.
A method of determining a depth of a hole milled into a first region of a sample, comprising: positioning the sample in a processing chamber having a charged particle beam column; milling a hole in the first region of the sample using a charged particle beam generated by the charged particle beam column; identifying a first registration mark at an upper level of the milled hole; identifying a second registration mark at a lower level of the milled hole; taking a first set of images at a first tilt angle, the first set of images including a first image taken with a field of view that captures the first registration mark but not the second registration mark, and a second image taken with a field of view that captures the second registration mark but not the first registration mark; taking a second set of images at a second tilt angle, different than the first tilt angle, the second set of images including a third image taken with a field of view that captures the first registration mark but not the second registration mark, and a fourth image taken with a field of view that captures the second registration mark but not the first registration mark; using stereoscopic measurement techniques to determine the depth of the hole based on the first and second sets of images.
G01N 23/2251 - Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups , or by measuring secondary emission from the material using electron or ion microprobes using incident electron beams, e.g. scanning electron microscopy [SEM]
G01N 23/2204 - Specimen supports thereforSample conveying means therefor
G01B 15/00 - Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons
62.
MACHINE LEARNING BASED DEFECT EXAMINATION FOR SEMICONDUCTOR SPECIMENS
There is provided a system and method of examination a semiconductor specimen. The method includes obtaining a runtime image of the specimen; processing the runtime image using a first machine learning (ML) model to extract a set of runtime features representative of a set of patches in the runtime image; and comparing the set of runtime features with a bank of reference features, giving rise to an anomaly map indicative of one or more defective patches in the runtime image. The bank of reference features is previously generated by obtaining a plurality of synthetic reference images generated by a second ML model based on a plurality of actual images; and processing the plurality of synthetic reference images by the first ML model to extract, for each synthetic reference image, a set of reference features representative thereof, giving rise to the bank of reference features.
A sample related system that includes a vacuum chamber, a load lock chamber that includes a first port that is interfaces with a first environment having a first pressure; a second port that interfaces with a second environment that comprises the vacuum chamber; a load lock chamber pressure control unit that is configured to control a pressure within the load lock chamber; and a mass measurement unit that is configured measure a mass of the sample, during at least one point in time, wherein during each point of time of the at least one point in time the load lock chamber is at a load lock chamber vacuum level. The load lock chamber is mechanically isolated from an environment of the sample related system. The vacuumed chamber is for performing a sample related operations elected out of sample evaluation or sample processing.
A high voltage noise reduction unit that includes (i) an input that is configured to receive a high voltage input signal (HVIS); (ii) a positive isolated supply unit that is configured to receive the HVIS and to output a positive supply signal that floats on the HVIS; (iii) a negative isolated supply unit that is configured to receive the HVIS and to output a negative supply signal that floats on the HVIS; (iv) a low pass filter that is configured to filter the HVIS to provide a filtered high voltage signal; and (v) an amplifier that is configured to receive the positive supply signal, to receive the negative supply signal, to receive the filtered high voltage signal and amplify the filtered high voltage signal to provide a high voltage output signal.
A chuck that supports a sample in a processing chamber and comprises: a support plate formed from a dielectric material, the support plate including an upper planar support surface sized and shaped to retain a substrate disposed on the support plate; one or more electrodes disposed within the support plate proximate the upper planar support surface; a plurality of lift pin holes formed completely through the support plate; a plurality of stub cavities formed within the support plate, each stub cavity having an opening at the upper planar support surface; a plurality of retractable stubs corresponding in number to the plurality of stub cavities, wherein each retractable stub is disposed in a unique one of the stub cavities; and a stub lift mechanism operable to move each retractable stub in the plurality of stubs between a down position and an up position, wherein in the down position a distal end of the retractable stub is disposed within its respective stub cavity and recessed below the upper planar support surface and the up position the distal end of the retractable stub protrudes above the upper planar support surface through the stub cavity opening.
G01N 23/2204 - Specimen supports thereforSample conveying means therefor
G01N 23/225 - Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups , or by measuring secondary emission from the material using electron or ion microprobes
There are provided systems and methods comprising obtaining design data of each of a plurality of given overlay targets comprising a plurality of stacked layers, using at least part of the design data to simulate image data of each given overlay target that would have been acquired by an electron beam examination system, using the image data to determine, before actual manufacturing of each given overlay target, second data informative of estimated probability that each given overlay target, upon being manufactured according to the design data, provides measurement data in an overlay measurement process meeting a measurement quality criterion, and using the second data of each given overlay target to select at least one optimal overlay target among the plurality of different overlay targets, wherein the at least one optimal overlay target is usable to be actually manufactured on the semiconductor specimen.
There are provided systems and methods comprising, for each given overlay target of a plurality of different overlay targets to be manufactured on a semiconductor specimen, said given overlay target comprising a plurality of stacked semiconductor layers, obtaining a design image of the given overlay target, feeding the design image to a trained machine learning model, to simulate at least one image of the given overlay target that would have been acquired by an electron beam examination system, using the at least one image to determine, before actual manufacturing of the given overlay target, data informative of at least one simulated overlay in the image, and using the data informative of the at least one simulated overlay of each given overlay target to select at least one optimal overlay target among the plurality of different overlay targets, the optimal overlay target being usable to be manufactured on the semiconductor specimen.
A chuck that supports a sample in a processing chamber and comprises: a support plate formed from a dielectric material, the support plate including an upper planar support surface sized and shaped to retain a substrate disposed on the support plate; one or more electrodes disposed within the support plate proximate the upper planar support surface; a plurality of lift pin holes formed completely through the support plate; a plurality of stub cavities formed within the support plate, each stub cavity having an opening at the upper planar support surface; a plurality of retractable stubs corresponding in number to the plurality of stub cavities, wherein each retractable stub is disposed in a unique one of the stub cavities; and a stub lift mechanism operable to move each retractable stub in the plurality of stubs between a down position and an up position, wherein in the down position a distal end of the retractable stub is disposed within its respective stub cavity and recessed below the upper planar support surface and the up position the distal end of the retractable stub protrudes above the upper planar support surface through the stub cavity opening.
H01J 37/20 - Means for supporting or positioning the object or the materialMeans for adjusting diaphragms or lenses associated with the support
H01L 21/683 - Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereofApparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components for supporting or gripping
An illumination module of a wafer inspection system including: an illumination source providing ultraviolet illumination with wavelengths below 300 nm; a pulse cascader, optically coupled to the illumination source to receive the ultraviolet illumination, which pulse cascade including a chain of a plurality of loops, each loop including: a loop input and a loop output, a first loop output optically coupled to a loop input of a subsequent loop in the chain; and a delay line having: a delay line input optically coupled to the loop input; and a delay line output, the delay line configured to output a delay line light output, from the delay line output, including an image of light received at the delay line input, after a time delay from a time of receipt of light received at the delay line input; and a splitter configured to receive light at a splitter input and output a first portion of the light from the loop through a loop output and to pass a second portion of the light to the delay line input.
G02B 26/04 - Optical devices or arrangements for the control of light using movable or deformable optical elements for controlling the intensity of light by periodically varying the intensity of light, e.g. using choppers
70.
OPTICAL INSPECTION SYSTEMS WITH PULSED LIGHT SOURCES AND PULSE MULTIPLEXING
Implementations disclosed describe, among other things, a sample inspection system that includes an illumination subsystem to illuminate a sample with a plurality of time-spaced light pulses generated, using a pulse multiplexing system, from a source light pulse. The pulse multiplexing system includes a plurality of optical loops, each deploying an optical coupler that outputs a first portion of incident light to a sample and provides a second portion of incident light as an input into the next optical loop. The sample inspection system further includes a collection subsystem to collect a portion of light generated upon interaction of the plurality of time-spaced light pulses with the sample, and a light detection subsystem to detect the collected portion of light.
The presently disclosed subject matter provides a method for aligning an objective and a pupil relay module of a microscope. The objective is configured to introduce an objective aberration component and the pupil relay module is configured to have a corresponding pupil relay module aberration component such that the pupil relay module aberration component compensates said objective aberration component when the pupil relay module is accurately aligned with the objective. The method comprises: (a) measuring a combined aberration indicator indicative of a combined aberration resulting from the optical combination of the objective and pupil relay module; (b) adjusting an optical alignment of the objective and pupil relay module based on the measured combined aberration indicator; (c) iterating (a) and (b) until the measured combined aberration indicator reaches a predetermined combined aberration indicator target thereby achieving accurate alignment.
There is provided a system and method of examination of a semiconductor specimen. The method includes obtaining an e-beam image representative of a given layer of a given structure on the specimen in runtime, processing at least the e-beam image using a ML model, and obtaining yield related prediction with respect to the given structure prior to performing an electrical test. The ML model is previously trained using a training set comprising multiple stacks of e-beam images corresponding to multiple sites of the given structure on one or more training specimens, each stack of e-beam images representative of the at least given layer of a respective site; and test data acquired from an electrical test performed at the multiple sites and related to actual yield of the training specimens, the test data respectively correlated with the stacks of e-beam images and used as ground truth thereof.
G06N 3/04 - Architecture, e.g. interconnection topology
G06N 3/082 - Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections
H01J 37/22 - Optical or photographic arrangements associated with the tube
H01J 37/28 - Electron or ion microscopesElectron- or ion-diffraction tubes with scanning beams
H01L 21/67 - Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereofApparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components
73.
MACHINE LEARNING BASED EXAMINATION FOR PROCESS MONITORING
There is provided a system and method of examination of semiconductor specimens. The method includes generating a sequence of anomaly scores corresponding to a sequence of specimens sequentially fabricated and examined during a fabrication process, comprising, for each given specimen: obtaining an image of the given specimen acquired by an examination tool; using a machine learning (ML) model to process the image and obtaining an anomaly map indicative of pattern variation in the image; and deriving, based on the anomaly map, an anomaly score indicative of level of pattern variation presented in the given specimen, wherein the anomaly score is correlated with a defectivity score related to defect detection in a correlation relationship, and has higher detection sensitivity than the defectivity score; and analyzing the sequence of anomaly scores to monitor on-going process stability, thereby providing defect related prediction along the fabrication process based on the correlation relationship.
G01N 21/88 - Investigating the presence of flaws, defects or contamination
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 10/70 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning
A system that includes a vacuum module that includes a first vacuum source, a first vacuum propagation path, a second vacuum source, and a second vacuum propagation path. The first vacuum source is configured to provide first vacuum of a first vacuum level, via the first vacuum propagation path, to a chuck. The chuck is mounted on a mechanical stage. The second vacuum source is configured to provide second vacuum at a second vacuum level, via the second vacuum propagation path, to the chuck. The second vacuum level exceeds the first vacuum level. The chuck is configured to apply at least one of the first vacuum or the second vacuum to the wafer. The first vacuum propagation path is configured to follow movements of the chuck. The second vacuum propagation path is configured to remain static despite the movements of the chuck.
H01L 21/683 - Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereofApparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components for supporting or gripping
H01L 21/68 - Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereofApparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components for positioning, orientation or alignment
H01L 21/687 - Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereofApparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components for supporting or gripping using mechanical means, e.g. chucks, clamps or pinches
A wafer inspection tool comprising an illumination system having: a field of view (FOV); a light source pupil having a size and shape; a central optical axis; and one or more field angle defining a shape of said FOV extending away from said light source pupil; an objective lens arrangement including an objective and a plurality of interchangeable telescopes coupled thereto, the objective lens arrangement being configured to collect light reflected off a plurality of field points on the wafer and to onwardly transmit a light beam formed from the collected light; and a light separator having a first reflective surface with a transmissive region formed therein and a second surface, wherein said transmissive region is arranged to allow therethrough a central portion of said light beam transmitted from said objective lens arrangement corresponding to the brightfield channel while said reflective surface is arranged to reflect a peripheral portion of said light beam transmitted from said objective lens arrangement corresponding to the darkfield channel; a relay module configured to relay said light source pupil to said transmissive region; wherein said transmissive region has a shape defined as a geometric intersection volume between a model of said illumination light and said reflective surface and said second surface; wherein said model includes a plurality of solids each solid having a cross section of said light source pupil and angled to a field angle of said one or more field angle.
Disclosed herein is a system for non-destructive classification of specimens. The system includes an e-beam source, an X-ray measurement module, and a computational module. The e-beam source is configured to project e-beams on a specimen at one or more e-beam landing energies, so as to penetrate the specimen and induce emission of X-rays. The X-ray measurement module is configured to measure the emitted X-rays. The computational module is configured to process the measurement data to obtain an energy signature of at least one target substance included in the specimen and classify the inspected specimen based on the obtained energy signature and one or more reference energy signatures pertaining to one or more reference specimens, respectively.
A polarizer system is described. The polarizer system comprises at least one polarization beam splitter, a polarization rotator, and a beam combiner. The at least one polarization beam splitter is positioned to receive input radiation beam and to split the input radiation beam directing a first beam portion having a first linear polarization orientation along a first path and a second beam portion having a second linear polarization orientation orthogonal to said first linear polarization orientation along a second path. The polarization rotator is located along said second path and configured to rotate polarization of said beam portion to be parallel to said first linear polarization orientation. The beam combiner is configured and positioned to combine said first and second beam portions to form a common beam having said first linear polarization orientation propagating along a selected optical path.
A method of evaluating, with an evaluation tool that includes a first charged particle column, a region of interest on a sample that includes an array of holes separated by solid portions, the method comprising: positioning the sample such that the region of interest is under a field of view of the first charged particle column; and locally depositing material within the array of holes in the region of interest by: pulsing a flow of deposition gas to the region of interest by turning the flow of the deposition gas ON and then OFF; thereafter, scanning a charged particle beam generated by the first charged particle column across the region of interest; and iteratively repeating the pulsing and scanning steps a plurality of times to locally deposit material within the array of holes in the region of interest.
A system for evaluating manufactured items that includes a memory module; an evaluation unit configured to execute instructions related to the evaluating of the manufactured items while applying a group of features; and a memory leakage unit configured to: select a first feature out of the group of features and disable an execution, by the evaluation unit, of instructions associated with the first feature at a presence of a memory leakage event. The first feature has a priority that is lower than a priority of a second feature of the group of feature. Priorities of features of the group of features are determined based on (i) priority information provided by one or more developers of the instructions related to the evaluating of the manufactured item, and (ii) usage information indicative of usage of the features of the group of features by the evaluation unit.
A device for discharging an electrostatic chuck located within a vacuum chamber, the device includes a plasma distribution unit that is configured to receive plasma from an external plasma source that is located outside the vacuum chamber, and perform a distribution of the plasma within the vacuum chamber that discharges the electrostatic chuck. The device also includes a controller for controlling the distribution of the plasma; wherein the distribution of the plasma occurs during a plasma distribution period that is shorter than a duration of a plasma based cleaning process of the electrostatic chuck.
H01J 37/02 - Discharge tubes with provision for introducing objects or material to be exposed to the discharge, e.g. for the purpose of examination or processing thereof Details
H01J 37/20 - Means for supporting or positioning the object or the materialMeans for adjusting diaphragms or lenses associated with the support
A method for phase retrieval, the method may include (a) obtaining multiple out-of-focus intensity images of one or more point spread function targets; wherein the out-of-focus intensity images are generated by based on residual collected light signals obtained by a residual collection channel of an optical unit having a numerical aperture that exceeds 0.8; and (b) calculating phase information, based on the multiple out-of-focus intensity images and on a vectorial model of the point spread function.
A method of milling a diagonal cut in a region of a sample, the method comprising: positioning the sample in a processing chamber having a charged particle beam column; moving the region of the sample under a field of view of the charged particle column; generating a charged particle beam with the charged particle beam column and scanning the charged particle beam over the region of the sample along scan lines arranged parallel to a slope of the diagonal cut; and repeating the generating and scanning step a plurality of times to mill the diagonal cut in the region of the sample; wherein, for each iteration of the generating and scanning steps, a velocity of the charged particle beam is slower when the beam is near a deep end of the diagonal cut than when the beam is near a shallow end of the diagonal cut.
There is provided a system and method of examining a specimen. The method comprises obtaining an actual measurement in response to scanning the specimen using a set of scanning parameters with predefined values; obtaining a simulated measurement based on design data; comparing the actual measurement with the simulated measurement to identify a deviation with respect to a predefined tolerance; identifying at least one structural property as root cause of the deviation by: obtaining one or more additional actual measurements in response to scanning the specimen using one or more varying values of at least one scanning parameter; and providing the actual measurement and the additional actual measurements to a simulation model representative of simulated measurement distribution in a multi-dimensional property space characterized by the structural properties of the plurality of layers and the at least one scanning parameter, thereby identifying the at least one structural property.
There are provided methods and systems to automatically determine, for acquisition by an examination system, of a plurality of regions covering a plurality of dies of a specimen, along a first direction and/or along a second direction orthogonal to the first direction. The dimension of the region along the first direction is selected to enable optimizing a total level of overlap of slices acquired by the examination system to cover the plurality of regions. The dimension of the region along the second direction enables maximizing a total parallel computation power used by the examination system to process an image of each region.
A method of evaluating a region of interest of a sample with a sample evaluation tool that includes a focused ion beam (FIB) column, a scanning electron microscope (SEM) column, and an atomic force microscope (AFM) instrument, the method comprising: transferring the sample into in a vacuum chamber of the sample evaluation tool; acquiring a plurality of two-dimensional images of the region of interest over a plurality of iterations of a delayering process by: (a) positioning the region of interest under a field of view of the FIB column; (b) milling a layer of material from the region of interest with the FIB column; (c) moving the region of interest under a field of view of the SEM column; (d) imaging the region of interest with the SEM column and measuring a depth of the milled layer in the region of interest with the AFM instrument; and repeating steps (a)-(d) a plurality of times without removing the sample from the vacuum chamber.
G01Q 60/24 - AFM [Atomic Force Microscopy] or apparatus therefor, e.g. AFM probes
G01N 23/2251 - Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups , or by measuring secondary emission from the material using electron or ion microprobes using incident electron beams, e.g. scanning electron microscopy [SEM]
G01N 23/2255 - Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups , or by measuring secondary emission from the material using electron or ion microprobes using incident ion beams, e.g. proton beams
H01L 21/66 - Testing or measuring during manufacture or treatment
A method of evaluating a region of interest of a sample with a sample evaluation tool that includes a focused ion beam (FIB) column, a scanning electron microscope (SEM) column, and an atomic force microscope (AFM) instrument, the method comprising: transferring the sample into in a vacuum chamber of the sample evaluation tool; acquiring a plurality of two-dimensional images of the region of interest over a plurality of iterations of a delayering process by: (a) positioning the region of interest under a field of view of the FIB column; (b) milling a layer of material from the region of interest with the FIB column; (c) moving the region of interest under a field of view of the SEM column; (d) imaging the region of interest with the SEM column and measuring a depth of the milled layer in the region of interest with the AFM instrument; and repeating steps (a)-(d) a plurality of times without removing the sample from the vacuum chamber.
There is provided a method and a system in which a processing circuitry is configured to obtain an inspection image representative of 2D information of an inspection area of a semiconductor specimen, and feed the inspection image to a trained machine learning model operative to segment the inspection image into at least a first segment S′1 and a second segment S′2, wherein the first segment S′1 corresponds to a first region of the inspection area which has a height profile pattern corresponding to a first height profile pattern, and the second segment S′2 corresponds to a second region of the area which has a height profile pattern corresponding to a second height profile pattern, wherein the first height profile pattern is different from the second height profile pattern.
A method of operating a substrate processing system that includes a substrate processing chamber, a substrate storage container and robot configured to select a substrate from the substrate storage container and transfer a selected substrate into the substrate processing chamber, the method comprising: detecting a lower edge and upper edge of the substrate; calculating a thickness of the substrate based on the detected lower and upper edges of the substrate; comparing the calculated thickness of the substrate to an expected thickness of the substrate; and (i) if the calculated thickness matches the expected thickness, controlling the robot to transfer the substrate into the substrate processing chamber, (ii) if the calculated thickness does not match the expected thickness, generating an alert indicating a thickness mismatch.
H01L 21/67 - Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereofApparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components
H01L 21/677 - Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereofApparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components for conveying, e.g. between different work stations
G01B 21/08 - Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring length, width, or thickness for measuring thickness
89.
USING LASER BEAM FOR SEM BASE TOOLS, WORKING DISTANCE MEASUREMENT AND CONTROL WORKING DISTANCE SEM TO TARGET
A system for processing a sample comprising: a vacuum chamber having a window formed along one of its walls; a sample support configured to hold a sample within the vacuum chamber during a sample processing operation and move the substrate within the vacuum chamber along the X, Y and Z axes; a charged particle beam column configured to direct a charged particle beam into the vacuum chamber and focus the beam to collide with a region of interest on the sample; an optical distance measurement device configured to generate and direct electromagnetic radiation into the vacuum chamber through the window, detect photons from the electromagnetic radiation reflected off the sample, and determine a working distance between the sample and charged particle column based on the generated electromagnetic radiation and the detected photons; and one or more mirrors disposed within the vacuum chamber and positioned to direct the electromagnetic radiation generated by the optical distance measurement system to a measured location on the sample that is in close proximity to the region of interest, the one or more mirrors comprising at least one mirror positioned directly under a portion of the charged particle column.
A system for processing a sample comprising: a vacuum chamber having a window formed along one of its walls; a sample support configured to hold a sample within the vacuum chamber during a sample processing operation and move the substrate within the vacuum chamber along the X, Y and Z axes; a charged particle beam column configured to direct a charged particle beam into the vacuum chamber and focus the beam to collide with a region of interest on the sample; an optical distance measurement device configured to generate and direct electromagnetic radiation into the vacuum chamber through the window, detect photons from the electromagnetic radiation reflected off the sample, and determine a working distance between the sample and charged particle column based on the generated electromagnetic radiation and the detected photons; and one or more mirrors disposed within the vacuum chamber and positioned to direct the electromagnetic radiation generated by the optical distance measurement system to a measured location on the sample that is in close proximity to the region of interest, the one or more mirrors comprising at least one mirror positioned directly under a portion of the charged particle column.
H01J 37/20 - Means for supporting or positioning the object or the materialMeans for adjusting diaphragms or lenses associated with the support
G01N 23/2251 - Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups , or by measuring secondary emission from the material using electron or ion microprobes using incident electron beams, e.g. scanning electron microscopy [SEM]
A method of operating a substrate processing system that includes a substrate processing chamber, a substrate storage container and robot configured to select a substrate from the substrate storage container and transfer a selected substrate into the substrate processing chamber, the method comprising detecting a lower edge and upper edge of the substrate, calculating a thickness of the substrate based on the detected lower and upper edges of the substrate, comparing the calculated thickness of the substrate to an expected thickness of the substrate, and (i) if the calculated thickness matches the expected thickness, controlling the robot to transfer the substrate into the substrate processing chamber, (ii) if the calculated thickness does not match the expected thickness, generating an alert indicating a thickness mismatch.
H01L 21/67 - Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereofApparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components
B65G 47/90 - Devices for picking-up and depositing articles or materials
H01J 37/20 - Means for supporting or positioning the object or the materialMeans for adjusting diaphragms or lenses associated with the support
H01J 37/244 - DetectorsAssociated components or circuits therefor
H01J 37/28 - Electron or ion microscopesElectron- or ion-diffraction tubes with scanning beams
H01L 21/677 - Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereofApparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components for conveying, e.g. between different work stations
H01L 21/687 - Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereofApparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components for supporting or gripping using mechanical means, e.g. chucks, clamps or pinches
92.
IMPROVED PRECISION IN STEREOSCOPIC MEASUREMENTS USING A PRE-DEPOSITION LAYER
A method of determining the depth of a hole milled into a first region of a sample, the method comprising: positioning the sample in a processing chamber having a charged particle beam column; depositing material directly over a top surface of the sample in a second region of the sample adjacent to the first region; milling the hole in the first region of the sample using a charged particle beam generated by the charged particle beam column, wherein the hole abuts the material deposited over the top surface and includes a sidewall that extends from a bottom surface of the hole to an interface between the deposited material and the top surface of the sample; and using stereoscopic measurement techniques to calculate the depth of the hole based on distance measurements between a first point along an interface between the material and the top surface and a second point along a bottom surface of the hole.
G01B 15/00 - Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons
G01N 23/2251 - Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups , or by measuring secondary emission from the material using electron or ion microprobes using incident electron beams, e.g. scanning electron microscopy [SEM]
H01J 37/30 - Electron-beam or ion-beam tubes for localised treatment of objects
H01J 37/305 - Electron-beam or ion-beam tubes for localised treatment of objects for casting, melting, evaporating, or etching
93.
IMAGE DENOISING FOR EXAMINATION OF A SEMICONDUCTOR SPECIMEN
There is provided an image generation system and method. The method comprises obtaining a runtime image of a semiconductor specimen with a low Signal-to-noise ratio (SNR), and processing the runtime image using a machine learning (ML) model to obtain an output image with a high SNR. The ML model is previously trained using a training set comprising a plurality of low SNR images associated with a high SNR image. The plurality of low SNR images correspond to a plurality of sequences of frames acquired in a plurality of runs of scanning a first site of the specimen. The high SNR image is generated based on the plurality of low SNR images. The training comprises, for each low SNR image: processing the low SNR image by the ML model to obtain predicted image data, and optimizing the ML model based on the predicted image data and the high SNR image.
A method of determining the depth of a hole milled into a first region of a sample, the method comprising: positioning the sample in a processing chamber having a charged particle beam column; depositing material directly over a top surface of the sample in a second region of the sample adjacent to the first region; milling the hole in the first region of the sample using a charged particle beam generated by the charged particle beam column, wherein the hole abuts the material deposited over the top surface and includes a sidewall that extends from a bottom surface of the hole to an interface between the deposited material and the top surface of the sample; and using stereoscopic measurement techniques to calculate the depth of the hole based on distance measurements between a first point along an interface between the material and the top surface and a second point along a bottom surface of the hole.
A method for evaluating an impedance related value of a structure of a sample, the method includes: (i) performing a first illumination iteration that includes charging the structure with an illumination iteration charge; (ii) performing a second illumination iteration that includes imaging the structure to provide an image of the structure; a value of the illumination iteration charge and a value of a time difference between step (i) and step (ii) are determined to introduce a dependency between an impedance of the structure and the image of the structure; wherein steps (i) and (ii) are executed using an electron beam, and (iii) determining the impedance related value of the structure based on the image of the structure. There may be three or more values of the impedance related value.
An indication of a sequence of cleaning operations associated with a substrate process at a manufacturing system is received. An indication of one or more criteria that trigger initiation of the sequence of operations during a process at one or more manufacturing equipment of the manufacturing system is also received. A set of instructions corresponding to the sequence of operations is generated. In response to a detection that at least one of the one or more criteria is satisfied, the generated set of instructions are executed to initiate the sequence of operations at the one or more manufacturing equipment.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
97.
METHOD FOR CREATING A SMOOTH DIAGONAL SURFACE USING A FOCUSED ION BEAM AND AN INNOVATIVE SCANNING STRATEGY
A method of milling a diagonal cut in a region of a sample, the method comprising: positioning the sample in a processing chamber having a charged particle beam column; moving the region of the sample under a field of view of the charged particle column; generating a charged particle beam with the charged particle beam column and scanning the charged particle beam over the region of the sample along scan lines arranged parallel to a slope of the diagonal cut; and repeating the generating and scanning step a plurality of times to mill the diagonal cut in the region of the sample; wherein, for each iteration of the generating and scanning steps, a velocity of the charged particle beam is slower when the beam is near a deep end of the diagonal cut than when the beam is near a shallow end of the diagonal cut.
H01J 37/305 - Electron-beam or ion-beam tubes for localised treatment of objects for casting, melting, evaporating, or etching
H01J 37/147 - Arrangements for directing or deflecting the discharge along a desired path
H01J 37/28 - Electron or ion microscopesElectron- or ion-diffraction tubes with scanning beams
H01J 37/20 - Means for supporting or positioning the object or the materialMeans for adjusting diaphragms or lenses associated with the support
G01N 23/2255 - Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups , or by measuring secondary emission from the material using electron or ion microprobes using incident ion beams, e.g. proton beams
98.
END-TO-END MEASUREMENT FOR SEMICONDUCTOR SPECIMENS
There is provided a system and method for examining a semiconductor specimen. The method includes obtaining a runtime image of the specimen, and providing the runtime image as an input to an end-to-end (E2E) learning model to process, thereby obtaining, as an output of the E2E learning model, runtime measurement data specific for a metrology application. The E2E learning model is previously trained for the metrology application using a training set comprising a plurality of training images of the specimen and respective ground truth measurement data associated therewith, and one or more cost functions specifically configured to evaluate, for the plurality of training images and corresponding training measurement data outputted by the E2E learning model, one or more metrology benchmarks from a group comprising precision, correlation, and matching.
A method of depositing material over a localized region of a sample comprising: positioning a sample within a vacuum chamber such that the localized region is under a field of view of a charged particle beam column; injecting a deposition precursor gas, with a gas injection nozzle, into the vacuum chamber at a location adjacent to the deposition region; generating a charged particle beam with the charged particle beam column and focusing the charged particle beam within the deposition region of the sample; and scanning the charged particle beam across the deposition region of the sample to activate molecules of the deposition gas that have adhered to the sample surface in the deposition region and deposit material on the sample within the deposition region; and applying a negative bias voltage to the gas injection nozzle while the focused ion beam is scanned across the deposition region to alter a trajectory of the secondary electrons and repel the secondary electrons back to the sample surface.
H01J 37/317 - Electron-beam or ion-beam tubes for localised treatment of objects for changing properties of the objects or for applying thin layers thereon, e.g. ion implantation
C23C 14/04 - Coating on selected surface areas, e.g. using masks
C23C 14/18 - Metallic material, boron or silicon on other inorganic substrates
C23C 14/22 - Coating by vacuum evaporation, by sputtering or by ion implantation of the coating forming material characterised by the process of coating
H01J 37/147 - Arrangements for directing or deflecting the discharge along a desired path
H01J 37/30 - Electron-beam or ion-beam tubes for localised treatment of objects
H01L 21/285 - Deposition of conductive or insulating materials for electrodes from a gas or vapour, e.g. condensation
100.
ENHANCED DEPOSITION RATE BY APPLYING A NEGATIVE VOLTAGE TO A GAS INJECTION NOZZLE IN FIB SYSTEMS
A method of depositing material over a localized region of a sample comprising: positioning a sample within a vacuum chamber such that the localized region is under a field of view of a charged particle beam column; injecting a deposition precursor gas, with a gas injection nozzle, into the vacuum chamber at a location adjacent to the deposition region; generating a charged particle beam with the charged particle beam column and focusing the charged particle beam within the deposition region of the sample; and scanning the charged particle beam across the deposition region of the sample to activate molecules of the deposition gas that have adhered to the sample surface in the deposition region and deposit material on the sample within the deposition region; and applying a negative bias voltage to the gas injection nozzle while the focused ion beam is scanned across the deposition region to alter a trajectory of the secondary electrons and repel the secondary electrons back to the sample surface.
G01N 23/225 - Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups , or by measuring secondary emission from the material using electron or ion microprobes
C23C 16/48 - Chemical coating by decomposition of gaseous compounds, without leaving reaction products of surface material in the coating, i.e. chemical vapour deposition [CVD] processes characterised by the method of coating by irradiation, e.g. photolysis, radiolysis, particle radiation
patents
