Abstract: Disclosed herein is a method for depth-profiling of samples including a target region including a lateral structural feature. The method includes projecting an optical pump pulse on a semiconductor device comprising a target region, such as to produce an acoustic pulse which propagates within the target region of the semiconductor device, wherein a wavelength of the pump pulse is at least two times greater than a lateral extent of a lateral structural feature of the semiconductor device along at least one lateral direction, projecting an optical probe pulse on the semiconductor device, such that the probe pulse undergoes Brillouin scattering off the acoustic pulse within the target region, detecting a scattered component of the probe pulse to obtain a measured signal, and analyzing the measured signal to obtain a depth-dependence of at least one parameter characterizing the lateral structural feature.

Abstract: Disclosed herein is a method for detecting defects on a sample. The method includes obtaining scan data of a region of a sample in a multiplicity of perspectives, and performing an integrated analysis of the obtained scan data. The integrated analysis includes computing, based on the obtained scan data, and/or estimating cross-perspective covariances, and determining presence of defects in the region, taking into account the cross-perspective covariances.

Abstract: Disclosed herein is s computer-based method for obtaining and analyzing multi-die scan data of a patterned wafer. The method includes sequentially implementing an operation of scanning a respective plurality of sets of slices on a wafer, and, per each slice segment in a multiplicity of slice segments in the plurality of sets of slices, an operation of performing die-to-multi-die (D2MD) analysis of scan data of the slice segment in order to detect defects in the slice segment. Each set of slices may constitute a subset of the totality of slices on the respective die-column. Sets scanned in a same implementation are analogous to one another, thereby facilitating—in the die-to-multi-die analysis of scan data of a slice segment—taking into account, as reference, scan data of areas on other die-columns, which were scanned in the same implementation.

Abstract: Disclosed herein is a method for non-destructive hybrid acousto-optic and scanning electron microscopy-based metrology. The method includes: (i) obtaining acousto-optic and scanning electron microscopy measurement data of an inspected structure on a sample; (ii) processing the measurement data to extract values of key measurement parameters corresponding to the acousto-optic measurement data and the scanning electron microscopy measurement data, respectively; and (iii) obtaining estimated values of one or more structural parameters of the inspected structure by inputting the extracted values into an algorithm, which is configured to jointly process the extracted values to output estimated values of the one or more structural parameters.

Abstract: Disclosed herein is a system for profiling holes in non-opaque samples. The system includes: (i) an e-beam source configured to project an e-beam into an inspection hole in a sample, such that a wall of the inspection hole is struck and a localized electron cloud is produced; (ii) a light sensing infrastructure configured to sense cathodoluminescent light, generated by the electron cloud; and (iii) a computational module configured to analyze the measured signal to obtain the probed depth at which the wall was struck. A lateral offset, and/or orientation, of the e-beam is controllable, so as to allow generating localized electron clouds at each of a plurality of depths inside the inspection hole, and thereby obtain information at least about a two-dimensional geometry of the inspection hole.

Abstract: Disclosed herein is a system for profiling holes in non-opaque samples. The system includes: (i) an e-beam source configured to project an e-beam into an inspection hole in a sample, such that a wall of the inspection hole is struck and a localized electron cloud is produced; (ii) a light sensing infrastructure configured to sense cathodoluminescent light, generated by the electron cloud; and (iii) a computational module configured to analyze the measured signal to obtain the probed depth at which the wall was struck. A lateral offset, and/or orientation, of the e-beam is controllable, so as to allow generating localized electron clouds at each of a plurality of depths inside the inspection hole, and thereby obtain information at least about a two-dimensional geometry of the inspection hole.

Abstract: Disclosed is a computerized method for detecting defects on a sample. The method includes: (i) receiving scan data corresponding to a pixel on the sample; (ii) computing a difference vector d based on the scan data and corresponding reference data; (iii) computing a parameter D dependent on t=?d?(Glinear/??s?2)?s, wherein ?T?=K?1 with K being a covariance matrix corresponding to the pixel, s is a predetermined kernel characterizing a defect signal, and Glinear=s·(K?1 d) is a gaussian approximation of a likelihood ratio test expression for distinguishing the defect signal from noise, and wherein D substantially monotonically increases with ?t?; and (iv) computing a score q(g, D) indicative of whether the pixel is defective, wherein g is a parameter indicative of a value of Glinear and q(g, D) substantially monotonically increases with g and substantially monotonically decreases with D.

Abstract: A computer-based method for three-dimensional surface metrology of samples based on scanning electron microscopy and atomic force microscopy. The method includes: (i) using a scanning electron microscope (SEM) to obtain SEM data of a set of sites on a surface of a sample; (ii) using an atomic force microscope (AFM) to measure vertical parameters of sites in a calibration subset of the set; (iii) calibrating an algorithm, configured to estimate a vertical parameter of a site when SEM data of the site are fed as inputs, by determining free parameters of the algorithm, such that residuals between the algorithm-estimated vertical parameters and the AFM-measured vertical parameters are about minimized; and (iv) using the calibrated algorithm to estimate vertical parameters of the sites in the complement to the calibration subset.

Abstract: Disclosed herein is s computer-based method for obtaining and analyzing multi-die scan data of a patterned wafer. The method includes sequentially implementing an operation of scanning a respective plurality of sets of slices on a wafer, and, per each slice segment in a multiplicity of slice segments in the plurality of sets of slices, an operation of performing die-to-multi-die (D2MD) analysis of scan data of the slice segment in order to detect defects in the slice segment. Each set of slices may constitute a subset of the totality of slices on the respective die-column. Sets scanned in a same implementation are analogous to one another, thereby facilitating—in the die-to-multi-die analysis of scan data of a slice segment—taking into account, as reference, scan data of areas on other die-columns, which were scanned in the same implementation.

Abstract: Disclosed herein is a method for depth-profiling of samples including a target region including a lateral structural feature. The method includes projecting an optical pump pulse on a semiconductor device comprising a target region, such as to produce an acoustic pulse which propagates within the target region of the semiconductor device, wherein a wavelength of the pump pulse is at least two times greater than a lateral extent of a lateral structural feature of the semiconductor device along at least one lateral direction, projecting an optical probe pulse on the semiconductor device, such that the probe pulse undergoes Brillouin scattering off the acoustic pulse within the target region, detecting a scattered component of the probe pulse to obtain a measured signal, and analyzing the measured signal to obtain a depth-dependence of at least one parameter characterizing the lateral structural feature.

Abstract: Disclosed herein is a method for depth-profiling of samples including a target region including a lateral structural feature. The method includes obtaining measured signals of the sample and analyzing thereof to obtain a depth-dependence of at least one parameter characterizing the lateral structural feature. The measured signals are obtained by repeatedly: projecting a pump pulse on the sample, thereby producing an acoustic pulse propagating within the target region; Brillouin-scattering a probe pulse off the acoustic pulse within the target region; and detecting a scattered component of the probe pulse to obtain a measured signal. In each repetition the respective probe pulse is scattered off the acoustic pulse at a respective depth within the target region, thereby probing the target region at a plurality of depths. A wavelength of the pump pulse is at least about two times greater than a lateral extent of the lateral structural feature.

Abstract: Disclosed is a computerized method for detecting defects on a sample. The method includes: (i) receiving scan data corresponding to a pixel on the sample; (ii) computing a difference vector d based on the scan data and corresponding reference data; (iii) computing a parameter D dependent on t=?d?(Glinear/??s?2)?s, wherein ?T?=K?1 with K being a covariance matrix corresponding to the pixel, s is a predetermined kernel characterizing a defect signal, and Glinear=s·(K?1 d) is a gaussian approximation of a likelihood ratio test expression for distinguishing the defect signal from noise, and wherein D substantially monotonically increases with ?t?; and (iv) computing a score q(g, D) indicative of whether the pixel is defective, wherein g is a parameter indicative of a value of Glinear and q(g, D) substantially monotonically increases with g and substantially monotonically decreases with D.

Abstract: Disclosed herein is a method for depth-profiling of samples including a target region including a lateral structural feature. The method includes obtaining measured signals of the sample and analyzing thereof to obtain a depth-dependence of at least one parameter characterizing the lateral structural feature. The measured signals are obtained by repeatedly: projecting a pump pulse on the sample, thereby producing an acoustic pulse propagating within the target region; Brillouin-scattering a probe pulse off the acoustic pulse within the target region; and detecting a scattered component of the probe pulse to obtain a measured signal. In each repetition the respective probe pulse is scattered off the acoustic pulse at a respective depth within the target region, thereby probing the target region at a plurality of depths.

Abstract: Disclosed herein is method for multi-perspective-based wafer analysis. The method includes (i) scanning a plurality of pages, or portions thereof, one after the other, wherein each page, or a portion thereof, is successively scanned, in each of a multiplicity of perspectives, and (ii) analyzing scan data of a last scanned page while scanning a next page from the plurality of pages. At least some of the pages include multiple slices of the wafer. The analysis of the scan data includes identifying defects in the scanned pages, based on an integrated analysis combining scan data from each of the multiplicity of perspectives. Further disclosed is a computerized system configured to implement the method.

Abstract: Disclosed herein is method for multi-perspective-based wafer analysis. The method includes (i) scanning a plurality of pages, or portions thereof, one after the other, wherein each page, or a portion thereof, is successively scanned, in each of a multiplicity of perspectives, and (ii) analyzing scan data of a last scanned page while scanning a next page from the plurality of pages. At least some of the pages include multiple slices of the wafer. The analysis of the scan data includes identifying defects in the scanned pages, based on an integrated analysis combining scan data from each of the multiplicity of perspectives. Further disclosed is a computerized system configured to implement the method.

Abstract: Disclosed herein is a computerized system including scanning equipment configured to obtain multi-perspective scan data of a slice on a sample. The scanning equipment includes: (i) a light source configured to generate a light beam; (ii) an acousto-optic deflector (AOD) configured to focus the light beam such as to generate a beam train scanned along consecutive lines on the slice, in groups of n?2 successively scanned lines, along each of which the beam train forms at least one illumination spot, respectively; and (iii) one or more detectors configured to sense light returned from the slice. The n?2 lines are scanned different perspectives, respectively. The consecutive lines may be longitudinally displaced relative to one another, such as to overlap in 100·(n?1)/n % of widths thereof, so that the slice may be fully scanned in each of the perspectives.

Abstract: There is provided a system and a method comprising obtaining data representative of potential defects in at least one image of a semiconductor specimen, for each potential defect of at least a first subset of potential defects of the semiconductor specimen, obtaining pixel values representative of the potential defect in multiple images of the specimen which differ from each other by at least one parameter, classifying the potential defects into a plurality of first clusters, for each first cluster, building, based on pixel values representative of potential defects, at least one first matching filter for the first cluster, for at least a given potential defect not belonging to the first subset, determining whether it corresponds to a defect based on the first matching filters associated with the plurality of first clusters.

Abstract: A method, system and computer readable medium for providing information about a region of a sample. The method includes (i) obtaining, by an imager, multiple images of the region; wherein the multiple images differ from each other by at least one parameter (ii) receiving or generating multiple reference images; (iii) generating multiple difference images that represent differences between the multiple images and the multiple reference images; (iv) calculating a set of region pixel attributes, (v) calculating a set of noise attributes, based on multiple sets of region pixels attributes of the multiple region pixels; and (vi) determining for each region pixel, whether the region pixel represents a defect based on a relationship between the set of noise attributes and the set of region pixel attributes of the pixel.

Abstract: Disclosed herein is a method for detecting defects on a sample. The method includes obtaining scan data of a region of a sample in a multiplicity of perspectives, and performing an integrated analysis of the obtained scan data. The integrated analysis includes computing, based on the obtained scan data, and/or estimating cross-perspective covariances, and determining presence of defects in the region, taking into account the cross-perspective covariances.

Abstract: Disclosed herein is a method for detecting defects on a sample. The method includes obtaining scan data of a region of a sample in a multiplicity of perspectives, and performing an integrated analysis of the obtained scan data. The integrated analysis includes computing, based on the obtained scan data, and/or estimating cross-perspective covariances, and determining presence of defects in the region, taking into account the cross-perspective covariances.