Abstract: 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.

Abstract: 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.

Abstract: There is provided a system and method of runtime defect examination of a semiconductor specimen, comprising obtaining a first image representative of at least part of the semiconductor specimen, the first image acquired by an examination tool configured with a first focus plane; estimating whether the first image is in focus using a machine learning (ML) model, wherein the ML model is previously trained for classifying images into focused images and defocused images; upon an estimation that the first image is out of focus, performing focus calibration on the examination tool to select a second focus plane associated with an optimal focus score; and obtaining a second image acquired by the examination tool configured with the second focus plane, and estimating whether the second image is in focus using the ML model. The second image, upon being estimated as being in focus, is usable for defect examination on the specimen.

Abstract: There is provided a system and a method comprising obtaining a first (respectively second) image of an area of the semiconductor specimen acquired by an electron beam examination tool at a first (respectively second) illumination angle, determining a plurality of height values informative of a height profile of the specimen in the area, the determination comprising solving an optimization problem which comprises a plurality of functions, each function being representative of a difference between data informative of a grey level intensity at a first location in the first image and data informative of a grey level intensity at a second location in the second image, wherein, for each function, the second location is determined with respect to the first location, or conversely, when solving the optimization problem, wherein a distance between the first and the second locations depends on the height profile, and the first and second illumination angles.

Abstract: 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.

Abstract: A system, method and computer readable medium for examining a specimen, the method comprising: obtaining defects of interest (DOIs) and false alarms (FAs) from a review subset selected from a group of potential defects received from an inspection tool, each potential defect is associated with attribute values defining a location of the potential defect in an attribute space; generating a representative subset of the group, comprising potential defects selected in accordance with a distribution of the potential defects within the attribute space, and indicating the potential defects in the representative subset as FA; and training a classifier using data informative of the attribute values of the DOIs, the potential defects of the representative subset, and respective indications thereof as DOIs or FAs, wherein the trained classifier is to be applied to at least some of the potential defects to obtain an estimation of a number of expected DOIs.

Abstract: Disclosed herein is a computer-based method for non-destructive depth-profiling of samples. The method includes a measurement operation and a data analysis operation. The measurement operation includes, for each of a plurality of landing energies: (i) projecting an electron beam on a sample, which penetrates the sample to a respective depth determined by the landing energy, and (ii) sensing electrons returned from the sample, thereby obtaining a respective sensed electrons data set. The data analysis operation includes generating from the sensed electrons data sets a concentration map, which characterizing at least a vertical dimension of the sample.

Abstract: A gas injection nozzle that includes an elongated gas conduit that comprises: a first gas conduit segment configured to be coupled with a gas reservoir; a second gas conduit segment fluidly coupled to the first gas conduit segment and defining a downward curve of the elongated gas conduit; a third gas conduit segment defining an upward curve of the elongated gas conduit that extends to a sealed end and is disposed in a mirrored relationship with at least a portion of the second gas conduit; and a central gas conduit segment coupled between the second and third gas conduit segments, the central gas conduit segment having a first aperture formed in an upper surface of the central gas conduit and a second aperture, larger than the first aperture, formed in a lower surface of the central gas conduit directly across from the first aperture, wherein the elongated gas conduit has a first diameter along a portion of its length that includes at least the second, third and central gas conduit segments and wherein the c

Abstract: Disclosed herein is a system for non-destructive depth-profiling of samples. The system includes: (i) an electron beam (e-beam) source for projecting e-beams at each of a plurality of landing energies on an inspected sample; (ii) an electron sensor for obtaining a measured set of electron intensities pertaining to each of the landing energies; and (iii) processing circuitry for determining a set of structural parameters, which characterizes an internal geometry and/or a composition of the inspected sample, based on the measured set of electron intensities and taking into account reference data indicative of an intended design of the inspected sample.

Abstract: Disclosed herein is a system for non-destructive depth-profiling of samples. The system includes an electron beam source, a light sensor, and processing circuitry. The electron beam source configured to project e-beams on an inspected sample at each of a plurality of landing energies, which induce X-ray emitting interactions within each of a plurality of probed regions in the inspected sample, respectively, whose depth is determined by the landing energy. The light sensor is configured to measure the emitted X-ray light to obtain optical emission data sets pertaining to each of the probed regions, respectively. The processing circuitry is configured to determine a set of structural parameters, characterizing an internal geometry and/or a composition of the inspected sample, based on the measured optical emission data sets and taking into account reference data indicative of an intended design of the inspected sample.

Abstract: A computer-based method for non-destructive z-profiling of samples. The method includes: a measurement operation and a data analysis operation. The measurement operation includes, for each of a plurality of landing energies: (i) projecting an electron beam on a sample at a respective landing energy, such that light-emitting interactions between electrons from the electron beam and the sample occur within a respective probed region of the sample, which is centered about a respective depth; and (ii) measuring the emitted light to obtain an optical emission data set of the sample. The data analysis operation includes obtaining from the measured optical emission data sets a concentration map quantifying a dependence of a concentration of a material, which the sample comprises, on at least the depth.

Abstract: There is provided a system and method of measuring a lateral recess in a semiconductor specimen, comprising: obtaining a first image acquired by collecting SEs emitted from the surface of the specimen, and a second image acquired by collecting BSEs scattered from an interior region of the specimen between the surface and a target second layer, the specimen scanned using an electron beam with a landing energy selected to penetrate to a depth corresponding to the target second layer; generating a first GL waveform based on the first image, and a second GL waveform based on the second image; estimating a first width of the first layers based on the first GL waveform, and a second width with respect to at least the target second layer based on the second GL; and measuring a lateral recess based on the first width and the second width.

Abstract: A charged particle evaluation system that may include a column that includes an opening; an illumination unit that is configured to scan an area of a sample with an electron beam that passes through the opening; and an optical auto-focus unit that is configured to (i) illuminate the sample with an optical beam that is proximate to the electron beam, during the scan of the area with the electron beam; (ii) receive a reflected optical beam from the sample, (iii) determine a focus status of the electron beam, and (iv) participate in a compensating of an electron beam misfocus.

Abstract: Provided is a system and method of generating training data for training a Deep Neural Network usable for examination of a semiconductor specimen. The method includes: obtaining a first training image and first labels respectively associated with a group of pixels selected in each segment, extract a set of features characterizing the first training image, train a machine learning (ML) model using the first labels, values of the group of pixels, and the feature values of each of the set of features corresponding to the group of pixels, process the first training image using the trained ML model to obtain a first segmentation map, and determine to include the first training image and the first segmentation map into the DNN training data upon a criterion being met, and to repeat the extracting of the second features, the training and the processing upon the criterion not being met.

Abstract: An EDX sensing unit that includes an x-ray sensor including one or more sensing regions, and a protective unit that is configured to introduce a change in one or more properties of electrons emitted from the sample, thereby preventing the electrons emitted from the sample from reaching the one or more sensing regions; wherein the electrons are emitted from the sample due to an illuminating of the sample by a primary electron beam. The x-ray sensor is configured to (i) receive, by the one or more sensing regions, x-ray photons emitted from the sample due to the illuminating of the sample, and (ii) generate detection signals indicative of the x-ray photons.

Abstract: A system for depositing material over a sample in a localized region of the sample, the system including: a vacuum chamber; a thermal mass disposed outside the vacuum chamber; a sample support configured to hold a sample within the vacuum chamber during a sample evaluation process; a charged particle beam column configured to direct a charged particle beam into the vacuum chamber toward the sample such that the charged particle beam collides with the sample in a deposition region; a gas injection system configured to deliver a process gas to the deposition region of the sample; and a thermal isolation shield spaced apart from and disposed between the gas injection system and the sample, wherein the thermal isolation shield has a high thermal conductivity and a low emissivity and is thermally coupled to the thermal mass to transfer heat radiated from the gas injection system to the thermal mass.

Abstract: An energy-dispersive x-ray spectroscopy (EDX) sensing unit, the EDX sensing unit include a protective unit and an x-ray sensor that includes one or more sensing regions. The protective unit is configured to (i) introduce a change in one or more properties of electrons emitted from a sample, thereby preventing the electrons emitted from the sample from reaching the one or more sensing regions, the electrons are emitted from the sample due to an illuminating of the sample by a primary electron beam, and (ii) increase a safety of operation of the EDX sensing unit. The x-ray sensor is configured to (i) receive, by the one or more sensing regions, x-ray photons emitted from the sample due to the illuminating of the sample, and (ii) generate detection signals indicative of the x-ray photons.

Abstract: A method of processing a region of a sample, the method comprising: positioning a sample within a vacuum chamber; generating an ion beam with a focused ion beam (FIB) column; focusing the ion beam on the sample and scanning the focused ion beam across the region of the sample thereby generating secondary electrons that are ejected from a surface of the sample within the region; and during the scanning, applying a negative bias voltage to an electrically conductive structure proximate the region to alter a trajectory of the secondary electrons and repel the secondary electrons back to the sample surface, wherein the electrically conductive structure is one of a gas injection nozzle, a voltage pin or a nano-manipulator.

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: A method for detecting a rare stochastic defect, the method may include searching for a rare stochastic defect in a dense pattern of a substrate, wherein the rare stochastic defect is (a) of nanometric scale, (b) appears in a functional pattern of the substrate with a defect density that is below 10?9, and (c) appears in the dense pattern with a defect density that is above 10?7; wherein the dense pattern is a dense representation of the functional pattern that differs from the functional pattern by at least one out of (a) a distance between features of the dense pattern, and (b) a width of the features of the dense pattern; and estimating the occurrence of the rare stochastic defect within the functional pattern based on an outcome of the searching.