Abstract: A semiconductor metrology system including a spectrum acquisition tool for collecting, using a first measurement protocol, baseline scatterometric spectra on first semiconductor wafer targets, and for various sources of spectral variability, variability sets of scatterometric spectra on second semiconductor wafer targets, the variability sets embodying the spectral variability, a reference metrology tool for collecting, using a second measurement protocol, parameter values of the first semiconductor wafer targets, and a training unit for training, using the collected spectra and values, a prediction model using machine learning and minimizing an associated loss function incorporating spectral variability terms, the prediction model for predicting values for production semiconductor wafer targets based on their spectra.

Abstract: A method for optical metrology of a sample, the method may include illuminating areas of the sample by sets of pulses of different wavelengths, during a movement of a variable speed of the sample; collecting light reflected from the sample, as a result of the illuminating, to provide sets of frames, each set of frames comprises partially overlapping frames associated with the different wavelengths; and processing the frames to provide optical metrology results indicative of one or more evaluated parameters of elements of the areas of the sample; wherein the processing is based on a mapping between the sets of frames and reference measurements obtained by an other optical metrology process that exhibits a higher spectral resolution than a spectral resolution obtained by the illuminating and the collecting.

Abstract: A system and methods for OCD metrology are provided including receiving multiple first sets of scatterometric data, dividing each set into k sub-vectors, and training, in a self-supervised manner, k2 auto-encoder neural networks that map each of the k sub-vectors to each other. Subsequently multiple respective sets of reference parameters and multiple corresponding second sets of scatterometric data are received and a transfer neural network (NN) is trained. Initial layers include a parallel arrangement of the k2 encoder neural networks. Target output of the transfer NN training is set to the multiple sets of reference parameters and feature input is set to the multiple corresponding second sets of scatterometric data, such that the transfer NN is trained to estimate new wafer pattern parameters from subsequently measured sets of scatterometric data.

Abstract: A method, a system, and a non-transitory computer readable medium for accurate Raman spectroscopy. The method may include executing at least one iteration of the steps of: (i) performing, by an optical measurement system, a calibration process that comprises (a) finding a misalignment between a region of interest defined by a spatial filter, and an impinging beam of radiation that is emitted from an illuminated area of a sample, the impinging beam impinges on the spatial filter; and (b) determining a compensating path of propagation of the impinging beam that compensates the misalignment; and (ii) performing a measurement process, while the optical measurement system is configured to provide the compensating path of propagation of the impinging beam, to provide one or more Raman spectra.

Abstract: A method and system are presented for use in X-ray based measurements on patterned structures. The method comprises: processing data indicative of measured signals corresponding to detected radiation response of a patterned structure to incident X-ray radiation, and subtracting from said data an effective measured signals substantially free of background noise, said effective measured signals being formed of radiation components of reflected diffraction orders such that model based interpretation of the effective measured signals enables determination of one or more parameters of the patterned structure, wherein said processing comprises: analyzing the measured signals and extracting therefrom a background signal corresponding to the background noise; and applying a filtering procedure to the measured signals to subtract therefrom signal corresponding to the background signal, resulting in the effective measured signal.

Abstract: A system and method are presented for controlling measurements of various sample's parameters. The system comprises a control unit configured as a computer system comprising data input and output utilities, memory, and a data processor, and being configured to communicate with a measured data provider to receive measured data indicative of measurements on the sample. The data processor is configured to perform model-based processing of the measured data utilizing at least one predetermined model, and determine, for each of one or more measurements of one or more parameters of interest of the sample, an estimated upper bound on an error value for the measurement individually, and generate output data indicative thereof.

Abstract: A method, a system, and a non-transitory computer readable medium for Raman spectroscopy.

Abstract: A test structure for use in metrology measurements of a sample pattern formed by periodicity of unit cells, each formed of pattern features arranged in a spaced-apart relationship along a pattern axis, the test structure having a test pattern, which is formed by a main pattern which includes main pattern features of one or more of the unit cells and has a symmetry plane, and a predetermined auxiliary pattern including at least two spaced apart auxiliary features located within at least some of those features of the main pattern, parameters of which are to be controlled during metrology measurements.

Abstract: A method, a system, and a non-transitory computer readable medium for measuring a local critical dimension uniformity of an array of two-dimensional structural elements, the method may include obtaining an acquired optical spectrometry spectrum of the array; feeding the acquired optical spectrometry spectrum of the array to a trained machine learning process, wherein the trained machine learning process is trained to map an optical spectrometry spectrum to an average critical dimension (CD) and a local critical dimension uniformity (LCDU); and outputting, by the trained machine learning process, the average CD and the LCDU of the array.

Abstract: A method for use in optical measurements on patterned structures, the method including performing a number of optical measurements on a structure with a measurement spot configured to provide detection of light reflected from an illuminating spot at least partially covering at least two different regions of the structure, the measurements including detecting light reflected from the at least part of the at least two different regions within the measurement spot, the detected light including interference of at least two complex electric fields reflected from the at least part of the at least two different regions, and being therefore indicative of a phase response of the structure, carrying information about properties of the structure.

Abstract: A system and methods for Advance Process Control (APC) in semiconductor manufacturing include: for each of a plurality of waiter sites, receiving a pre-process set of scatterometric training data, measured before implementation of a processing step, receiving a corresponding post-process set of scatterometric training data measured after implementation of the process step, and receiving a set of process control knob training data indicative of process control knob settings applied during implementation of the process step; and generating a machine learning model correlating variations in the pre-process sets of scatterometric training data and the corresponding process control knob training data with the corresponding post-process sets of scatterometric training data, to train the machine learning model to recommend changes to process control knob settings to compensate for variations in the pre-process scatterometric data.

Abstract: A measurement system is provided for use in optical metrology measurements. The measurement system comprises a control system which processes raw measured data indicative of spectral interferometric signals measured on a sample in response to illuminating electromagnetic field incident onto a top portion of the sample and comprising at least one spectral range to which said sample is substantially not absorbing.

Abstract: An integrated metrology system for evaluating semiconductor wafers, the metrology system comprises a main body that has a rear side and a front side; the front side defines a front border of the main body; one or more detachable supporting units that are detachably coupled to the main body and support the main body while extending outside the front border; and at least one auxiliary supporting unit that is configured to support the main body at an absence of the one or more detachable supporting units

Abstract: A combined OCD and photoreflectance system and method for improving the OCD performance in measurements of optical properties of a target sample.

Abstract: A system and methods for OCD metrology are provided including receiving reference parameters, receiving multiple sets of measured scatterometric data, and receiving an optical model designed to generate one or more sets of model scatterometric data according to a set of pattern parameters, and training a machine learning model by applying, during the training, target features including the reference parameters, and by applying input features including the sets of measured scatterometric data and the sets of model scatterometric data, such that the trained machine learning model estimates new wafer pattern parameters from subsequently sets of measured scatterometric data.

Abstract: Photoreflectance (PR) spectroscopy system and method for accumulating separately a “pump on” light beam and a “pump off light beam reflecting off a sample. The system comprises: (a) a probe source for producing a probe beam, the probe beam is used for measuring spectral reflectivity of a sample, (b) a pump source for producing a pump beam, (c) at least one spectrometer, (d) a first modulation device to allow the pump beam to alternatingly modulate the spectral reflectivity of the sample, so that, a light beam reflecting from the sample is alternatingly a “pump on” light beam and a “pump off light beam, (e) a second modulation device in a path of the light beam reflecting off the sample to alternatingly direct the “pump on” light beam and the “pump off light beam to the at least one spectrometer, and (f) a computer.

Abstract: A polarized Raman Spectrometric system for defining parameters of a polycrystaline material, the system comprises a polarized Raman Spectrometric apparatus, a computer-controlled sample stage for positioning a sample at different locations, and a computer comprising a processor and an associated memory. The polarized Raman Spectrometric apparatus generates signal(s) from either small sized spots at multiple locations on a sample or from an elongated line-shaped points on the sample, and the processor analyzes the signal(s) to define the parameters of said polycrystalline material.

Abstract: An optical system and method are presented for use in measurements on an upper surface of a layered sample when located in a measurement plane. The optical system is configured as a normal-incidence system having an illumination channel and a collection channel, and comprises an objective lens unit and a light propagation affecting device. The objective lens unit is accommodated in the illumination and collection channels, thereby defining a common optical path for propagation of illuminating light from the illumination channel toward an illuminating region in the measurement plane and for propagation of light returned from measurement plane to the collection channel. The light propagation affecting device comprises an apertured structure located in at least one of the illumination and collection channels, and configured to provide angular obscuration of light propagation path for blocking angular segments associated with light propagation from regions outside the illuminated region.

Abstract: A method for use in measuring one or more characteristics of patterned structures, the method including providing measured data comprising data indicative of at least one Raman spectrum obtained from a patterned structure under measurements using at least one selected optical measurement scheme each with a predetermined configuration of at least one of illuminating and collected light conditions corresponding to the one or more characteristics to be measured, processing the measured data, and determining, for each of the at least one Raman spectrum, a distribution of Raman-contribution efficiency (RCE) within at least a part of the structure under measurements, being dependent on characteristics of the structure and the predetermined configuration of the at least one of illuminating and collected light conditions in the respective optical measurement scheme, and analyzing the distribution of Raman-contribution efficiency and determining the one or more characteristics of the structure.

Abstract: A method for use in optical measurements on patterned structures, the method including performing a number of optical measurements on a structure with a measurement spot configured to provide detection of light reflected from an illuminating spot at least partially covering at least two different regions of the structure, the measurements including detecting light reflected from the at least part of the at least two different regions within the measurement spot, the detected light including interference of at least two complex electric fields reflected from the at least part of the at least two different regions, and being therefore indicative of a phase response of the structure, carrying information about properties of the structure.