Nova Ltd.

A system for use in metrology of a patterned structure, the system which includes a data input utility configured to receive: first type of data related to the patterned structure, the first type of data was obtained by a first type of metrology system and comprises first type measurements and first geometrical information regarding the patterned structure; second type of data related to the patterned structure, the second type of data was obtained by a second type of metrology system and comprises second type measurement results and second geometrical information regarding the patterned structure; the second type of metrology system differs from the first type of metrology system, and a data processing and analyzing utility configured to determine values of parameters of interest based on the first type of data and the second type of data. The parameters of interest comprise (i) a first parameter of interest that is related to the first type of metrology and (ii) a second parameter of interest that is related to the second type of metrology; in which the first parameter of interest is a parameter of a first model for interpreting the first type of measurements; in which the second parameter of interest is a parameter of a second model for interpreting the second type of measurements; wherein the data processing and analyzing utility is configured to determine values of parameters of interest by applying an iterative process, wherein the iterative process comprises updating the first model based on the second type of data to provide a currently updated first model and updating the second model based on the first type of data. The first type measurements and the second type measurements are taken from measurement sites of a substrate that comprises the patterned structure; wherein the data processing and analyzing utility configured to adjust the first type measurements by using correlation curves to provide adjusted first type measurements, and use the adjusted first type measurements during a data interpretation process applied on the second type of data, in which the data processing and analyzing utility is configured to reduce a number of floating parameters of the data interpretation process to provide a reduced number of floating parameters by stabilizing measurements of non-floating parameters; wherein each of the non-floating parameters has a greater impact on the first type measurements than an impact of each of the reduced number of floating parameters.

A system and methods for OCD metrology are provided including receiving training data for training an OCD machine learning (ML) model, including multiple pairs of corresponding sets of scatterometric data and reference parameters. For each of the pairs, one or more corresponding outlier metrics are by calculated and corresponding outlier thresholds are applied whether a given pair is an outlier pair. The OCD ML model is then trained with the training data less the outlier pairs.

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.

A method and system are presented for use in measuring characteristic(s) of patterned structures. The method utilizes processing of first and second measured data, wherein the first measured data is 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 illuminating and/or collected light conditions corresponding to the characteristic(s) to be measured, and the second measured data comprises at least one spectrum obtained from the patterned structure in Optical Critical Dimension (OCD) measurement session. The processing comprises applying model-based analysis to the at least one Raman spectrum and the at least one OCD spectrum, and determining the characteristic(s) of the patterned structure under measurements.

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.

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.

A method, a system, and a non-transitory computer readable medium for Raman spectroscopy. The method may include determining first acquisition parameters of a Raman spectroscope to provide a first acquisition set-up, the determining is based on at least one expected radiation pattern to be detected by a sensor of the Raman spectroscope as a result of an illumination of a first area of a sample, the first area comprises a first nano-scale structure, wherein at least a part of the at least one expected radiation pattern is indicative of at least one property of interest of the first nano-scale structure of the sample; wherein the first acquisition parameters belong to a group of acquisition parameters; setting the Raman spectroscope according to the first acquisition set-up; and acquiring at least one first Raman spectrum of the first nano-scale structure of the sample, while being set according to the first acquisition set-up.

A method and system are presented for monitoring measurement of parameters of patterned structures based on a predetermined fitting model. The method comprises: (a) providing data indicative of measurements in at least one patterned structure; and (b) applying at least one selected verification mode to said data indicative of measurements, said at least one verification mode comprising: I) analyzing the data based on at least one predetermined factor and classifying the corresponding measurement result as acceptable or unacceptable, II) analyzing the data corresponding to the unacceptable measurement results and determining whether one or more of the measurements providing said unacceptable result are to be disregarded, or whether one or more parameters of the predetermined fitting model are to be modified.

A measurement system for use in measuring parameters of a patterned sample, the system including a broadband light source, an optical system configured as an interferometric system, a detection unit, and a control unit, where the interferometric system defines illumination and detection channels having a sample arm and a reference arm having a reference reflector, and is configured for inducing an optical path difference between the sample and reference arms, the detection unit for detecting a combined light beam formed by a light beam reflected from the reflector and a light beam propagating from a sample's support, and generating measured data indicative of spectral interference pattern formed by spectral interference signatures, and the control unit for receiving the measured data and applying a model-based processing to the spectral interference pattern for determining one or more parameters of the pattern in the sample.

A method and system are presented for use in measuring on patterned samples, aimed at determining asymmetry in the pattern. A set of at least first and second measurements on a patterned region of a sample is performed, where each of the measurements comprises: directing illuminating light onto the patterned region along an illumination channel and collecting light reflected from the illuminated region propagating along a collection channel to be detected, such that detected light from the same patterned region has different polarization states which are different from polarization of the illuminating light, and generating a measured data piece indicative of the light detected in the measurement. Thus, at least first and second measured data pieces are generated for the at least first and second measurements on the same patterned region. The at least first and second measured data pieces are analyzed and output data is generated being indicative of a condition of asymmetry in the patterned region.