Nova Ltd.

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 measurement system for use in optical metrology, the measurement system which includes a control system configured and operable to carry out the following: (i) receive raw measured data generated by a measurement unit that is configured and operable for performing normal-incidence spectral interferometric measurements on a sample and generating the raw measured data indicative of spectral interferometric signals measured on the sample for a number of different optical path differences (OPDs) between sample and reference arms using infrared wavelengths; (ii) extract, from the raw measured data, a portion of spectral interferometric signals describing variation of signal intensity with a change of an optical path difference OPD during interferometric measurements, said portion of the spectral interferometric signals being independent of interferometric signals returned from a bottom portion of the sample in response to said illuminating electromagnetic field; and (iii) directly determine, from the extracted portion of the spectral interferometric signals, both spectral amplitude and phase of reflection of the illuminating electromagnetic field from the top portion of the sample, thereby enabling to determine a measured spectral signature characterizing the top portion of the sample.

A metrology system that may include (i) thermal response critical dimensions (TRCD) optics that comprises pump beam optics and probe beam optics: wherein during a measurement iteration the pump beam optics are configured to illuminate the structure with a pump beam, and the probe beam optics are configured to illuminate the structure with a probe beam, to collect the response radiation and to sense the response radiation; and (ii) one or more modeling engines that are configured to determine at least one critical dimension of the structure based on the response radiation.

A system and methods for OCD metrology are provided including receiving training data for training an OCD machine learning (ML) model, the training data measured from multiple wafers and including multiple pairs of corresponding input and label datasets obtained from each respective wafer. The input dataset of each pair includes multiple scatterometric datasets, measured at multiple respective locations defined by a first map. The label dataset of each pair includes one or more critical dimension (CD) parameters of respective locations defined by a second map, the second map including at least one location not in the first map. The OCD ML model is then applied to a new set of scatterometric datasets, measured from locations of a new wafer, according to the first map, to generate predicted CD parameters of locations of the second map on the new wafer.

A control system and method are presented for use in optical measurements on patterned samples. The control system comprises a computer system configured for data communication with a measured data provider and comprising a data processor configured and operable to receive and process raw measured data of first and second types concurrently collected from the patterned sample being measured. said first and second types of the measured data comprising, respectively. scatterometry measured data. characterized by first relatively high signal-to-noise and predetermined first relatively low spatial resolution, and interferometric measured data characterized by second relatively low signal-to-noise and predetermined second relatively high spatial resolution, said data processor being configured to process the measured data to determine pattern parameters along said patterned sample characterized by said first signal to-noise and said second spatial resolution.

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 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.