Abstract: A broadband ultraviolet illumination source for a characterization system is disclosed. The broadband ultraviolet illumination source includes an enclosure having one or more walls, the enclosure configured to contain a gas, and a plasma discharge device based on a graphene-dielectric-semiconductor (GOS) planar-type structure. The GOS structure includes a silicon substrate having a top surface, a dielectric layer disposed on the top surface of the silicon substrate, and at least one layer of graphene disposed on a top surface of the dielectric layer. A metal contact may be formed on the top surface of the graphene layer. The GOS structure has several advantages for use in an illumination source, such as low operating voltage (below 50 V), planar surface electron emission, and compatibility with standard semiconductor processes. The broadband ultraviolet illumination source further includes electrodes placed inside the enclosure or magnets placed outside the enclosure to increase the current density.

Abstract: First and second metrology data are used to train a machine-learning model to predict metrology data for a metrology target based on metrology data for a device area. The first metrology data are for a plurality of instances of a device area on semiconductor die fabricated using a fabrication process. The second metrology data are for a plurality of instances of a metrology target that contains structures distinct from structures in the device area. Using the trained machine-learning model, fourth metrology data are predicted for the metrology target based on third metrology data for an instance of the device area. Using a recipe for the metrology target, one or more parameters of the metrology target are determined based on the fourth metrology data. The fabrication process is monitored and controlled based at least in part on the one or more parameters.

Abstract: A light modulated electron source utilizes a photon-beam source to modulate the emission current of an electron beam emitted from a silicon-based field emitter. The field emitter's cathode includes a protrusion fabricated on a silicon substrate and having an emission tip covered by a coating layer. An extractor generates an electric field that attracts free electrons toward the emission tip for emission as part of the electron beam. The photon-beam source generates a photon beam including photons having an energy greater than the bandgap of silicon, and includes optics that direct the photon beam onto the emission tip, whereby each absorbed photon creates a photo-electron that combines with the free electrons to enhance the electron beam's emission current. A controller modulates the emission current by controlling the intensity of the photon beam applied to the emission tip. A monitor measures the electron beam and provides feedback to the controller.

Abstract: The present disclosure is directed to laser produced plasma light sources having a target material, such as xenon, that is coated on the outer surface of a drum. Bearing systems rotate the drum that have structures for reducing leakage of contaminant material and/or bearing gas into the LPP chamber. Injection systems are disclosed for coating and replenishing target material on the drum. Wiper systems are disclosed for preparing the target material surface on the drum, e.g. smoothing the target material surface. Systems for cooling and maintaining the temperature of the drum and a housing overlying the drum are also disclosed.

Abstract: An inspection system is disclosed. The inspection system includes a shared memory configured to receive image data from a defect inspection tool and a controller communicatively coupled to the shared memory. The controller includes a host image module configured to apply one or more general-purpose defect-inspection algorithms to the image data using central-processing unit (CPU) architectures, a results module configured to generate inspection data for defects identified by the host image module, and secondary image module(s) configured to apply one or more targeted defect-inspection algorithms to the image data. The secondary image module(s) employ flexible sampling of the image data to match a data processing rate of the host image module within a selected tolerance. The flexible sampling of the image data is adjusted responsive to the inspection data generated by the results module and the host image module.

Abstract: An optical system for controlling polarization may include an illumination source to illuminate a surface of a sample, a set of collection optics to collect illumination from the surface of a sample, and a wave plate having a spatially-varying surface profile along a thickness direction positioned at a pupil plane of the set of collection optics, where the spatially-varying surface profile of the wave plate is configured to control polarization rotation as a continuous function of transverse position, and where the spatially-varying surface profile is selected to rotate light scattered from a surface of a sample to a selected polarization angle. The system may further include a linear polarizer oriented to block light with the selected polarization angle, and a sensor to detect illumination transmitted through the linear polarizer.

Abstract: A system is disclosed. In one embodiment, the system includes a scanning electron microscopy sub-system including an electron source configured to generate an electron beam and an electron-optical assembly including one or more electron-optical elements configured to direct the electron beam to the specimen. In another embodiment, the system includes one or more grounding paths coupled to the specimen, the one or more grounding paths configured to generate one or more transmission signals based on one or more received electron beam-induced transmission currents. In another embodiment, the system includes a controller configured to: generate control signals configured to cause the scanning electron microscopy sub-system to scan the portion of the electron beam across a portion of the specimen; receive the transmission signals via the one or more grounding paths; and generate transmission current images based on the transmission signals.

Abstract: A target for use in the measurement of misregistration between layers formed on a wafer in the manufacture of semiconductor devices, the target including a first pair of periodic structures (FPPS) and a second pair of periodic structures (SPPS), each of the FPPS and the SPPS including a first edge, a second edge, a plurality of first periodic structures formed in a first area as part of a first layer and having a first pitch along a first pitch axis, the first pitch axis not being parallel to either of the first edge or second edge, and a plurality of second periodic structures formed in a second area as part of a second layer and having the first pitch along a second pitch axis, the second pitch axis being generally parallel to the first pitch axis.

Abstract: Metrology methods, modules and systems are provided, for using machine learning algorithms to improve the metrology accuracy and the overall process throughput. Methods comprise calculating training data concerning metrology metric(s) from initial metrology measurements, applying machine learning algorithm(s) to the calculated training data to derive an estimation model of the metrology metric(s), deriving measurement data from images of sites on received wafers, and using the estimation model to provide estimations of the metrology metric(s) with respect to the measurement data. While the training data may use two images per site, in operation a single image per site may suffice—reducing the measurement time to less than half the current measurement time. Moreover, confidence score(s) may be derived as an additional metrology and process control, and deep learning may be used to enhance the accuracy and/or speed of the metrology module.

Abstract: For semiconductor inspection images, detection thresholds can be determined based on probability density functions at a pixel intensity. The detection thresholds can then be applied to an image. This can find outliers at a fixed probability at all pixel intensity levels by estimating the probability distribution of underlying data and adapting the detection threshold values. Laser power can be optimized based on the detection thresholds.

Abstract: A method includes receiving one or more sets of wafer data, identifying one or more primitives from one or more shapes in one or more layers in the one or more sets of wafer data, classifying each of the one or more primitives as a particular primitive type, identifying one or more primitive characteristics for each of the one or more primitives, generating a primitive database of the one or more primitives, generating one or more rules based on the primitive database, receiving one or more sets of design data, applying the one or more rules to the one or more sets of design data to identify one or more critical areas, and generating one or more wafer inspection recipes including the one or more critical areas for an inspection sub-system.

Abstract: A beam of light is directed from a light source at a wafer on a chuck. The beam of light is reflected off the wafer toward a 2D imaging camera. Movable focus lenses in the path of the beam of light can independently change the illumination conjugate and the collection conjugate. A structured mask in an illumination path can be used and the beam of light can be directed through apertures in the structured mask. A gray field image of a wafer in a zone without direct illumination is generated using the 2D imaging camera and locations of defects on the wafer can be determined using the gray field image.

Abstract: Using data about the geometry of the wafer, the geometry of the wafer is measured along at least three diameters originating at different points along a circumference of the wafer. A characterization of the geometry of the wafer is determined using the three diameters. A probability of wafer clamping failure for the wafer can be determined based on the characterization.

Abstract: An enclosure assembly is disclosed, in accordance with one or more embodiment of the present disclosure. The enclosure assembly includes a top portion. The enclosure assembly further includes a bottom portion. The top portion is detachably connectable to the bottom portion via one or more coupling devices. The top portion is further reversibly, electrically couplable to the bottom portion via one or more electronic contacts. One or more electronic components are disposed within the enclosure assembly.

Abstract: A reference substrate for calibrating high-energy inspection systems includes permanently affixed particle-emulating and/or integral void-type environmentally inert surface features that emulate particles/defects having sizes below about 18 nm. Particle-emulating surface features are fabricated directly onto the substrate's surface (or an intervening barrier film layer) using e-beam lithography or over-etch processing. Void-type defect features having sizes below 18 nm are etched into the substrate's surface using, for example, focused ion beam, reactive particle or pin-hole etching processes. Once formed, the actual size of each surface feature is measured (e.g., using SEM) and then recorded. During a subsequent inspection tool calibration session, the reference substrate is scanned and waveform data corresponding to light reflected/scattered from each surface feature is correlated with the scanned feature's actual size data.

Abstract: A focus-sensitive metrology target may be formed and read-out by a fabrication tool. A resulting overlay signal may be translated into a focus offset by comparison to a previously-determined calibration curve. One or more translated signals may be fed back to the fabrication tool for focus correction or used for prediction of on-device overlay (correction of overlay metrology results). In one embodiment, focus and overlay may be measured using a single target, where one portion of the target is formed on a first layer and includes a focus-sensitive design, and where another portion of the target is formed on a second layer and includes a relatively less focus-sensitive design. In some embodiments, a relative difference in focus response may be used to estimate an impact of focus error on device overlay and calculate non-zero offset contributions.

Abstract: Methods and systems for improved detection and classification of defects of interest (DOI) is realized based on values of one or more automatically generated attributes derived from images of a candidate defect. Automatically generated attributes are determined by iteratively training, reducing, and retraining a deep learning model. The deep learning model relates optical images of candidate defects to a known classification of those defects. After model reduction, attributes of the reduced model are identified which strongly relate the optical images of candidate defects to the known classification of the defects. The reduced model is subsequently employed to generate values of the identified attributes associated with images of candidate defects having unknown classification. In another aspect, a statistical classifier is employed to classify defects based on automatically generated attributes and attributes identified manually.

Abstract: Machine learning approaches provide additional information about semiconductor wafer inspection stability issues that makes it possible to distinguish consequential process variations like process excursions from minor process variations that are within specification. The effect of variable defect of interest (DOI) capture rates in the inspection result and the effect of variable defect count on the wafer can be monitored independently.

Abstract: A spectroscopic metrology system includes a spectroscopic metrology tool and a controller. The controller generates a model of a multilayer grating including two or more layers, the model including geometric parameters indicative of a geometry of a test layer of the multilayer grating and dispersion parameters indicative of a dispersion of the test layer. The controller further receives a spectroscopic signal of a fabricated multilayer grating corresponding to the modeled multilayer grating from the spectroscopic metrology tool. The controller further determines values of the one or more parameters of the modeled multilayer grating providing a simulated spectroscopic signal corresponding to the measured spectroscopic signal within a selected tolerance. The controller further predicts a bandgap of the test layer of the fabricated multilayer grating based on the determined values of the one or more parameters of the test layer of the fabricated structure.

Abstract: A metrology target is disclosed, in accordance with one or more embodiments of the present disclosure. The metrology target includes a first set of pattern elements having a first pitch, where the first set of pattern elements includes segmented pattern elements. The metrology target includes a second set of pattern elements having a second pitch, where the second set of pattern elements includes segmented pattern elements. The metrology target includes a third set of pattern elements having a third pitch, where the third set of pattern elements includes segmented pattern elements.