Abstract: Methods and systems for performing co-located measurements of semiconductor structures with two or more measurement subsystems are presented herein. To achieve a sufficiently small measurement box size, the metrology system monitors and corrects the alignment of the measurement spot of each metrology subsystem with a metrology target to achieve maximum co-location of the measurement spots of each metrology subsystem with the metrology target. In another aspect, measurements are performed simultaneously by two or more metrology subsystems at high throughput at the same wafer location. Furthermore, the metrology system effectively decouples simultaneously acquired measurement signals associated with each measurement subsystem. This maximizes signal information associated with simultaneous measurements of the same metrology by two or more metrology subsystems.

Abstract: Methods and systems for performing co-located measurements of semiconductor structures with two or more measurement subsystems are presented herein. To achieve a sufficiently small measurement box size, the metrology system monitors and corrects the alignment of the measurement spot of each metrology subsystem with a metrology target to achieve maximum co-location of the measurement spots of each metrology subsystem with the metrology target. In another aspect, measurements are performed simultaneously by two or more metrology subsystems at high throughput at the same wafer location. Furthermore, the metrology system effectively decouples simultaneously acquired measurement signals associated with each measurement subsystem. This maximizes signal information associated with simultaneous measurements of the same metrology by two or more metrology subsystems.

Abstract: Methods and systems for creating a measurement model based only on measured training data are presented. The trained measurement model is then used to calculate overlay values directly from measured scatterometry data. The measurement models receive scatterometry signals directly as input and provide overlay values as output. In some embodiments, overlay error is determined from measurements of design rule structures. In some other embodiments, overlay error is determined from measurements of specialized target structures. In a further aspect, the measurement model is trained and employed to measure additional parameters of interest, in addition to overlay, based on the same or different metrology targets. In some embodiments, measurement data from multiple targets, measurement data collected by multiple metrologies, or both, is used for model building, training, and measurement. In some embodiments, an optimization algorithm automates the measurement model building and training process.

Abstract: Methods and systems for measuring metrology targets smaller than the illumination spot size employed to perform the measurement are described herein. Collected measurement signals contaminated with information from structures surrounding the target area are reconstructed to eliminate the contamination. In some examples, measurement signals associated one or more small targets and one or more large targets located in close proximity to one another are used to train a signal reconstruction model. The model is subsequently used to reconstruct measurement signals from other small targets. In some other examples, multiple measurements of a small target at different locations within the target are de-convolved to estimate target area intensity. Reconstructed measurement signals are determined by a convolution of the illumination spot profile and the target area intensity. In a further aspect, the reconstructed signals are used to estimate values of parameters of interest associated with the measured structures.

Abstract: Methods and systems for creating a measurement model based on measured training data are presented. The trained measurement model is used to calculate process parameter values, structure parameter values, or both, directly from measured data collected from other wafers. The measurement models receive measurement data directly as input and provide process parameter values, structure parameter values, or both, as output. The measurement model enables the direct measurement of process parameters. Measurement data from multiple targets is collected for model building, training, and measurement. In some examples, the use of measurement data associated with multiple targets eliminates, or significantly reduces, the effect of under layers in the measurement result, and enables more accurate measurements. Measurement data collected for model building, training, and measurement, may be derived from measurements performed by a combination of multiple, different measurement techniques.

Abstract: Methods and systems for performing semiconductor metrology directly on device structures are presented. A measurement model is created based on measured training data collected from at least one device structure. The trained measurement model is used to calculate process parameter values, structure parameter values, or both, directly from measurement data collected from device structures of other wafers. In some examples, measurement data from multiple targets is collected for model building, training, and measurement. In some examples, the use of measurement data associated with multiple targets eliminates, or significantly reduces, the effect of under layers in the measurement result, and enables more accurate measurements. Measurement data collected for model building, training, and measurement may be derived from measurements performed by a combination of multiple, different measurement techniques.

Abstract: Methods and systems for realizing a high brightness liquid metal droplet based x-ray source suitable for high throughput x-ray metrology are presented herein. A high power laser bombards a solid target material to generate liquid metal droplets. The laser generated liquid metal droplets are excited with a focused, high power excitation beam such as an electron or laser beam. The excitation beam is synchronized with the stream of liquid metal droplets stimulated by the high power laser to achieve a stable x-ray emission generated by the excited liquid metal droplets. In some embodiments, x-ray optics are designed to efficiently collect and focus radiation within a desired emission band onto a measurement target. Reliability is improved by shielding the excitation source and the x-ray optics from the region of interaction between the excitation beam and the liquid metal droplet anode by a localized curtain of shielding gas.

Abstract: Methods and systems for measuring metrology targets smaller than the illumination spot size employed to perform the measurement are described herein. Collected measurement signals contaminated with information from structures surrounding the target area are reconstructed to eliminate the contamination. In some examples, measurement signals associated one or more small targets and one or more large targets located in close proximity to one another are used to train a signal reconstruction model. The model is subsequently used to reconstruct measurement signals from other small targets. In some other examples, multiple measurements of a small target at different locations within the target are de-convolved to estimate target area intensity. Reconstructed measurement signals are determined by a convolution of the illumination spot profile and the target area intensity. In a further aspect, the reconstructed signals are used to estimate values of parameters of interest associated with the measured structures.

Abstract: Methods and systems for creating a measurement model based only on measured training data are presented. The trained measurement model is then used to calculate overlay values directly from measured scatterometry data. The measurement models receive scatterometry signals directly as input and provide overlay values as output. In some embodiments, overlay error is determined from measurements of design rule structures. In some other embodiments, overlay error is determined from measurements of specialized target structures. In a further aspect, the measurement model is trained and employed to measure additional parameters of interest, in addition to overlay, based on the same or different metrology targets. In some embodiments, measurement data from multiple targets, measurement data collected by multiple metrologies, or both, is used for model building, training, and measurement. In some embodiments, an optimization algorithm automates the measurement model building and training process.

Abstract: Methods and systems for enhancing metrology sensitivity to particular parameters of interest are presented. Field enhancement elements (FEEs) are constructed as part of a specimen to enhance the measurement sensitivity of structures of interest present on the specimen. The design of the FEEs takes into account measurement goals and manufacturing design rules to make target fabrication compatible with the overall device fabrication process. Measurement of opaque materials, high-aspect ratio structures, structures with low-sensitivity, or mutually correlated parameters is enhanced by the addition of FEEs. Exemplary measurements include critical dimension, film thickness, film composition, and optical scatterometry overlay. In some examples, a target element includes different FEEs to improve the measurement of different structures of interest. In other examples, different target elements include different FEEs.

Abstract: Methods and systems for performing semiconductor metrology directly on device structures are presented. A measurement model is created based on measured training data collected from at least one device structure. The trained measurement model is used to calculate process parameter values, structure parameter values, or both, directly from measurement data collected from device structures of other wafers. In some examples, measurement data from multiple targets is collected for model building, training, and measurement. In some examples, the use of measurement data associated with multiple targets eliminates, or significantly reduces, the effect of under layers in the measurement result, and enables more accurate measurements. Measurement data collected for model building, training, and measurement may be derived from measurements performed by a combination of multiple, different measurement techniques.

Abstract: Methods and systems for creating a measurement model based on measured training data are presented. The trained measurement model is used to calculate process parameter values, structure parameter values, or both, directly from measured data collected from other wafers. The measurement models receive measurement data directly as input and provide process parameter values, structure parameter values, or both, as output. The measurement model enables the direct measurement of process parameters. Measurement data from multiple targets is collected for model building, training, and measurement. In some examples, the use of measurement data associated with multiple targets eliminates, or significantly reduces, the effect of under layers in the measurement result, and enables more accurate measurements. Measurement data collected for model building, training, and measurement, may be derived from measurements performed by a combination of multiple, different measurement techniques.

Abstract: A metrology unit includes an integrated reference target with which an automated system check process is performed. The automated system check process includes measuring a feature on the reference target and determining if the measurement is within a desired specification for the metrology unit. When the metrology unit fails the automated system check, or if otherwise warranted, an automated diagnosis process may be performed using the same integrated reference target. The automated system check and automated diagnosis may be optimized based on correlations between parameters of the automated qualification and parameters of the automated diagnosis. Similarly, the measurement of a processed wafer may be optimized based on a correlation between parameters of the metrology of the processed wafer and parameters of the automated system check.

Abstract: A chuck that clamps a substrate to the top surface using, e.g., a vacuum, electrostatic force, or other appropriate means, includes a plurality of lift pins that can raise the substrate off the top surface of the chuck. The chuck may be used with a metrology device that measures the substrate using a first type of measurement, e.g., film thickness measurement, while the substrate is held flat, and measures the substrate using a second type of measurement, e.g., radius of curvature measurement, while the substrate is supported on the lift pins. The thickness and radius of curvature measurements may then be used to determine the stress on the substrate. The lift pins may include an aperture through which a vacuum is applied through the top surface of the lift pins to the bottom of the substrate to securely hold the substrate while moving.

Abstract: A process for effectively reducing reactivity of a surface of a semiconductor substrate is described. The process includes: (1) oxidizing in an oxidizing environment the semiconductor substrate surface, the semiconductor substrate having a dopant concentration profile that extends across a depth of the semiconductor substrate; and (2) annealing the semiconductor substrate surface in an inert gas environment, wherein the oxidizing and the annealing of the semiconductor substrate surface are performed at a temperature that is sufficiently low to substantially preserve the dopant concentration profile in the semiconductor substrate. A surface passivation apparatus is also described. The apparatus includes: a heating source for heating a substrate surface; an ozone generator; and a chamber for exposing a substrate surface to an oxidizing environment that includes a gas composition, wherein the ozone generator is configured to produce ozone within the chamber using the gas composition.