Kla Tencor Corporation

Kla Corporation

Kla-tenor Corp.

Jonathan M Madsen

Andrei V Shchegrov

Stilian Pandev

Alexander Kuznetsov

Liran Yerushalmi

Min-Yeong Moon

Dimitry Sanko

Mahendra Dubey

Thaddeus Gerard Dziura

David Y Wang

Michael S Bakeman

Derrick A Shaughnessy

Pablo Rovira

Amnon Manassen

Michael E Adel

Ady Levy

Andrew V Hill

Daniel Kandel

Shankar Krishnan

Walter Dean Mieher

Michael Friedmann

Wei Guang Lu

Xuefeng Liu

Guorong Vera Zhuang

Yin Xu

Lie-Quan Lee

Johannes D De Veer

Gilad Laredo

Song Qing Wu

Yoram Uziel

Yossi Simon

Esen Salcin

Ori Tadmor

Bin-Ming (Benjamin) Tsai

A multi-column metrology tool may include two or more measurement columns distributed along a column direction, where the two or more measurement columns simultaneously probe two or more measurement regions on a sample including metrology targets. A measurement column may include an illumination sub-system to direct illumination to the sample, a collection sub-system including a collection lens to collect measurement signals from the sample and direct it to one or more detectors, and a column-positioning sub-system to adjust a position of the collection lens. A measurement region of a measurement column may be defined by a field of view of the collection lens and a range of the positioning system in the lateral plane. The tool may further include a sample-positioning sub-system to scan the sample along a scan path different than the column direction to position metrology targets within the measurement regions of the measurement columns for measurements.

Massive overlay metrology sampling with multiple measurement columns

A self-calibrating overlay metrology system may receive device overlay data for a device targets on a sample from an overlay metrology tool, determine preliminary device overlay measurements for the device targets including device-scale features using an overlay recipe with the device overlay data as inputs, receive assist overlay data for one or more assist targets on the sample including device-scale features from the overlay metrology tool, where at least one of the one or more assist targets has a programmed overlay offset of a selected value along a particular measurement direction, determine self-calibrating assist overlay measurements for the one or more assist targets based on the assist overlay data, where the self-calibrating assist overlay measurements are linearly proportional to overlay on the sample, and generate corrected overlay measurements for the device targets by adjusting the preliminary device overlay measurements based on the self-calibrating assist overlay measurements.

Self-calibrating overlay metrology

An overlay metrology system may receive overlay data for in-die overlay targets within various fields on a skew training sample from one or more overlay metrology tools, wherein the in-die overlay targets within the fields have a range programmed overlay offsets, wherein the fields are fabricated with a range of programmed skew offsets. The system may further generate asymmetric target signals for the in-die overlay targets using an asymmetric function providing a value of zero when physical overlay is zero and a sign indicative of a direction of physical overlay. The system may further generate corrected overlay offsets for the in-die overlay targets on the asymmetric target signals, generate self-calibrated overlay offsets for the in-die overlay targets based on the programmed overlay offsets and the corrected overlay offsets, generate a trained overlay recipe, and generate overlay measurements for in-die overlay targets on additional samples using the trained overlay recipe.

Self-calibrated overlay metrology using a skew training sample

A self-calibrating overlay metrology system may receive device overlay data from device targets on a sample, determine preliminary device overlay measurements for the device targets including device-scale features using an overlay recipe with the device overlay data as inputs, receive assist overlay data from sets of assist targets on the sample including device-scale features, where a particular set of assist targets includes one or more target pairs formed with two overlay targets having programmed overlay offsets of a selected value with opposite signs along a particular measurement direction. The system may further determine self-calibrating assist overlay measurements for the sets of assist targets based on the assist overlay data, where the self-calibrating assist overlay measurements are linearly proportional to overlay on the sample, and generate corrected overlay measurements for the device targets by adjusting the preliminary device overlay measurements based on the self-calibrating assist overlay measurements.

A metrology system is disclosed. In one embodiment, the metrology system includes a controller communicatively coupled to a reference metrology tool and an optical metrology tool, the controller including one or more processors configured to: generate a geometric model for determining a profile of a test HAR structure from metrology data from a reference metrology tool; generate a material model for determining one or more material parameters of a test HAR structure from metrology data from the optical metrology tool; form a composite model from the geometric model and the material model; measure at least one additional test HAR structure with the optical metrology tool; and determine a profile of the at least one additional test HAR structure based on the composite model and metrology data from the optical metrology tool associated with the at least one HAR test structure.

Loosely-coupled inspection and metrology system for high-volume production process monitoring

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.

Methods and systems for co-located metrology

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.

Signal response metrology for scatterometry based overlay measurements

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.

Measurement of small box size targets

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.

Statistical model-based metrology

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.

On-device metrology

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.

High brightness liquid droplet X-ray source for semiconductor metrology

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. In some other examples, field enhancement elements are shaped to concentrate an electric field in a thin film deposited over the FEE.

Optical metrology using targets with field enhancement elements

Various metrology systems and methods for high aspect ratio and large lateral dimension structures are provided. One method includes directing light to one or more structures formed on a wafer. The light includes ultraviolet light, visible light, and infrared light. The one or more structures include at least one high aspect ratio structure or at least one large lateral dimension structure. The method also includes generating output responsive to light from the one or more structures due to the light directed to the one or more structures. In addition, the method includes determining one or more characteristics of the one or more structures using the output.

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Los Altos, CA, United States of America

Jonathan M Madsen