| Patent application number | Description | Published |
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| 20080231863 | Automated process control using optical metrology with a photonic nanojet - A fabrication cluster can be controlled using optical metrology. A fabrication process is performed on a wafer using a fabrication cluster. A photonic nanojet, an optical intensity pattern induced at a shadow-side surface of a dielectric microsphere, is generated. An inspection area on the wafer is scanned with the photonic nanojet. A measurement is obtained of the retroreflected light from the dielectric microsphere as the photonic nanojet scans the inspection area. The existence of a structure in the inspection area is determined with the obtained measurement of the retroreflected light. One or more process parameters of the fabrication cluster is adjusted based on the determination of the existence of the structure in the inspection area. | 09-25-2008 |
| 20080241975 | Automated process control using optical metrology and photoresist parameters - To control a photolithography cluster using optical metrology, a structure is fabricated on a wafer using the photolithography cluster. A measured diffraction signal off the structure is obtained. The measured diffraction signal is compared to a simulated diffraction signal. The simulated diffraction signal is associated with one or more values of one or more photoresist parameters. The one or more photoresist parameters characterize behavior of photoresist when the photoresist undergoes processing steps in the photolithography cluster. The simulated diffraction signal was generated using one or more values of one or more profile parameters. The one or more values of the one or more profile parameters used to generate the simulated diffraction signal were derived from the one or more values of the one or more photoresist parameters associated with the simulated diffraction signal. If the measured diffraction signal and the simulated diffraction signal match, then one or more values of one or more photoresist parameters used in the photolithography cluster are determined to be the one or more values of the one or more photoresist parameters associated with the matching simulated diffraction signal. One or more process parameters or equipment settings of the photolithography cluster are adjusted based on the one or more values of the one or more photoresist parameters. | 10-02-2008 |
| 20080243730 | Training a machine learning system to determine photoresist parameters - To train a machine learning system, a set of different values of one or more photoresist parameters, which characterize behavior of photoresist when the photoresist undergoes processing steps in a wafer application, is obtained. A set of diffraction signals is obtained using the set of different values of the one or more photoresist parameters. The machine learning system is trained using the set of measured diffraction signals as inputs to the machine learning system and the set of different values of the one or more photoresist parameters as expected outputs of the machine learning system. | 10-02-2008 |
| 20080252908 | CONTROLLING A FABRICATION TOOL USING SUPPORT VECTOR MACHINE - A fabrication tool can be controlled using a support vector machine. A profile model of the structure is obtained. The profile model is defined by profile parameters that characterize the geometric shape of the structure. A set of values for the profile parameters is obtained. A set of simulated diffraction signals is generated using the set of values for the profile parameters, each simulated diffraction signal characterizing the behavior of light diffracted from the structure. The support vector machine is trained using the set of simulated diffraction signals as inputs to the support vector machine and the set of values for the profile parameters as expected outputs of the support vector machine. After the support vector machine has been trained, a fabrication process is performed using the fabrication tool to fabricate the structure on the wafer. A measured diffraction signal off the structure is obtained. The measured diffraction signal is inputted into the trained support vector machine. Values of profile parameters of the structure are obtained as an output from the trained support vector machine. One or more process parameters or equipment settings of the fabrication tool are adjusted based on the obtained values of the profile parameters. | 10-16-2008 |
| 20080291429 | AUTOMATED PROCESS CONTROL USING PARAMETERS DETERMINED FROM A PHOTOMASK COVERED BY A PELLICLE - Provided is a method of controlling a photolithography cluster or a subsequent fabrication cluster using optical metrology to determine profile parameters of a photomask structure covered with a pellicle. An optical metrology model of the pellicle is developed and integrated with the optical metrology model of the photomask structure. The optical metrology model of the photomask taking into account the optical effects on the illumination and detection beams transmitted through the pellicle and diffracted by the photomask structure. One or more profile parameters of the photomask structure is determined and used to adjust one or more process parameters or equipment settings of a photolithography cluster using the photomask or a subsequent fabrication cluster. | 11-27-2008 |
| 20090063077 | AUTOMATED PROCESS CONTROL USING PARAMETERS DETERMINED WITH APPROXIMATION AND FINE DIFFRACTION MODELS - Provided is a method of controlling a fabrication cluster using a machine learning system, the machine learning system trained developed using an optical metrology model, the optical metrology model comprising a profile model, an approximation diffraction model, and a fine diffraction model. A simulated approximation diffraction signal is generated based on an approximation diffraction model of the structure. A set of difference diffraction signal is obtained by subtracting the simulated approximation diffraction signal from each of simulated fine diffraction signals and paired with the corresponding profile parameters. A first machine learning system is trained using the pairs of difference diffraction signal and corresponding profile parameters. A library of simulated fine diffraction signals and profile parameters is generated using the trained first machine learning system and using ranges and corresponding resolutions of the profile parameters. The library is used to train a second machine learning system. A measured diffraction signal is input into the trained second machine learning system to determine at least one profile parameter. The at least one profile parameter is used to adjust at least one process parameter or equipment setting of the fabrication cluster. | 03-05-2009 |
| 20090082993 | AUTOMATED PROCESS CONTROL OF A FABRICATION TOOL USING A DISPERSION FUNCTION RELATING PROCESS PARAMETER TO DISPERSION - An optical metrology model for the structure is obtained. The optical metrology model comprising one or more profile parameters, one or more process parameters, and a dispersion. A dispersion function that relates the dispersion to at least one of the one or more process parameters is obtained. A simulated diffraction signal is generated using the optical metrology model and a value for the at least one of the process parameters and a value for the dispersion. The value for the dispersion is calculated using the value for the at least one of the process parameter and the dispersion function. A measured diffraction signal of the structure is obtained using an optical metrology tool. The measured diffraction signal is compared to the simulated diffraction signal to determine one or more profile parameters of the structure. The fabrication tool is controlled based on the determined one or more profile parameters of the structure. | 03-26-2009 |
| 20090234687 | METHOD OF DESIGNING AN OPTICAL METROLOGY SYSTEM OPTIMIZED FOR OPERATING TIME BUDGET - Provided is a method of designing an optical metrology system for measuring structures on a workpiece wherein the optical metrology system is configured to achieve a time budget for completing metrology process steps. The design of the optical metrology system is optimized by using collected operating data in comparison to the selected operating criteria. In one embodiment, the optical metrology system is used for stand alone systems. In another embodiment, the optical metrology system is integrated with fabrication clusters in semiconductor manufacturing. | 09-17-2009 |
| 20090240537 | APPARATUS FOR DESIGNING AN OPTICAL METROLOGY SYSTEM OPTIMIZED FOR OPERATING TIME BUDGET - Provided is an apparatus for designing an optical metrology system for measuring structures on a workpiece wherein the optical metrology system is configured to achieve a time budget for completing metrology process steps. The design of the optical metrology system is optimized by using collected operating data in comparison to the selected operating criteria. In one embodiment, the optical metrology system is used for stand alone systems. In another embodiment, the optical metrology system is integrated with fabrication clusters in semiconductor manufacturing. | 09-24-2009 |
| 20090248339 | DESIGNING AN OPTICAL METROLOGY SYSTEM OPTIMIZED WITH SIGNAL CRITERIA - Provided is a method of designing an optical metrology system for measuring structures on a workpiece wherein the optical metrology system is configured to meet one or more signal criteria. The design of the optical metrology system is optimized by using collected signal data in comparison to the one or more signal criteria. In one embodiment, the optical metrology system is used for stand alone systems. In another embodiment, the optical metrology system is integrated with a fabrication cluster in semiconductor manufacturing. | 10-01-2009 |
| 20090248340 | APPARATUS FOR DESIGNING AN OPTICAL METROLOGY SYSTEM OPTIMIZED WITH SIGNAL CRITERIA - Provided is an apparatus for designing an optical metrology system for measuring structures on a workpiece wherein the optical metrology system is configured to meet one or more signal criteria. The design of the optical metrology system is optimized by using collected signal data in comparison to set one or more signal criteria. In one embodiment, the optical metrology system is used for stand alone systems. In another embodiment, the optical metrology system is integrated with a fabrication cluster in semiconductor manufacturing. | 10-01-2009 |
| 20090248341 | PROCESS CONTROL USING AN OPTICAL METROLOGY SYSTEM OPTIMIZED WITH SIGNAL CRITERIA - Provided is system and method for controlling a fabrication cluster using at least one parameter of a structure measured with an optical metrology system designed and configured to meet one or more signal criteria. The design of the optical metrology system is optimized by using collected signal data in comparison to set one or more signal criteria. In one embodiment, the optical metrology system is used for standalone systems. In another embodiment, the optical metrology system is integrated with a fabrication cluster in semiconductor manufacturing. At least one parameter determined from a signal measured using the optical metrology system is transmitted to a fabrication cluster. The at least one parameter is used to modify at least one process variable or equipment setting of the fabrication cluster. | 10-01-2009 |
| 20090319075 | AUTOMATED PROCESS CONTROL USING AN OPTICAL METROLOGY SYSTEM OPTIMIZED WITH DESIGN GOALS - Provided is a method of designing an optical metrology system for measuring structures on a workpiece wherein the optical metrology system is configured to meet a plurality of design goals. The design of the optical metrology system is optimized by using collected design goal data in comparison to the set plurality of design goals. In one embodiment, the optical metrology system is used for stand alone metrology systems. In another embodiment, the optical metrology system is integrated with a fabrication cluster in semiconductor manufacturing. At least one parameter determined from a diffraction signal measured using the optical metrology system is transmitted to the fabrication cluster. The at least one parameter is used to modify at least one process variable or equipment setting of the fabrication cluster. | 12-24-2009 |
| 20090319214 | OPTICAL METROLOGY SYSTEM OPTIMIZED WITH DESIGN GOALS - Provided is a method of designing an optical metrology system for measuring structures on a workpiece where the optical metrology system is configured to meet two or more design goals. The design of the optical metrology system is optimized by using collected design goal data in comparison to the set two or more design goals. In one embodiment, the optical metrology system is used for stand alone metrology systems. In another embodiment, the optical metrology system is integrated with a fabrication cluster in semiconductor manufacturing. | 12-24-2009 |
| 20100118316 | AUTO FOCUS ARRAY DETECTOR OPTIMIZED FOR OPERATING OBJECTIVES - Provided are an apparatus and a method of measuring structures on a workpiece using an optical metrology system, the optical metrology system comprising an auto focus subsystem which includes a motion control system and a focus detector. The focus detector includes an array of sensors where each sensor has identification (ID). The focus detector measures the focus beam and converts the measurements into a focus signal for each sensor. The focus signal and associated ID of each sensor are transmitted to a processor that generates a best focus instruction. A motion control system utilizes the best focus instruction to move the workpiece to the best focus location. The auto focusing of the workpiece is performed to meet set operating objectives of the auto focus subsystem. | 05-13-2010 |
| 20100245807 | OPTIMIZING SENSITIVITY OF OPTICAL METROLOGY MEASUREMENTS - Provided is a method of optimizing sensitivity of measurements of an optical metrology tool using two or more illumination beams directed to a structure on a workpiece comprising selecting target structures for measurement, obtaining diffraction signals off the selected structures as a function of angle of incidence for each illumination beam, determining a selected angle of incidence for each of the two or more illumination beams, setting sensitivity objectives for optical metrology measurements, developing a design for the optical metrology tool to achieve the corresponding selected angle of incidence of the two or more illumination beams, obtaining sensitivity data using the optical metrology tool, and if the sensitivity objectives are not met, adjusting the selection of target structures, the selected angle of incidence of the two or more illumination beams, the sensitivity objectives, and/or the design of the optical metrology tool, and iterating the developing of the design, obtaining sensitivity data, and comparing sensitivity data to sensitivity objectives until the sensitivity objectives are met. | 09-30-2010 |
