Abstract: Implementations disclosed describe, among other things, a system and a method of scanning a substrate with a beam of light and detecting for each of a set of locations of the substrate, a respective one of a set of intensity values associated with a beam of light reflected from (or transmitted through) the substrate. The detected intensity values are used to determine a profile of a thickness of the substrate.

Abstract: A cool cluster comprises one or more transfer chambers; a plurality of process chambers connected to the one or more transfer chambers; and a computing device of the tool cluster. The computing device is to receive first measurements generated by sensors of a first process chamber during or after a process is performed within the first process chamber; determine that the first process chamber is due for maintenance based on processing the first measurements using a first trained machine learning model; after maintenance has been performed on the first process chamber, receive second measurements generated by the sensors during or after a seasoning process is performed within the first process chamber; and determine that the first process chamber is ready to be brought back into service based on processing the second measurements using a second trained machine learning model.

Abstract: An organic light-emitting diode (OLED) deposition system includes two deposition chambers, a transfer chamber between the two deposition chambers, a metrology system having one or more sensors to perform measurements of the workpiece within the transfer chamber, and a control system to cause the system to form an organic light-emitting diode layer stack on the workpiece. Vacuum is maintained around the workpiece while the workpiece is transferred between the two deposition chambers and while retaining the workpiece within the transfer chamber. The control system is configured to cause the two deposition chambers to deposit two layers of organic material onto the workpiece, and to receive a first plurality of measurements of the workpiece in the transfer chamber from the metrology system.

Abstract: A system can provide in-situ analysis of at least some of a plurality of targets simultaneously during a fabrication process. The system can include a semiconductor processing tool having a chamber. The system can also include a sample arranged within the chamber, the sample having the plurality of targets with different feature orientations and/or feature geometries. The semiconductor processing tool can be configured to perform the fabrication process on the sample. Additionally, the system can include a metrology tool integrated with the semiconductor processing tool. The metrology tool can provide the in-situ analysis of at least some of the plurality of targets simultaneously during the fabrication process.

Abstract: A system includes a radiation source configured to emit a radiation beam. The system further includes a first optical sensor configured to detect a first intensity of a first portion of the radiation beam reflected from a surface of an object. The system further includes a second optical sensor configured to detect a second intensity of a second portion of the radiation beam scattered by the surface of the object. The system further includes a processing device communicatively coupled to the first optical sensor and the second optical sensor. The processing device is configured to determine at least one of a roughness or an emissivity of the surface of the object based on a comparison of the first intensity and the second intensity.

Abstract: Implementations disclosed describe a system that includes a deposition chamber, a light source to produce an incident beam of light, wherein the incident beam of light is to illuminate a region of the deposition chamber, and a camera to collect a scattered light originating from the illuminated region of the deposition chamber, wherein the scattered light is to be produced upon interaction of the first incident beam of light with particles inside the illuminated region of the deposition chamber. The described system may optionally have a processing device, coupled to the camera, to generate scattering data for a plurality of locations of the illuminated region, wherein the scattering data for each location comprises intensity of the scattered light originating from this location.

Abstract: An optical metrology model for in-line thickness measurements of a film overlying non-ideal structures on a substrate is generated by performing pre-measurements prior to deposition of the film and performing post-measurements after the deposition. The pre- and post-measurements are performed at at least one of multiple polarization angles or multiple orientations of the substrate. Differences in reflectance between the pre- and post-measurements are determined at the multiple polarization angles and the multiple orientations. At least one of the multiple polarization angles or the multiple orientations are identified where the differences in reflectance are indicative of a suppressed influence from the non-ideal structures. The optical metrology model is generated using the identified polarization angles and the identified orientations as inputs to a machine-learning algorithm.

Abstract: Implementations disclosed describe a system that includes a deposition chamber, a light source to produce an incident beam of light, wherein the incident beam of light is to illuminate a region of the deposition chamber, and a camera to collect a scattered light originating from the illuminated region of the deposition chamber, wherein the scattered light is to be produced upon interaction of the first incident beam of light with particles inside the illuminated region of the deposition chamber. The described system may optionally have a processing device, coupled to the camera, to generate scattering data for a plurality of locations of the illuminated region, wherein the scattering data for each location comprises intensity of the scattered light originating from this location.

Abstract: An organic light-emitting diode (OLED) deposition system includes two deposition chambers, a transfer chamber between the two deposition chambers, a metrology system having one or more sensors to perform measurements of the workpiece within the transfer chamber, and a control system to cause the system to form an organic light-emitting diode layer stack on the workpiece. Vacuum is maintained around the workpiece while the workpiece is transferred between the two deposition chambers and while retaining the workpiece within the transfer chamber. The control system is configured to cause the two deposition chambers to deposit two layers of organic material onto the workpiece, and to receive a first plurality of measurements of the workpiece in the transfer chamber from the metrology system.

Abstract: A system includes a radiation source configured to emit a radiation beam. The system further includes a first optical sensor configured to detect a first intensity of a first portion of the radiation beam reflected from a surface of an object. The system further includes a second optical sensor configured to detect a second intensity of a second portion of the radiation beam scattered by the surface of the object. The system further includes a processing device communicatively coupled to the first optical sensor and the second optical sensor. The processing device is configured to determine at least one of a roughness or an emissivity of the surface of the object based on a comparison of the first intensity and the second intensity.

Abstract: An organic light-emitting diode (OLED) deposition system includes two deposition chambers, a transfer chamber between the two deposition chambers, a metrology system having one or more sensors to perform measurements of the workpiece within the transfer chamber, and a control system to cause the system to form an organic light-emitting diode layer stack on the workpiece. Vacuum is maintained around the workpiece while the workpiece is transferred between the two deposition chambers and while retaining the workpiece within the transfer chamber. The control system is configured to cause the two deposition chambers to deposit two layers of organic material onto the workpiece, and to receive a first plurality of measurements of the workpiece in the transfer chamber from the metrology system.

Abstract: A cool cluster comprises one or more transfer chambers; a plurality of process chambers connected to the one or more transfer chambers; and a computing device of the tool cluster. The computing device is to receive first measurements generated by sensors of a first process chamber during or after a process is performed within the first process chamber; determine that the first process chamber is due for maintenance based on processing the first measurements using a first trained machine learning model; after maintenance has been performed on the first process chamber, receive second measurements generated by the sensors during or after a seasoning process is performed within the first process chamber; and determine that the first process chamber is ready to be brought back into service based on processing the second measurements using a second trained machine learning model.

Abstract: A substrate processing system comprises one or more transfer chambers; a plurality of process chambers connected to the one or more transfer chambers; and a computing device connected to each of the plurality of process chambers. The computing device is to receive first measurements generated by sensors of a first process chamber during or after a process is performed within the first process chamber; determine that the first process chamber is due for maintenance based on processing the first measurements using a first trained machine learning model; after maintenance has been performed on the first process chamber, receive second measurements generated by the sensors during or after a seasoning process is performed within the first process chamber; and determine that the first process chamber is ready to be brought back into service based on processing the second measurements using a second trained machine learning model.

Abstract: Described are systems and techniques directed to optical inspection of moving products (wafers, substrates, films, patterns) that are being transported to or from processing chambers in device manufacturing systems. Implementations include a system that has a first source of light to direct a first light to a first location on a surface of a product. The first light generates, at the first location, a first reflected light. The system further includes a first optical sensor to generate a first data representative of a first reflected light, and a processing device, in communication with the first optical sensor to determine, using the first data, a property of the product.

Abstract: Implementations disclosed describe a method of obtaining a first image of a sample using a first light, wherein the sample has been subjected to a processing operation associated with a change of a thickness of the sample. The method further includes weighing the sample to obtain a first mass of the sample. The method further includes determining, based at least in part on the first image of the sample and the first mass of the sample, one or more properties of the sample, such as the change of a thickness of the sample, a change of an refractive index of the sample, and/or a change of an optical density of the sample a distribution of the change of the thickness of the sample.

Abstract: Implementations disclosed describe an optical inspection device comprising a source of light to direct a light beam to a location on a surface of a wafer, the wafer being transported from a processing chamber, wherein the light beam is to generate, a reflected light, an optical sensor to collect a first data representative of a direction of the first reflected light, collect a second data representative of a plurality of values characterizing intensity of the reflected light at a corresponding one of a plurality of wavelengths, and a processing device, in communication with the optical sensor, to determine, using the first data, a position of the surface of the wafer; retrieve calibration data, and determine, using the position of the surface of the wafer, the second data, and the calibration data, a characteristic representative of a quality of the wafer.

Abstract: Implementations disclosed describe, among other things, a system and a method of scanning a substrate with a beam of light and detecting for each of a set of locations of the substrate, a respective one of a set of intensity values associated with a beam of light reflected from (or transmitted through) the substrate. The detected intensity values are used to determine a profile of a thickness of the substrate.

Abstract: Methods and systems for monitoring etch or deposition processes using image-based in-situ process monitoring techniques include illuminating a measurement area on a sample disposed in a process chamber. The measurement area is illuminated using an input beam generated remote from the process chamber and transmitted to a first viewing window of the process chamber by a first optical fiber. Portions of the first input beam reflected from the measurement area are transmitted from the first viewing window to an imaging sensor by a second optical fiber. A sequence of images is obtained at the imaging sensor, and a change in reflectance of pixels within each of the images is determined. The etch or deposition process is monitored based on the change in reflectance.

Abstract: An optical metrology model for in-line thickness measurements of a film overlying non-ideal structures on a substrate is generated by performing pre-measurements prior to deposition of the film and performing post-measurements after the deposition. The pre- and post-measurements are performed at at least one of multiple polarization angles or multiple orientations of the substrate. Differences in reflectance between the pre- and post-measurements are determined at the multiple polarization angles and the multiple orientations. At least one of the multiple polarization angles or the multiple orientations are identified where the differences in reflectance are indicative of a suppressed influence from the non-ideal structures.

Abstract: A substrate processing system comprises one or more transfer chambers; a plurality of process chambers connected to the one or more transfer chambers; and a computing device connected to each of the plurality of process chambers. The computing device is to receive first measurements generated by sensors of a first process chamber during or after a process is performed within the first process chamber; determine that the first process chamber is due for maintenance based on processing the first measurements using a first trained machine learning model; after maintenance has been performed on the first process chamber, receive second measurements generated by the sensors during or after a seasoning process is performed within the first process chamber; and determine that the first process chamber is ready to be brought back into service based on processing the second measurements using a second trained machine learning model.