Abstract: Multi-pixel sensors such as camera sensors may be configured to capture two-dimensional and/or three-dimensional images of the interior of a process chamber or other fabrication tool. The sensors may be configured to capture pixelated electromagnetic radiation intensity information from within the interior of such process chamber before, during, and/or after processing of a substrate in the chamber. Such sensors may also be utilized for control, predictive, and/or diagnostic applications.

Abstract: Multi-pixel sensors such as camera sensors may be configured to capture two-dimensional and/or three-dimensional images of the interior of a process chamber or other fabrication tool. The sensors may be configured to capture pixelated electromagnetic radiation intensity information from within the interior of such process chamber before, during, and/or after processing of a substrate in the chamber. Such sensors may also be utilized for control, predictive, and/or diagnostic applications.

Abstract: Methods, systems, and computer programs are presented for predicting the performance of semiconductor manufacturing equipment operations. One method includes an operation for obtaining machine-learning (ML) models, each model related to predicting a performance metric for an operation of a semiconductor manufacturing tool. Further, each ML model utilizes features defining inputs for the ML model. The method further includes an operation for receiving a process definition for manufacturing a product with the semiconductor manufacturing tool. One or more ML models are utilized to estimate a performance of the process definition used in the semiconductor manufacturing tool. Additionally, the method includes presenting, on a display, results showing the estimate of the performance of the manufacturing of the product.

Abstract: The present invention provides a superior method for the removal of nitride semiconductor thin films, thick films, heterostructures, and bulk material from initial substrates and/or templates. The method utilizes specially patterned mask layers between the initial substrates/templates and the nitride semiconductors to decrease adhesion between the nitride semiconductor and underlying material. Thermal stresses generated upon cooling the nitride semiconductor from its deposition temperature trigger spontaneous separation of the nitride semiconductor from the initial substrate or template at the mask layer. The invention remedies deficiencies in the prior art by providing a simple, reproducible, and effective means of removing initial substrates and templates from a variety of nitride semiconductor layers and structures.