Abstract: Forming an integrated circuit by first, forming a first fin and a second fin from a semiconductor layer, with an area between the first fin and the second fin, second, forming a dielectric layer covering at least a portion of the first fin, at least a portion of the second fin, and at least a portion of the area, and third, forming amorphous polysilicon covering a least a portion of the dielectric layer.

Abstract: A method for constructing a process performance prediction model for a material processing system, the method including the steps of: recording tool data for a plurality of observations during a process in a process tool, the tool data comprises a plurality of tool data parameters; recording process performance data for the plurality of observations during the process in the process tool, the process performance data comprises one or more process performance parameters; performing a partial least squares analysis using the tool data and the process performance data; and computing correlation data from the partial least squares analysis.

Abstract: A method for constructing a process performance prediction model for a material processing system, the method including the steps of: recording tool data for a plurality of observations during a process in a process tool, the tool data comprises a plurality of tool data parameters; recording process performance data for the plurality of observations during the process in the process tool, the process performance data comprises one or more process performance parameters; performing a partial least squares analysis using the tool data and the process performance data; and computing correlation data from the partial least squares analysis.

Abstract: A material processing system including a process tool and a process performance prediction system. The performance prediction system includes sensors coupled to the tool to measure tool data and a controller coupled to the sensors to receive tool data, where the controller is configured to predict the process performance for the tool using the tool data. A method for detecting a fault in a material processing system using a process performance prediction model is also provided. The method includes preparing the tool, initiating a process in the tool, and recording tool data to form to a tool data matrix. The method also includes performing a matrix multiplication of the tool data matrix and a correlation matrix to form predicted process performance data, where the correlation matrix includes the performance prediction model, comparing the predicted data with target data, and determining a fault condition of the processing system from the comparing step.

Abstract: A plasma processing system that comprises a process chamber, a plasma source, a light detection device and a controller. The controller is useful for determining a seasoning state of the plasma processing system. The present invention further provides a method of determining the seasoning state of a plasma processing system comprising the steps of forming a first plasma in the process chamber utilizing the plasma source; measuring a first signal related to light emitted from the first plasma using the light detection device and storing the first signal using the controller; forming a second plasma in the process chamber utilizing the plasma source; measuring a second signal related to light emitted from the second plasma using the light detection device and storing the second signal using the controller; and correlating a change between the first signal and the second signal with a seasoning state of the plasma processing system.

Abstract: A plasma processing system that comprises a process chamber, a plasma source, a light detection device and a controller. The controller is useful for determining a seasoning state of the plasma processing system. The present invention further provides a method of determining the seasoning state of a plasma processing system comprising the steps of forming a first plasma in the process chamber utilizing the plasma source; measuring a first signal related to light emitted from the first plasma using the light detection device and storing the first signal using the controller; forming a second plasma in the process chamber utilizing the plasma source; measuring a second signal related to light emitted from the second plasma using the light detection device and storing the second signal using the controller; and correlating a change between the first signal and the second signal with a seasoning state of the plasma processing system.