Abstract:
A method includes determining a plurality of features of a first original image of a first product that are expected to be different for one or more products to be produced via manufacturing parameters of a manufacturing process compared to the first product. The method further includes adjusting one or more of the plurality of features of the first original image to generate a first synthetic image. The method further includes providing a plurality of images including the first original image and the first synthetic image to train a machine learning model to generate a trained machine learning model configured to generate output associated with updating the manufacturing parameters of the manufacturing process.
Abstract:
Electrostatic chucks with variable pixelated magnetic field are described. For example, an electrostatic chuck (ESC) includes a ceramic plate having a front surface and a back surface, the front surface for supporting a wafer or substrate. A base is coupled to the back surface of the ceramic plate. A plurality of electromagnets is disposed in the base, the plurality of electromagnets configured to provide pixelated magnetic field tuning capability for the ESC.
Abstract:
Implementations described herein provide a chamber lid assembly. In one embodiment, a chamber lid assembly includes a heater embedded in a dielectric body forming a boundary of a processing chamber, wherein the heater has one or more heating zones that are independently controlled.
Abstract:
Electrostatic chucks with variable pixelated magnetic field are described. For example, an electrostatic chuck (ESC) includes a ceramic plate having a front surface and a back surface, the front surface for supporting a wafer or substrate. A base is coupled to the back surface of the ceramic plate. A plurality of electromagnets is disposed in the base, the plurality of electromagnets configured to provide pixelated magnetic field tuning capability for the ESC.
Abstract:
In an optimized method to apply a plasma sprayed coating of a yttrium containing oxide onto an article, a plasma power of between about 89-91 kW is selected for a plasma spraying system. Gas is flowed through the plasma spraying system at a selected gas flow rate of about 115-130 L/min. Ceramic powder comprising a yttrium containing oxide is fed into the plasma spraying system at a selected powder feed rate of about 10-30 g/min. A yttrium dominant ceramic coating is then formed on the article based on the selected power, the selected gas flow rate and the selected powder feed rate.
Abstract:
Electrostatic chucks with variable pixelated magnetic field are described. For example, an electrostatic chuck (ESC) includes a ceramic plate having a front surface and a back surface, the front surface for supporting a wafer or substrate. A base is coupled to the back surface of the ceramic plate. A plurality of electromagnets is disposed in the base, the plurality of electromagnets configured to provide pixelated magnetic field tuning capability for the ESC.
Abstract:
Embodiments may also include a residual chemical reaction diagnostic device. The residual chemical reaction diagnostic device may include a substrate and a residual chemical reaction sensor formed on the substrate. In an embodiment, the residual chemical reaction sensor provides electrical outputs in response to the presence of residual chemical reactions. In an embodiment, the substrate is a device substrate, and the sensor is formed in a scribe line of the device substrate. In an alternative embodiment, the substrate is a process development substrate. In some embodiments, the residual chemical reaction sensor includes, a first probe pad, wherein a plurality of first arms extend out from the first probe pad, and a second probe pad, wherein a plurality of second arms extend out from the second probe pad and are interdigitated with the first arms.
Abstract:
A machined ceramic article having an initial surface defect density and an initial surface roughness is provided. The machined ceramic article is heated to a temperature range between about 1000° C. and about 1800° C. at a ramping rate of about 0.1° C. per minute to about 20° C. per minute. The machined ceramic article is heat-treated in air atmosphere. The machined ceramic article is heat treated at one or more temperatures within the temperature range for a duration of up to about 24 hours. The machined ceramic article is then cooled at the ramping rate, wherein after the heat treatment the machined ceramic article has a reduced surface defect density and a reduced surface roughness.
Abstract:
A machined ceramic article having an initial surface defect density and an initial surface roughness is provided. The machined ceramic article is heated to a temperature range between about 1000° C. and about 1800° C. at a ramping rate of about 0.1° C. per minute to about 20° C. per minute. The machined ceramic article is heat-treated in air atmosphere. The machined ceramic article is heat treated at one or more temperatures within the temperature range for a duration of up to about 24 hours. The machined ceramic article is then cooled at the ramping rate, wherein after the heat treatment the machined ceramic article has a reduced surface defect density and a reduced surface roughness.
Abstract:
A method includes providing attributes of a manufacturing process and an image of a product associated with the manufacturing process to a trained machine learning model. The method further includes obtaining, from the trained machine learning model, predictive data. The method further includes determining, based on the predictive data, image measurements of the image of the product associated with the manufacturing process. Manufacturing parameters of the manufacturing process are to be updated based on the image measurements.