Abstract: A method includes receiving measurement data from multiple sensors positioned along a delivery line that delivers a liquid as a gas to one of a gas panel or a processing chamber; simulating, using a computer-generated model, one or more process parameters associated with the delivery line and a plurality of heater jackets positioned around the delivery line; comparing the measurement data with values of the one or more process parameters; and determining, based on at least a threshold deviation between the measurement data and the values of the one or more process parameters, that a fault exists that is associated with maintaining temperature within the delivery line consistent with a gaseous state of the liquid.

Abstract: A method includes receiving, from sensors, sensor data associated with processing a substrate via a processing chamber of substrate processing equipment. The sensor data includes a first subset received from one or more first sensors and a second subset received from one or more second sensors, the first subset being mapped to the second subset. The method further includes identifying model input data and model output data. The model output data is output from a physics-based model based on model input data. The method further includes training a machine learning model with data input including the first subset and the model input data, and target output data including the second subset and the model output data to tune calibration parameters of the machine learning model. The calibration parameters are to be used by the physics-based model to perform corrective actions associated with the processing chamber.

Abstract: A method and apparatus for improved temperature control of a substrate is disclosed. In one embodiment, a pedestal is disclosed that includes a top plate, and a base plate coupled to the top plate, wherein the top plate comprises a multi-zone heater and the base plate comprises a plurality of grooves formed in a bottom surface thereof.

Abstract: A method includes receiving measurement data from multiple sensors positioned along a delivery line that delivers a liquid as a gas to one of a gas panel or a processing chamber; simulating, using a computer-generated model, one or more process parameters associated with the delivery line and a plurality of heater jackets positioned around the delivery line; comparing the measurement data with values of the one or more process parameters; and determining, based on at least a threshold deviation between the measurement data and the values of the one or more process parameters, that a fault exists that is associated with maintaining temperature within the delivery line consistent with a gaseous state of the liquid.

Abstract: A system includes a controller that has a processor. The processor is configured to receive a first signal from a first oxygen sensor indicative of a first oxygen measurement and a second signal from a second oxygen sensor indicative of a second oxygen measurement. The first oxygen sensor is disposed upstream of a catalytic converter system and the second oxygen sensor is disposed downstream of the catalytic converter system. The processor is also configured to derive a plurality of oxygen storage estimates based on the first signal, the second signal, and a catalytic converter model. Each of the plurality of oxygen storage estimates represents an oxygen storage estimate for a corresponding cell of a plurality of cells in the catalytic converter system. Further, the processor is configured to derive a system oxygen storage estimate for the catalytic converter system based on the plurality of oxygen storage estimates.

Abstract: The disclosure described herein is a reduced toxicity rocket propellant comprising a liquid fuel and a liquid oxidizer that ignites spontaneously upon contact with each other. The rocket propellant includes a metal hydride catalyst. Multiple embodiments of the propellant include multiple compositions of liquid fuel.