Abstract: Computer-implemented methods of optimizing a process simulation model that predicts a result of a semiconductor device fabrication operation to process parameter values characterizing the semiconductor device fabrication operation are disclosed. The methods involve generating cost values using a computationally predicted result of the semiconductor device fabrication operation and a metrology result produced, at least in part, by performing the semiconductor device fabrication operation in a reaction chamber operating under a set of fixed process parameter values. The determination of the parameters of the process simulation model may employ pre-process profiles, via optimization of the resultant post-process profiles of the parameters against profile metrology results. Cost values for, e.g., optical scatterometry, scanning electron microscopy and transmission electron microscopy may be used to guide optimization.

Abstract: Computer-implemented methods of optimizing a process simulation model that predicts a result of a semiconductor device fabrication operation to process parameter values characterizing the semiconductor device fabrication operation are disclosed. The methods involve generating cost values using a computationally predicted result of the semiconductor device fabrication operation and a metrology result produced, at least in part, by performing the semiconductor device fabrication operation in a reaction chamber operating under a set of fixed process parameter values. The determination of the parameters of the process simulation model may employ pre-process profiles, via optimization of the resultant post-process profiles of the parameters against profile metrology results. Cost values for, e.g., optical scatterometry, scanning electron microscopy and transmission electron microscopy may be used to guide optimization.

Abstract: A method for controlling a semiconductor fabrication process includes determining a representative feature within a given area on a wafer. The representative feature has a critical dimension (CD) response to a specified process control parameter that is correlated to a CD response to the specified process control parameter of other features within the given area on the wafer. A CD adjustment is determined for the representative feature to achieve a target CD for the representative feature. The CD response to the specified process control parameter for the representative feature and the CD adjustment for the representative feature are used to determine an adjustment to the specified process control parameter that will drive a CD of the representative feature to the target critical dimension for the representative feature. A process controller is updated to implement the adjustment to the specified process control parameter during subsequent processing of another wafer.

Abstract: A system includes sensors, an interface and a controller. The interface receives feedback signals from the sensors. At least some of the sensors are disposed in an electrostatic chuck. The feedback signals are indicative respectively of fields of a heating plate of the electrostatic chuck. The controller, based on the fields and sets of calibration values, estimates values of a first field respectively for multiple points on a substrate. Each of the sets of calibration values corresponds respectively to one of multiple actuators. The calibration values, in each of the sets of calibration values, define amounts of contribution provided by a respective one of the actuators to the first field for the points. The controller changes physical states of the actuators based on the estimated values of the first field of the points to provide a predetermined temperature distribution profile across the electrostatic chuck.

Abstract: A substrate support in a substrate processing system includes an inner portion arranged to support a substrate, an edge ring surrounding the inner portion, and a controller. The controller at least one of raises the edge ring to selectively cause the edge ring to engage the substrate and lowers the inner portion to selectively cause the edge ring to engage the substrate. The controller determines when the edge ring engages the substrate and calculates at least one characteristic of the substrate processing system based on the determination of when the edge ring engages the substrate.

Abstract: Computer-implemented methods of optimizing a process simulation model that predicts a result of a semiconductor device fabrication operation to process parameter values characterizing the semiconductor device fabrication operation are disclosed. The methods involve generating cost values using a computationally predicted result of the semiconductor device fabrication operation and a metrology result produced, at least in part, by performing the semiconductor device fabrication operation in a reaction chamber operating under a set of fixed process parameter values. The determination of the parameters of the process simulation model may employ pre-process profiles, via optimization of the resultant post-process profiles of the parameters against profile metrology results. Cost values for, e.g., optical scatterometry, scanning electron microscopy and transmission electron microscopy may be used to guide optimization.

Abstract: A system for controlling a condition of a wafer processing chamber is disclosed. According the principles of the present disclosure, the system includes memory and a first controller. The memory stores a plurality of profiles of respective ones of a plurality of first control elements. The plurality of first control elements are arranged throughout the chamber. The first controller determines non-uniformities in a substrate processing parameter associated with the plurality of first control elements. The substrate processing parameter is different than the condition of the chamber. The first controller adjusts at least one of the plurality of profiles based on the non-uniformities in the substrate processing parameter and a sensitivity of the substrate processing parameter to the condition.

Abstract: Computer-implemented methods of optimizing a process simulation model that predicts a result of a semiconductor device fabrication operation to process parameter values characterizing the semiconductor device fabrication operation are disclosed. The methods involve generating cost values using a computationally predicted result of the semiconductor device fabrication operation and a metrology result produced, at least in part, by performing the semiconductor device fabrication operation in a reaction chamber operating under a set of fixed process parameter values. The determination of the parameters of the process simulation model may employ pre-process profiles, via optimization of the resultant post-process profiles of the parameters against profile metrology results. Cost values for, e.g., optical scatterometry, scanning electron microscopy and transmission electron microscopy may be used to guide optimization.

Abstract: A method for controlling a semiconductor fabrication process includes determining a representative feature within a given area on a wafer. The representative feature has a critical dimension (CD) response to a specified process control parameter that is correlated to a CD response to the specified process control parameter of other features within the given area on the wafer. A CD adjustment is determined for the representative feature to achieve a target CD for the representative feature. The CD response to the specified process control parameter for the representative feature and the CD adjustment for the representative feature are used to determine an adjustment to the specified process control parameter that will drive a CD of the representative feature to the target critical dimension for the representative feature. A process controller is updated to implement the adjustment to the specified process control parameter during subsequent processing of another wafer.

Abstract: Computer-implemented methods of optimizing a process simulation model that predicts a result of a semiconductor device fabrication operation to process parameter values characterizing the semiconductor device fabrication operation are disclosed. The methods involve generating cost values using a computationally predicted result of the semiconductor device fabrication operation and a metrology result produced, at least in part, by performing the semiconductor device fabrication operation in a reaction chamber operating under a set of fixed process parameter values. The determination of the parameters of the process simulation model may employ pre-process profiles, via optimization of the resultant post-process profiles of the parameters against profile metrology results. Cost values for, e.g., optical scatterometry, scanning electron microscopy and transmission electron microscopy may be used to guide optimization.

Abstract: A system includes sensors, an interface and a controller. The interface receives feedback signals from the sensors. At least some of the sensors are disposed in an electrostatic chuck. The feedback signals are indicative respectively of fields of a heating plate of the electrostatic chuck. The controller, based on the fields and sets of calibration values, estimates values of a first field respectively for multiple points on a substrate. Each of the sets of calibration values corresponds respectively to one of multiple actuators. The calibration values, in each of the sets of calibration values, define amounts of contribution provided by a respective one of the actuators to the first field for the points. The controller changes physical states of the actuators based on the estimated values of the first field of the points to provide a predetermined temperature distribution profile across the electrostatic chuck.

Abstract: Computer-implemented methods of optimizing a process simulation model that predicts a result of a semiconductor device fabrication operation to process parameter values characterizing the semiconductor device fabrication operation are disclosed. The methods involve generating cost values using a computationally predicted result of the semiconductor device fabrication operation and a metrology result produced, at least in part, by performing the semiconductor device fabrication operation in a reaction chamber operating under a set of fixed process parameter values. The determination of the parameters of the process simulation model may employ pre-process profiles, via optimization of the resultant post-process profiles of the parameters against profile metrology results. Cost values for, e.g., optical scatterometry, scanning electron microscopy and transmission electron microscopy may be used to guide optimization.

Abstract: A system including a controller, an interface, and a calibration controller. The controller is configured to (i) select a set of fields, and (ii) based on the set of fields, supply control effort to first actuators in zones of a chamber. The interface is configured to receive feedback signals from sensors. The feedback signals are indicative of fields respectively of the zones. The controller is configured to adjust an amount of control effort supplied to the actuators based on the fields. The calibration controller is configured to, based on the fields, generate calibration values for each of the sensors. The calibration values for each of the sensors are indicative of field contributions corresponding respectively to the actuators.

Abstract: A substrate support in a substrate processing system includes an inner portion arranged to support a substrate, an edge ring surrounding the inner portion, and a controller. The controller, to selectively cause the edge ring to engage the substrate and tilt the substrate, controls at least one actuator to at least one of raise and lower the edge ring and raise and lower the inner portion of the substrate support. The controller determines an alignment of a measurement device in the substrate processing system based on a signal reflected from a surface of the substrate when the substrate is tilted.

Abstract: A substrate support in a substrate processing system includes an inner portion arranged to support a substrate, an edge ring surrounding the inner portion, and a controller. The controller, to selectively cause the edge ring to engage the substrate and tilt the substrate, controls at least one actuator to at least one of raise and lower the edge ring and raise and lower the inner portion of the substrate support. The controller determines an alignment of a measurement device in the substrate processing system based on a signal reflected from a surface of the substrate when the substrate is tilted.

Abstract: A substrate support in a substrate processing system includes an inner portion arranged to support a substrate, an edge ring surrounding the inner portion, and a controller. The controller at least one of lowers the edge ring to selectively cause the edge ring to engage the substrate and raises the inner portion to selectively cause the edge ring to engage the substrate. The controller determines when the edge ring engages the substrate and calculates at least one characteristic of the substrate processing system based on the determination of when the edge ring engages the substrate.

Abstract: A system for controlling a condition of a wafer processing chamber is disclosed. According the principles of the present disclosure, the system includes memory and a first controller. The memory stores a plurality of profiles of respective ones of a plurality of first control elements. The plurality of first control elements are arranged throughout the chamber. The first controller determines non-uniformities in a substrate processing parameter associated with the plurality of first control elements. The substrate processing parameter is different than the condition of the chamber. The first controller adjusts at least one of the plurality of profiles based on the non-uniformities in the substrate processing parameter and a sensitivity of the substrate processing parameter to the condition.

Abstract: A system including a controller, an interface, and a calibration controller. The controller is configured to (i) select a set of fields, and (ii) based on the set of fields, supply control effort to first actuators in zones of a chamber. The interface is configured to receive feedback signals from sensors. The feedback signals are indicative of fields respectively of the zones. The controller is configured to adjust an amount of control effort supplied to the actuators based on the fields. The calibration controller is configured to, based on the fields, generate calibration values for each of the sensors. The calibration values for each of the sensors are indicative of field contributions corresponding respectively to the actuators.