Abstract: Systems and methods are provided for leveraging different data repositories. One example computer-implemented method includes receiving a transfer request for a transfer from a sender in a first region to a recipient in a second region and determining whether the transfer request satisfies a regulation associated with the first and/or second region for information related to the recipient and/or sender. The method also includes submitting an identity request for the recipient and/or sender to an identity network, in response to the transfer request failing to satisfy the regulation, and receiving information regarding the recipient and/or sender, in response to the identity request, from the identity network, where the information includes identifying information for the recipient and/or sender. The method then includes compiling and submitting a transfer request for the transfer to an associated network, whereby the transfer request is submitted to be completed.

Abstract: Process recipe data associated a process to be performed for a substrate at a process chamber is provided as input to a trained machine learning model. A set of process recipe settings for the process that minimizes scratching on one or more surfaces of the substrate is determined based on one or more outputs of the machine learning model. The process is performed for the substrate at the process chamber in accordance with the determined set of process recipe settings.

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: Process recipe data associated a process to be performed for a substrate at a process chamber is provided as input to a trained machine learning model. A set of process recipe settings for the process that minimizes scratching on one or more surfaces of the substrate is determined based on one or more outputs of the machine learning model. The process is performed for the substrate at the process chamber in accordance with the determined set of process recipe settings.

Abstract: Methods and systems for reducing substrate particle scratching using machine learning are provided. A machine learning model is trained to predict process recipe settings for a substrate temperature control process to be performed for a current substrate at a manufacturing system. First training data and second training data are generated for the machine learning model. The first training data includes historical data associated with prior process recipe settings for a prior substrate temperature control process performed for a prior substrate at a prior process chamber. The second training data is associated with a historical scratch profile of one or more surfaces of the prior substrate after performance of the prior substrate temperature control process according to the prior process recipe settings.

Abstract: Methods, software systems and processes to develop surrogate model-based optimizers for controlling and optimizing flow and pressure of purges between a showerhead and a heater having a substrate support to control non-uniformity inherent in a processing chamber due to geometric configuration and process regimes. The flow optimizer process utilizes experimental data from optimal process space coverage models, generated simulation data and statistical machine learning tools (i.e. regression models and global optimizers) to predict optimal flow rates for any user-specified process regime.

Abstract: Methods and systems for reducing substrate particle scratching using machine learning are provided. A machine learning model is trained to predict process recipe settings for a substrate temperature control process to be performed for a current substrate at a manufacturing system. First training data and second training data are generated for the machine learning model. The first training data includes historical data associated with prior process recipe settings for a prior substrate temperature control process performed for a prior substrate at a prior process chamber. The second training data is associated with a historical scratch profile of one or more surfaces of the prior substrate after performance of the prior substrate temperature control process according to the prior process recipe settings.

Abstract: A method including receiving, by a processing device, a first selection of at least one of a first fabrication process or first manufacturing equipment to perform manufacturing operations of the first fabrication process. The method can further include inputting the first selection into a digital replica of the first manufacturing equipment wherein the digital replica outputs physical conditions of the first fabrication process. The method may further include determining environmental resource usage data indicative of a first environmental resource consumption of the first fabrication process run on the first manufacturing equipment based on the physical conditions of the first fabrication process. The processing device may further determine a modification to the first fabrication process that reduces the environmental resource consumption of the first fabrication process run on the first manufacturing equipment.

Abstract: Methods, software systems and processes to develop surrogate model-based optimizers for controlling and optimizing flow and pressure of purges between a showerhead and a heater having a substrate support to control non-uniformity inherent in a processing chamber due to geometric configuration and process regimes. The flow optimizer process utilizes experimental data from optimal process space coverage models, generated simulation data and statistical machine learning tools (i.e. regression models and global optimizers) to predict optimal flow rates for any user-specified process regime.

Abstract: A method, system and computer-usable medium are disclosed for reducing communication payload in an e-commerce system. Certain embodiments include a computer-implemented method for storing, at a product host platform, product configuration data including, item identifiers associated with each item of a product configuration, descriptor data respectively associated with each item identifier, and a reductive identifier respectively associated with each item identifier, wherein the reductive identifier associated with each item identifier is generated, at least in part, from the descriptor data of the item identifier. In certain embodiments, the reductive identifiers stored in the product configuration data at the order platform are compared with the reductive identifiers in master product configuration data stored at the product host platform. In certain embodiments, the differences are used as a basis to update the configuration data at the order platform.

Abstract: Embodiments described herein include processes for generating a hybrid model for modeling processes in semiconductor processing equipment. In a particular embodiment, method of creating a hybrid machine learning model comprises identifying a first set of cases spanning a first range of process and/or hardware parameters, and running experiments in a lab for the first set of cases. The method may further comprise compiling experimental outputs from the experiments, and running physics based simulations for the first set of cases. In an embodiment, the method may further comprise compiling model outputs from the simulations, and correlating the model outputs with the experimental outputs with a machine learning algorithm to provide the hybrid machine learning model.

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: Systems and methods are provided for use in appending log entries to a data structure. One exemplary method includes receiving, at a communication device, a log entry from a terminal and signing the log entry with a private key of a key pair specific to the communication device. The method also includes transmitting the signed log entry to an identity provider (IDP) and receiving, by the communication device, from the IDP, a signed, encrypted log entry. The method further includes verifying, by the communication device, a signature of the signed, encrypted log entry based on a public key associated with a key pair specific to the IDP and then appending the encrypted log entry to a digital identity included in the communication device.

Abstract: Heaters having a body with having a top and bottom comprising pyrolytic boron nitride (PBN), a first heater electrode and a second heater electrode are described. The heater electrodes can be enclosed within an electrically insulating standoff and connected to separate busbars to provide power. Heater assemblies including one or more of the heaters and processing chambers including the heater assemblies are also described.

Abstract: A method, system and computer-usable medium are disclosed for reducing communication payload in an e-commerce system. Certain embodiments include a computer-implemented method for storing, at a product host platform, product configuration data including, item identifiers associated with each item of a product configuration, descriptor data respectively associated with each item identifier, and a reductive identifier respectively associated with each item identifier, wherein the reductive identifier associated with each item identifier is generated, at least in part, from the descriptor data of the item identifier. In certain embodiments, the reductive identifiers stored in the product configuration data at the order platform are compared with the reductive identifiers in master product configuration data stored at the product host platform. In certain embodiments, the differences are used as a basis to update the configuration data at the order platform.

Abstract: Apparatus and methods to deposit a film using a batch processing chamber with a plurality of heating zones are described. The film is deposited on one or more substrates and the uniformity of the deposition thickness is determined at a plurality of points. The heating zones set points are applied to a sensitivity matrix and new temperature or power set points for the heating zones are determined and set. One or more substrates are processed using the new set points and the thickness uniformity is determined and may be adjusted again to increase the uniformity.

Abstract: Embodiments of the present disclosure generally relate to a susceptor for thermal processing of semiconductor substrates. In one embodiment, the susceptor includes a first rim, an inner region coupled to and surrounded by the first rim, and one or more annular protrusions formed on the inner region. The one or more annular protrusions may be formed on the inner region at a location corresponding to the location where a valley is formed on the substrate, and the one or more annular protrusions help reduce or eliminate the formation of the valley.

Abstract: A dynamic propulsion system may be implemented to recover some or all of the wasted energy during a flight. The dynamic propulsion system may include one or more propellers that are configured to act as a propulsion system when altitude is rising and act as a windmill to generate energy to charge a battery during descent. The one or more propellers may include blades that are configured to adjust their angle of attack or pitch on command to switch from propulsion mode to regenerative mode and vice versa.

Abstract: Implementations of the present disclosure generally relate to a susceptor for thermal processing of semiconductor substrates. In one implementation, the susceptor includes a first rim surrounding and coupled to an inner region, and a second rim disposed between the inner rim and the first rim. The second rim includes an angled support surface having a plurality of cut-outs formed therein, and the angled support surface is inclined with respect to a top surface of the inner region.