Abstract: An example microelectromechanical system (MEMS) force sensor is described herein. The MEMS force sensor can include a sensor die configured to receive an applied force. The sensor die can include a first substrate and a second substrate, where a cavity is formed in the first substrate, and where at least a portion of the second substrate defines a deformable membrane. The MEMS force sensor can also include an etch stop layer arranged between the first substrate and the second substrate, and a sensing element arranged on a surface of the second substrate. The sensing element can be configured to convert a strain on the surface of the membrane substrate to an analog electrical signal that is proportional to the strain.

Abstract: In one embodiment, a ruggedized wafer level microelectromechanical (“MEMS”) force sensor includes a base and a cap. The MEMS force sensor includes a flexible membrane and a sensing element. The sensing element is electrically connected to integrated complementary metal-oxide-semiconductor (“CMOS”) circuitry provided on the same substrate as the sensing element. The CMOS circuitry can be configured to amplify, digitize, calibrate, store, and/or communicate force values through electrical terminals to external circuitry.

Abstract: Systems and methods for automated resource allocation during a computational simulation are described herein. An example method includes analyzing a set of simulation inputs to determine a first set of computing resources for performing a simulation, and starting the simulation with the first set of computing resources. The method also includes dynamically analyzing at least one attribute of the simulation to determine a second set of computing resources for performing the simulation, and performing the simulation with the second set of computing resources. The second set of computing resources is different than the first set of computing resources.

Abstract: Described herein is a ruggedized microelectromechanical (“MEMS”) force sensor including both piezoresistive and piezoelectric sensing elements and integrated with complementary metal-oxide-semiconductor (“CMOS”) circuitry on the same chip. The sensor employs piezoresistive strain gauges for static force and piezoelectric strain gauges for dynamic changes in force. Both piezoresistive and piezoelectric sensing elements are electrically connected to integrated circuits provided on the same substrate as the sensing elements. The integrated circuits can be configured to amplify, digitize, calibrate, store, and/or communicate force values electrical terminals to external circuitry.

Abstract: Described herein is a ruggedized microelectromechanical (“MEMS”) force sensor including both piezoresistive and piezoelectric sensing elements and integrated with complementary metal-oxide-semiconductor (“CMOS”) circuitry on the same chip. The sensor employs piezoresistive strain gauges for static force and piezoelectric strain gauges for dynamic changes in force. Both piezoresistive and piezoelectric sensing elements are electrically connected to integrated circuits provided on the same substrate as the sensing elements. The integrated circuits can be configured to amplify, digitize, calibrate, store, and/or communicate force values electrical terminals to external circuitry.

Abstract: Systems and methods for automated resource allocation during a computational simulation are described herein. An example method includes analyzing a set of simulation inputs to determine a first set of computing resources for performing a simulation, and starting the simulation with the first set of computing resources. The method also includes dynamically analyzing at least one attribute of the simulation to determine a second set of computing resources for performing the simulation, and performing the simulation with the second set of computing resources. The second set of computing resources is different than the first set of computing resources.

Abstract: Described herein is a ruggedized microelectromechanical (“MEMS”) force sensor including both piezoresistive and piezoelectric sensing elements and integrated with complementary metal-oxide-semiconductor (“CMOS”) circuitry on the same chip. The sensor employs piezoresistive strain gauges for static force and piezoelectric strain gauges for dynamic changes in force. Both piezoresistive and piezoelectric sensing elements are electrically connected to integrated circuits provided on the same substrate as the sensing elements. The integrated circuits can be configured to amplify, digitize, calibrate, store, and/or communicate force values electrical terminals to external circuitry.

Abstract: Systems and methods are provided to move the solving of multi-physics engineering simulations away from specific CAE, or combination CAD and CAE, applications. In one embodiment, an Application Programming Interface (API) is provided that can be integrated into any device, system, application, or software workflow. The API exposes a series of functions or modules that a user can use to create a simulation file that includes parameters such as a model for the simulation, physics for the simulation, timings for the simulation, and other parameters. The simulation file may then be executed on one or more nodes of a cloud-based computer cluster, and the results of executing the simulation can be provided back to the user. The user may then visualize the results using their preferred device, software, application, or workflow.

Abstract: Described herein is a ruggedized microelectromechanical (“MEMS”) force sensor including both piezoresistive and piezoelectric sensing elements and integrated with complementary metal-oxide-semiconductor (“CMOS”) circuitry on the same chip. The sensor employs piezoresistive strain gauges for static force and piezoelectric strain gauges for dynamic changes in force. Both piezoresistive and piezoelectric sensing elements are electrically connected to integrated circuits provided on the same substrate as the sensing elements. The integrated circuits can be configured to amplify, digitize, calibrate, store, and/or communicate force values electrical terminals to external circuitry.

Abstract: An example microelectromechanical system (MEMS) force sensor is described herein. The MEMS force sensor can include a sensor die configured to receive an applied force. The sensor die can include a first substrate and a second substrate, where a cavity is formed in the first substrate, and where at least a portion of the second substrate defines a deformable membrane. The MEMS force sensor can also include an etch stop layer arranged between the first substrate and the second substrate, and a sensing element arranged on a surface of the second substrate. The sensing element can be configured to convert a strain on the surface of the membrane substrate to an analog electrical signal that is proportional to the strain.

Abstract: In one embodiment, a ruggedized wafer level microelectromechanical (“MEMS”) force sensor includes a base and a cap. The MEMS force sensor includes a flexible membrane and a sensing element. The sensing element is electrically connected to integrated complementary metal-oxide-semiconductor (“CMOS”) circuitry provided on the same substrate as the sensing element. The CMOS circuitry can be configured to amplify, digitize, calibrate, store, and/or communicate force values through electrical terminals to external circuitry.

Abstract: Described herein is a ruggedized microelectromechanical (“MEMS”) force sensor including both piezoresistive and piezoelectric sensing elements and integrated with complementary metal-oxide-semiconductor (“CMOS”) circuitry on the same chip. The sensor employs piezoresistive strain gauges for static force and piezoelectric strain gauges for dynamic changes in force. Both piezoresistive and piezoelectric sensing elements are electrically connected to integrated circuits provided on the same substrate as the sensing elements. The integrated circuits can be configured to amplify, digitize, calibrate, store, and/or communicate force values electrical terminals to external circuitry.

Abstract: An example microelectromechanical system (MEMS) force sensor is described herein. The MEMS force sensor can include a sensor die configured to receive an applied force. The sensor die can include a first substrate and a second substrate, where a cavity is formed in the first substrate, and where at least a portion of the second substrate defines a deformable membrane. The MEMS force sensor can also include an etch stop layer arranged between the first substrate and the second substrate, and a sensing element arranged on a surface of the second substrate. The sensing element can be configured to convert a strain on the surface of the membrane substrate to an analog electrical signal that is proportional to the strain.

Abstract: Systems and methods for automated resource allocation during a computational simulation are described herein. An example method includes analyzing a set of simulation inputs to determine a first set of computing resources for performing a simulation, and starting the simulation with the first set of computing resources. The method also includes dynamically analyzing at least one attribute of the simulation to determine a second set of computing resources for performing the simulation, and performing the simulation with the second set of computing resources. The second set of computing resources is different than the first set of computing resources.

Abstract: In one embodiment, a ruggedized wafer level microelectromechanical (“MEMS”) force sensor includes a base and a cap. The MEMS force sensor includes a flexible membrane and a sensing element. The sensing element is electrically connected to integrated complementary metal-oxide-semiconductor (“CMOS”) circuitry provided on the same substrate as the sensing element. The CMOS circuitry can be configured to amplify, digitize, calibrate, store, and/or communicate force values through electrical terminals to external circuitry.

Abstract: Described herein is a ruggedized microelectromechanical (“MEMS”) force sensor including both piezoresistive and piezoelectric sensing elements and integrated with complementary metal-oxide-semiconductor (“CMOS”) circuitry on the same chip. The sensor employs piezoresistive strain gauges for static force and piezoelectric strain gauges for dynamic changes in force. Both piezoresistive and piezoelectric sensing elements are electrically connected to integrated circuits provided on the same substrate as the sensing elements. The integrated circuits can be configured to amplify, digitize, calibrate, store, and/or communicate force values electrical terminals to external circuitry.

Abstract: Systems and methods for automated resource allocation during a computational simulation are described herein. An example method includes analyzing a set of simulation inputs to determine a first set of computing resources for performing a simulation, and starting the simulation with the first set of computing resources. The method also includes dynamically analyzing at least one attribute of the simulation to determine a second set of computing resources for performing the simulation, and performing the simulation with the second set of computing resources. The second set of computing resources is different than the first set of computing resources.

Abstract: An example microelectromechanical system (MEMS) force sensor is described herein. The MEMS force sensor can include a sensor die configured to receive an applied force. The sensor die can include a first substrate and a second substrate, where a cavity is formed in the first substrate, and where at least a portion of the second substrate defines a deformable membrane. The MEMS force sensor can also include an etch stop layer arranged between the first substrate and the second substrate, and a sensing element arranged on a surface of the second substrate. The sensing element can be configured to convert a strain on the surface of the membrane substrate to an analog electrical signal that is proportional to the strain.

Abstract: Described herein are methods and systems for the estimation of the computational cost of simulation using a machine learning model. An example method includes inputting a feature data set into a machine learning model. The feature data set includes model geometry metadata and simulation metadata. The method further includes predicting, using the machine learning model, a computational cost characteristic for a simulation process.

Abstract: Systems and methods are provided to move the solving of multi-physics engineering simulations away from specific CAE, or combination CAD and CAE, applications. In one embodiment, an Application Programming Interface (API) is provided that can be integrated into any device, system, application, or software workflow. The API exposes a series of functions or modules that a user can use to create a simulation file that includes parameters such as a model for the simulation, physics for the simulation, timings for the simulation, and other parameters. The simulation file may then be executed on one or more nodes of a cloud-based computer cluster, and the results of executing the simulation can be provided back to the user. The user may then visualize the results using their preferred device, software, application, or workflow.