Patent classifications
B81B2201/0285
Nanosheet MEMS Sensor Device and Method of Manufacture
A nanosheet MEMS sensor device and method are described for integrating the fabrication of nanosheet transistors (61) and MEMS sensors (62) in a single nanosheet process flow by forming separate nanosheet transistor and MEMS sensor stacks (12A-16A, 12B-16B) of alternating Si and SiGe layers which are selectively processed to form gate electrodes (49A-C) which replace the silicon germanium layers in the nanosheet transistor stack, to form silicon fixed electrodes using silicon layers (13B-2, 15B-2) on a first side of the MEMS sensor stack, and to form silicon cantilever electrodes using silicon layers (13B-1, 15B-1) on a second side of the MEMS sensor stack by forming a narrow trench opening (54) in the MEMS sensor stack to expose and remove remnant silicon germanium layers on the second side in the MEMS sensor stack.
Acoustic transducer assembly
The present disclosure relates to a sensor assembly (100) comprising: a base (102) having a host-device interface (104), a lid (108) mounted on the base (102) to form a housing (110), the lid (108) having an insulative structural core (112) between an inner metal skin (114) and an outer metal skin (116); and a transduction element (118) disposed in the housing (112). Advantageously, the lid (108) of the sensor assembly (100) can help to minimize and reduce undesirable thermo-acoustic effects produced by external environmental conditions that may result in acoustic artifacts.
MEMS sensor structure comprising mechanically preloaded suspension springs
A MEMS sensor comprising preloaded suspension springs and a method for mechanically preloading suspension springs of a MEMS sensor are described. The MEMS sensor comprises a MEMS support structure; a plurality of suspension springs connected to said support structure; and, a proof mass flexibly suspended by said suspension springs; wherein at least one of said suspension springs is mechanically preloaded with a compressive force for reducing the natural frequency of said proof mass.
Overload recovery optimization in microelectromechanical system application specific integrated circuit
Disclosed herein is a MEMS ASIC. In some examples, the MEMS ASIC can include a MEMS, an analog front end (AFE) amplifier, an analog-to-digital converter (ADC), an overload detector, and a high-ohmic (HO) block. The HO block and the MEMS can form a high-pass filter (HPF). The impedance of the HO block can be related to the DC operating level of the AFE amplifier and the cutoff frequency of the HPF. In some examples, an overload event can occur, and the overload detector can be configured to adjust the impedance of the HO block to reduce the settling time of the MEMS ASIC. Methods of using the MEMS ASIC to reduce the settling time of the MEMS ASIC due to an overload event are disclosed herein.
METHOD FOR PRODUCING DAMPER STRUCTURES ON A MICROMECHANICAL WAFER
A method for producing damper structures on a micromechanical wafer. The method includes: providing an at least partially UV-transparent master mold for molding damper structures; inserting and pressing a micromechanical wafer into the master mold so that micromechanical structures in the wafer are aligned in relation to the damper structures; filling the master mold with UV-curing LSR and subsequent UV irradiation; and mold release and removal of the connected structure of the micromechanical wafer with attached dampers. A method for producing a singulated MEMS chip comprising a UV-cured damper is also described.
COMPUTATION DEVICES AND ARTIFICIAL NEURONS BASED ON NANOELECTROMECHANICAL SYSTEMS
Techniques, systems, and devices are described for implementing for implementing computation devices and artificial neurons based on nanoelectromechanical (NEMS) systems. In one aspect, a nanoelectromechanical system (NEMS) based computing element includes: a substrate; two electrodes configured as a first beam structure and a second beam structure positioned in close proximity with each other without contact, wherein the first beam structure is fixed to the substrate and the second beam structure is attached to the substrate while being free to bend under electrostatic force. The first beam structure is kept at a constant voltage while the other voltage varies based on an input signal applied to the NEMS based computing element.
Semiconductor Device
A semiconductor device has a deformable membrane, e.g., for the measurement of at least one of an acceleration, a vibration, or a pressure. The membrane has a supporting connection with a support structure which includes at least one elastic supporting connection. Also disclosed are a sensor device including the semiconductor device along with methods for manufacturing the semiconductor device and the sensor device.
PIEZOELECTRIC MEMS DEVICE WITH CANTILEVER STRUCTURES
A MEMS device includes a first layer, a second layer connected to the first layer, a first mooring portion, a second mooring portion, and a MEMS device body. The MEMS device body is connected to the first mooring portion and the second mooring portion. The MEMS device body further includes a first cantilever attached to the first mooring portion, a second cantilever attached to the second mooring portion, and a spring. The spring is in operable communication with the first cantilever and the second cantilever.
MEMS VIBRATOR AND MEMS OSCILLATOR
The present disclosure relates to a MEMS vibrator or the like that has excellent chemical resistance and an excellent mechanical strength and that is easily thinned. The present disclosure is a MEMS vibrator comprising: a vibrating film including a graphite film; and a silicon member supporting the vibrating film, the graphite film having a thickness of 50 nm or more and less than 20 m, and the graphite film having a Young's modulus along a graphite film plane direction of 700 GPa or more.
Computation devices and artificial neurons based on nanoelectromechanical systems
Techniques, systems, and devices are described for implementing for implementing computation devices and artificial neurons based on nanoelectromechanical (NEMS) systems. In one aspect, a nanoelectromechanical system (NEMS) based computing element includes: a substrate; two electrodes configured as a first beam structure and a second beam structure positioned in close proximity with each other without contact, wherein the first beam structure is fixed to the substrate and the second beam structure is attached to the substrate while being free to bend under electrostatic force. The first beam structure is kept at a constant voltage while the other voltage varies based on an input signal applied to the NEMS based computing element.