MEMS design: Sensors and Actuators

Over the past few decades the increased level of public awareness concerning healthcare, physical activities, safety and environmental sensing has created an emerging need for smart sensor technologies and monitoring devices able to sense, classify, and provide feedbacks to users’ health status and physical activities, as well as to evaluate environmental and safety conditions in a pervasive, accurate and reliable fashion. Monitoring and precisely quantifying users’ physical activity with inertial measurement unit-based devices, for instance, has also proven to be important in health management of patients affected by chronic diseases, e.g., Parkinson’s disease, many of which are becoming highly prevalent in Italy and in the Western world. This review paper will focus on MEMS sensor technologies developed in Italy in the last three years describing research achievements for healthcare and physical activity, safety and environmental sensing, in addition to smart systems integration. Innovative and smart integrated solutions for sensing devices, pursued and implemented in Italian research centres, will be highlighted, together with specific applications of such technologies. Finally, the paper will depict the future perspective of sensor technologies and corresponding exploitation opportunities, again with a specific focus on Italy.

Advancements in neurotechnologies for electrophysiology, neurochemical sensing, neuromodulation, and optogenetics are revolutionizing scientific understanding of the brain while enabling treatments and preventative measures for a variety of neurological disorders. The grand challenge in neural interface engineering is to seamlessly integrate the interface between neurobiology and engineered technology to record from and modulate neu-rons over chronic timescales. However, the biological inflammatory response to implants, neural degeneration, and long-term material stability diminishes the quality of the interface overtime. Recent advances in functional materials are aimed at engineering solutions for chronic neural interfaces, yet, the development and deployment of neural interfaces designed from novel materials have introduced new challenges that have been largely unad-dressed. Many engineering efforts that solely focus on optimizing individual probe design parameters, such as softness or flexibility, downplay critical multi dimensional interactions between different physical properties of the device that contribute to overall performance and biocompatibility. Moreover, the use of these new materials present substantial new difficulties that must be addressed before regulatory approval for use in human patients is achievable. In this review, the interdependence of different electrode components is highlighted to demonstrate the current material-based challenges facing the field of neural interface engineering.

Modern Remotely Piloted Aircraft Systems (RPAS) employ a variety of sensors and multi-sensor data fusion techniques to provide advanced functionalities and trusted autonomy in a wide range of mission-essential and safety-critical tasks. In particular, Navigation and Guidance Systems (NGS) for small RPAS require a typical combination of lightweight, compact and inexpensive sensors to satisfy the Required Navigation Performance (RNP) in all flight phases. In this paper, the synergies attainable by the combination of Global Navigation Satellite System (GNSS), Micro-Electromechanical System based Inertial Measurement Unit (MEMS-IMU) and Vision-Based Navigation (VBN) sensors are explored. In case of VBN, an appearance-based navigation technique is adopted and feature extraction/optical flow methods are employed to estimate the navigation parameters during precision approach and landing phases. A key novelty of the proposed approach is the employment of Aircraft Dynamics Models (ADM) augmentation to compensate for the shortcomings of VBN and MEMS-IMU sensors in high-dynamics attitude determination tasks. To obtain the best estimates of Position, Velocity and Attitude (PVA), different sensor combinations are analysed and dynamic Boolean Decision Logics (BDL) are implemented for data selection before the centralised data fusion is accomplished. Various alternatives for data fusion are investigated including a traditional Extended Kalman Filter (EKF) and a more advanced Unscented Kalman Filter (UKF). A novel hybrid controller employing fuzzy logic and Proportional-Integral-Derivative (PID) techniques is implemented to provide effective stabilization and control of pitch and roll angles. After introducing the key mathematical models describing the three NGS architectures: EKF based VBN-IMU-GNSS (VIG) and VBN-IMU-GNSS-ADM (VIGA) and UKF based Enhanced VIGA (EVIGA), the system performances are compared in a small RPAS integration scheme (i.e., AEROSONDE RPAS platform) exploring a representative cross-section of the aircraft operational flight envelope. A dedicated ADM processor (i.e., a local pre-filter) is adopted in the EVIGA architecture to account for the RPAS maneuvering envelope in different flight phases (assisted by a maneuver identification algorithm), in order to extend the ADM validity time across all segments of the RPAS trajectory. Simulation results show that the VIG, VIGA and EVIGA systems are compliant with ICAO requirements for precision approach down to CAT-II. In all other flight phases, the VIGA system shows improvement in PVA data output with respect to the VIG system. The EVIGA system shows the best performance in terms of attitude data accuracy and a significant extension of the ADM validity time is achieved in this configuration.

This documents describes a modular hardware platform for inertial measuring unit and its integration into Matlab Simulink. Its purpose is to give students a way to work with real device in an environment which they are familiar with. They can train various methods of signal processing and filtering and they can get familiar with used MEMS gyroscopes and accelerometers.

Cellulose nanocrystal/graphene oxide composite was reported as a humidity sensor in this study. The composite film was fabricated using simple blending the materials followed by oven drying. The composite film offers a unique advantages of cellulose combined with functionality of GO. It was capitalized to design renewable, flexible and cheap humidity sensor. Performance of the composite film as a humidity sensor was evaluated on the basis of relative capacitance change at different humidity level. Synthesized composite film was characterized using scanning electron microscope, Fourier transform infrared spectroscope, and X-ray diffraction. Environmental effect such as temperature was taken into account on the sensor performance. The sensing mechanism is explained on the basis of presence of hydrophilic functional groups in the composite. The linear and fast response of the developed sensor is advantageous.

Here we report on the mask-less deposition of Au–SnO 2 nanocomposites with a silicon-on-insulator (SOI) complementary metal oxide semiconductor (CMOS) micro electro mechanical system (MEMS) platform through the use of dip pen nanolithography (DPN) to create a low-cost ethanol sensor. MEMS technology is used in order to achieve low power consumption, by the employment of a membrane structure formed using deep reactive ion etching technique. The device consists of an embedded tungsten micro-heater with gold interdigitated electrodes on top of the SOI membrane. The tungsten micro-heater is used to raise the membrane temperature up to its operating temperature and the electrodes are used to measure the resistance of the nanocomposite sensing layer. The CMOS MEMS devices have high electro-thermal efficiency, with 8.2 °C temperature increase per mW power of consumption. The sensing material (Au– SnO 2 nanocomposite) was synthesised starting from SnO nanoplates, then Au nanoparticles were attached chemically to the surface of SnO nanoplates, finally the mixture was heated at 700 °C in an oven in air for 4 h. This composite material was sonicated for 2 h in terpineol to make a viscous homogeneous slurry and then 'written' directly across the electrode area using the DPN technique without any mask. The devices were characterised by exposure to ethanol vapour in humid air in the concentration range of 100–1000 ppm. The sensitivity varied from 1.2 to 0.27 ppm −1 for 100–1000 ppm of ethanol at 10% relative humid air. Selectivity measurements showed that the sensors were selective towards ethanol when they were exposed to acetone and toluene. S Online supplementary data available from stacks.iop.org/NANO/27/125502/mmedia

Now a day, health and patient monitoring is very tedious job to do. The monitoring personnel have to watch continuously. They have to keep monitoring the patients, who are admitted in Intensive Care Unit (ICU). These patients are in serious illness conditions and can't be said what happens in next instance to them and today increasing the number of patients in the ICU due to many increasing fatal diseases. These diseases are threatening the population all over the world. Doctors need more conscious about the patient health status. The health monitoring system proposed here gives doctor continuously updated health information of patient using various sensors used to monitor health of patient. It allows doctors to monitor patient over the long distance and also to consult others. Li-Fi technology is used here in to update information quickly and it can be viewed at monitor of the doctor. Simultaneously it also records the data of patient in the CPU. This data can be viewed through the internet for reference while consulting the patient.