Analysis of Complex Solid-Gas Flow under the Influence of Gravity through Inclined Channel and Comparison with Real-Time Dual-Sensor System

Gas-solid flow is used in the chemical industry, food industry, pharmaceuticals, vehicles, and power generation. The calculation of flow has aroused great interest in contemporary industry. In recent decades, researchers have been seeking to build an effective system to monitor and calculate gas-solid flow. Attempts have been extended from computational modeling to the creation of flow pattern visualization methods and mass flow (MFR) quantification. MFR is usually studied by volume flow concentration (VFC) and velocity distribution of solid particles. A non-invasive device is used for testing MFR, in which electronic and mechanical sensors are used to balance the shortcomings related to each other. This study investigates the simulation of flow patterns to demonstrate the behavior of solid particles as they pass through the channel. The particles are allowed to slide longitudinally in the insulated tending channel. This slippage is due to the influence of natural gravity. Electronic sensor components are used to measure the velocity distribution and concentration of volumetric flow. The load cell is used as an auxiliary sensor for measuring MFR. In addition, ANSYS fluent is used to analyze streaming queries. The experimental results are related to evaluating the accuracy and relative error of the data collected from various sensors under different conditions. However, the simulation results can help explain the movement of the gas-solid mixture and can understand the cause of pipeline blockage during the slow movement of solid particles.

Calibration of piezoresistive shape-memory alloy strain sensors

Continuous strain measurement on fibre-reinforced structures demands mechanical sensors with superior fatigue resistance. Shape-memory alloy wires are predestined for strain sensors utilising their strong piezo-resistance. Calibration of these sensors is necessary in order to extract mechanical data. Therefore, four-point bending of glass-fibre reinforced plastic specimens with applied strain sensors and an optical reference measuring system is used to calibrate and compare shape-memory alloy sensors and standard strain gauges. The gauge factor and its standard deviation is successfully measured by this calibration method. Shape-memory alloy sensors show strain-dependent gauge factor whilst standard strain gauges show a constant strain sensitivity, both with a narrow stochastic distribution. Shape-memory alloy mechanical sensors are reliable to determine strain of fibre-reinforced structures. This offers the possibility to use them in structural health monitoring applications of such structures. Consequently, the four-point bending calibration using glass-fibre reinforced specimens represents a suitable possibility for calibration of strain sensors exposed to higher strain amplitudes.

Textile-Based Mechanical Sensors: A Review

Innovations related to textiles-based sensors have drawn great interest due to their outstanding merits of flexibility, comfort, low cost, and wearability. Textile-based sensors are often tied to certain parts of the human body to collect mechanical, physical, and chemical stimuli to identify and record human health and exercise. Until now, much research and review work has been carried out to summarize and promote the development of textile-based sensors. As a feature, we focus on textile-based mechanical sensors (TMSs), especially on their advantages and the way they achieve performance optimizations in this review. We first adopt a novel approach to introduce different kinds of TMSs by combining sensing mechanisms, textile structure, and novel fabricating strategies for implementing TMSs and focusing on critical performance criteria such as sensitivity, response range, response time, and stability. Next, we summarize their great advantages over other flexible sensors, and their potential applications in health monitoring, motion recognition, and human-machine interaction. Finally, we present the challenges and prospects to provide meaningful guidelines and directions for future research. The TMSs play an important role in promoting the development of the emerging Internet of Things, which can make health monitoring and everyday objects connect more smartly, conveniently, and comfortably efficiently in a wearable way in the coming years.

Primary calibration of mechanical sensors with digital output for dynamic applications

This article tackles the challenge of the dynamic calibration of modern sensors with integrated data sampling and purely digital output for the measurement of mechanical quantities like acceleration, angular velocity, force, pressure, or torque. Based on the established calibration methods using sine excitation, it describes an extension of the established methods and devices that yields primary calibration results for the magnitude and phase of the complex transfer function. The system is demonstrated with a focus on primary accelerometer calibrations but can easily be transferred to the other mechanical quantities. Furthermore, it is shown that the method can be used to investigate the quality and characteristics of the timing for the internal sampling of such digital output sensors. Thus, it is able to gain crucial information for any subsequent phase-related measurements with such sensors.

Integrating magnetic capabilities to intracellular chips for cell trapping

Current microtechnologies have shown plenty of room inside a living cell for silicon chips. Microchips as barcodes, biochemical sensors, mechanical sensors and even electrical devices have been internalized into living cells without interfering their cell viability. However, these technologies lack from the ability to trap and preconcentrate cells in a specific region, which are prerequisites for cell separation, purification and posterior studies with enhanced sensitivity. Magnetic manipulation of microobjects, which allows a non-contacting method, has become an attractive and promising technique at small scales. Here, we show intracellular Ni-based chips with magnetic capabilities to allow cell enrichment. As a proof of concept of the potential to integrate multiple functionalities on a single device of this technique, we combine coding and magnetic manipulation capabilities in a single device. Devices were found to be internalized by HeLa cells without interfering in their viability. We demonstrated the tagging of a subpopulation of cells and their subsequent magnetic trapping with internalized barcodes subjected to a force up to 2.57 pN (for magnet-cells distance of 4.9 mm). The work opens the venue for future intracellular chips that integrate multiple functionalities with the magnetic manipulation of cells.

Phononic Crystal Sensors: A New Class of Resonant Sensors—Chances and Challenges for the Determination of Liquid Properties

Resonant mechanical sensors are often considered as mass balance, which responds to an analyte adsorbed on or absorbed in a thin sensitive (and selective) layer deposited on the surface of the resonant device. In a more general sense, the sensor measures properties at the interface of the mechanical resonator to the medium under inspection. A phononic crystal (PnC) sensor employs mechanical resonance as well; however, the working principle is fundamentally different. The liquid medium under inspection becomes an integral part of the PnC sensor. The liquid-filled compartment acts as a mechanical resonator. Therefore, the sensor probes the entire liquid volume within this compartment. In both sensor concepts, the primary sensor value is a resonant frequency. To become an attractive new sensing concept, specifically as a bio and chemical sensor, the PnC sensor must reach an extraordinary sensitivity. We pay attention to the liquid viscosity, which is an important factor limiting sensitivity. The main part of our analysis has been performed on 1D PnC sensors, since they underlie the same material-related acoustic dissipation mechanisms as 2D and 3D PnC sensors. We show that an optimal relation of frequency shift to bandwidth and amplitude of resonance is the key to an enhanced sensitivity of the sensor-to-liquid analyte properties. We finally address additional challenges of 2D and 3D PnC sensor design concept. We conclude that the sensor should seek for a frequency resolution close to 10−6 the probing frequency, or a resolution with speed of sound approaching 1 mm s−1, taking water-based analytes as an example.

From head micro-motions towards CSF dynamics and non-invasive intracranial pressure monitoring

Continuous monitoring of the intracranial pressure (ICP) is essential in neurocritical care. There are a variety of ICP monitoring systems currently available, with the intraventricular fluid filled catheter transducer currently representing the “gold standard”. As the placement of catheters is associated with the attendant risk of infection, hematoma formation, and seizures, there is a need for a reliable, non-invasive alternative. In the present study we suggest a unique theoretical framework based on differential geometry invariants of cranial micro-motions with the potential for continuous non-invasive ICP monitoring in conservative traumatic brain injury (TBI) treatment. As a proof of this concept, we have developed a pillow with embedded mechanical sensors and collected an extensive dataset (> 550 h on 24 TBI coma patients) of cranial micro-motions and the reference intraparenchymal ICP. From the multidimensional pulsatile curve we calculated the first Cartan curvature and constructed a ”fingerprint” image (Cartan map) associated with the cerebrospinal fluid (CSF) dynamics. The Cartan map features maxima bands corresponding to a pressure wave reflection corresponding to a detectable skull tremble. We give evidence for a statistically significant and patient-independent correlation between skull micro-motions and ICP time derivative. Our unique differential geometry-based method yields a broader and global perspective on intracranial CSF dynamics compared to rather local catheter-based measurement and has the potential for wider applications.

Toward Enhanced Humidity Stability of Triboelectric Mechanical Sensors via Atomic Layer Deposition

Humid conditions can disrupt the triboelectric signal generation and reduce the accuracy of triboelectric mechanical sensors. This study demonstrates a novel design approach using atomic layer deposition (ALD) to enhance the humidity resistance of triboelectric mechanical sensors. Titanium oxide (TiOx) was deposited on polytetrafluoroethylene (PTFE) film as a moisture passivation layer. To determine the effective ALD process cycle, the TiOx layer was deposited with 100 to 2000 process cycles. The triboelectric behavior and surface chemical bonding states were analyzed before and after moisture exposure. The ALD-TiOx-deposited PTFE showed three times greater humidity stability than pristine PTFE film. Based on the characterization of TiOx on PTFE film, the passivation mechanism was proposed, and it was related to the role of the oxygen-deficient sites in the TiOx layer. This study could provide a novel way to design stable triboelectric mechanical sensors in highly humid environments.