Mechanical Sensors Research Articles

Engineering a Graphene Quantum Dot‐Enhanced Surface Plasmon Resonance Sensor for Ultra‐Sensitive Detection of Hg2⁺ Ions

AbstractThe contamination of soil and water by heavy metals poses a significant environmental and public health concern worldwide. To address this issue, a novel graphene quantum dot (GQD)‐based surface plasmon resonance (SPR) sensor is developed for the detection of mercury ions (Hg2+), a notorious heavy metal pollutant. The thiol and amine‐functionalized GQDs (S,N‐GQDs), synthesized via pyrolysis of citric acid and L‐cysteine, are directly immobilized onto the SPR chip surface without prior pretreatment, demonstrating their potential as efficient sensing materials. The SPR sensor exhibits high sensitivity and selectivity toward Hg2+ ions, as confirmed by kinetic binding analysis and isotherm modeling. The Langmuir isotherm model, which accurately describes the interactions between Hg2+ and S,N‐GQDs, provides insights into the sensor's mechanism of action. Furthermore, the sensor demonstrates robustness and reusability, with recoveries ranging from 98% to 104% over multiple cycles of analysis. Given the presence of contaminants in tap water, the developed sensor system holds significant importance for environmental monitoring and public health protection, offering a rapid, accurate, and cost‐effective solution for detecting Hg2+ ions in such samples. Overall, this study represents a significant advancement in the field of heavy metal detection, with potential implications for addressing environmental pollution and ensuring water quality.

Bending response performance in nitrogen-doped reduced graphene oxide-PEDOT:PSS: The impact of nitrogen flow rate on the nitrogen doping configurations

Mechanical bending sensors play a pivotal role in various applications, from wearable devices to healthcare monitoring systems. The integration of nitrogen-doped reduced graphene oxide (NrGO) materials has emerged as a versatile approach, offering a promising avenue for enhancing the performances of these sensors. Various nitrogen doping configurations within the materials matrix have been found to profoundly influence the sensor's bending response. In this work, we identified that pyrrolic-N doping configurations were more dominant at lower nitrogen flow rates of 10 and 20 sccm, with the percentages of 52.9 and 48.7 %, respectively. These configurations exhibited a stable pattern of resistance changes in response to bending, particularly when subjected to bending angles of 55° and 65°. Despite some inconsistencies in bending response at lower bending angles, the sensors demonstrated heightened sensitivity, registering at 0.34 kPa. In contrast, sensors predominantly characterized by pyridinic-N configurations at 40 sccm maintained a consistent level of sensitivity across different bending angles, demonstrating remarkable stability and structural robustness, even after enduring 10,000 cycles. These findings indicated that pyridinic-N configurations play a critical role in enhancing sensor performance, ensuring reliable measurements across various mechanical deformations.

Design and development of machine vision robotic arm for vegetable crops in hydroponics

Modern agricultural machinery such as harvesting robotic arms are necessary to optimize the semi-automated agricultural processes to meet the ever-growing food needs of the population of the world. Production of low cost and highly efficient robotic arms are needed to meet the needs of the small-scale growers of underdeveloped countries. In this regard, mechanical design, sensor placement, and object identification are essential to optimize the performance of agricultural robots. This research is conducted to design a fully automated robotic arm for fruit picking in hydroponics system and research farm using machine vision to help the smallholders. For this purpose, a robotic arm with 1.3 m in height is designed using aluminum (18-gauge) and mild steel (MS-16) as fabrication material for the mechanical structure. The prototype design is tested for stress estimation at various payloads using SolidWorks simulations. The proposed robotic arm is based on a four degrees of freedom (4-DoF) design with the gripper having an opening range of 5.5 to 12 cm depending upon the task to handle various objects. The robotic arm is installed on an expandable vertical mobile platform that enables an expanded operational workspace with lower energy consumption. The total weight of the robotic arm is 60 kgs housing a payload capacity ranging between 8 and 10 kgs in accordance with industry-standard load-bearing specifications. The inverse kinematic algorithm using DH-table is computed with an accuracy of up to 95 % and target height of gripper is cross checked by mounting the ultrasonic sensor at the base of robotic arm. The YOLOv8 algorithm is used for object detection using the depth sense camera having angle range of 0.3 m to 3 m with the precision of up to 96 %. The time needed for recognition of fruits and pitching was about 15 s, with a success rate of up to 90 %. This research produces a low-cost and efficient solution for stallholders by developing a fully automated robotic arm for fruit picking. It optimizes agricultural productivity through improved mechanical design, sensor accuracy, and object detection which reduces labor costs by increasing efficiency of semi-automated farming systems. Further research is required to optimize the overall weight of the system and automation of the movement of robotic arm system between the consecutive rows to build a fully autonomous fruit picking operation in hydroponics.

Microscale chemiresistive hydrogen sensors: Current status and recent developments

Hydrogen is known for its efficient combustion, abundant natural availability, and environmentally friendly characteristics. It is recognized as a promising energy source for the future and is already utilized in various industries, including petrochemicals, electronics, food processing, aerospace, and new energy vehicles. However, challenges arise in the storage and use of hydrogen owing to its tendency to leak, its potential for explosion within a specific concentration range of 4%–75%, and itslow ignition energy requirements. Consequently, there is a demand for hydrogen sensors capable of quickly and accurately detecting low levels of hydrogen leaks. Microelectromechanical systems-based chemiresistive hydrogen sensors offer advantages such as low cost, compact size, low energy consumption, and superior sensing performance, making them a major focus of recent research. This article provides a comprehensive overview and comparison of the sensing principles of various hydrogen sensors, including chemiresistive sensors, electrochemical sensors, thermocatalytic sensors, acoustic sensors, and mechanical sensors. Micro-chemiresistive hydrogen sensors exhibit high sensitivity, low cost, and ease of integration, making them highly promising for practical applications. In response to the challenges encountered in practical applications of chemiresistive hydrogen sensors, such as high operating temperatures and high power consumption, this review explores emerging trends in chemiresistive hydrogen sensor technology from the perspectives of novel materials and activation methods. Finally, it discusses the applications and potential further developments of chemiresistive hydrogen sensors.

Designing High-Sensitivity Mechanochromic Luminescent Materials Through Friction-Induced Crystallization Strategy.

Despite recent significant breakthroughs in novel mechanochromic luminescent (ML) materials, developing a high-sensitivity ML material is still challengeable. Herein, a "friction-induced crystallization" strategy is proposed to realize highly sensitive transformations of luminescent signal, through an integration of polymeric chains and an aggregation-sensitive luminescent core, which act as mechanical sensors and fluochromic actuators, respectively. The coupling of these two components enables the material to crystallize in response to shear friction, thereby exhibiting blue-shift fluorescence due to a more restricted relaxation pathway. This study underscores a high-sensitivity ML material based on the precise regulation of molecular-scale motions, and also expands the scope and potential of ML materials toward user-friendly, interactive wearable devices.

Vibrational squeezing via spin inversion pulses

Magnetic resonance force microscopy (MRFM) describes a range of approaches to detect nuclear spins with mechanical sensors. MRFM has the potential to enable magnetic resonance imaging with near-atomic spatial resolution, opening up exciting possibilities in solid state and biological research. In many cases, the spin-mechanics coupling in MRFM is engineered with the help of periodic radio frequency pulses. In this paper, we report that such pulses can result in unwanted parametric amplification of the mechanical vibrations, causing misinterpretation of the measured signal. We show how the parametric effect can be canceled by auxiliary radio frequency pulses or by appropriate post-correction after careful calibration. Future MRFM measurements may even make use of the parametric amplification to reduce the impact of amplifier noise.

Recent Patents on Piano Tuning System

Piano tuning plays a very important role in piano playing and music education. Regular tuning can prolong the service life of the piano, improve the sound saturation, and make the sound more concentrated and full. Automated mechanical equipment, controllers, sensors, and other equipment are used to automatically tune pianos to solve the problems of human error, overtone resonance interference, string breakage, etc., occurring in manual tuning. To solve the above problems, based on the synthesis of related patents and research results, the patents on automatic tuning system and methods for modulating piano are introduced in detail. An automatic tuning system can replace manual tuning, simplify the complex process of tuning, and consider the problem of overtone interference caused by the vibration of the strings to improve the accuracy of tuning; it can, at the same time, perform real-time monitoring of the string tension, protecting the strings from breaking due to tuning. The automatic tuning system has a simple structure and a high degree of automation; its method is highly accurate and it can replace professional tuning technicians, being highly innovative and widely practical.

Exploring the interplay between zinc‐induced protein dyshomeostasis and mitochondrial dysfunction using viscosity‐sensitive sensor

AbstractMitochondria are crucial sites for protein quality control within cells. When mitochondrial stress is triggered by protein misfolding, it can accelerate abnormal protein aggregation, potentially inducing various diseases. This study developed a cascade‐responsive sensor, named AggHX, to monitor the microenvironment of protein aggregation induced by zinc (II) ions and the accompanying mitochondrial dysfunction. The AggHX consists of two key components: (1) A Zn2+ recognition group for triggering a fluorescent enhance response, and (2) a near‐infrared BODIPY scaffold that detects viscosity changes in cell aggregation via HaloTag. This sensor's mechanism of action is elucidated through photochemical and biochemical characterizations. To further investigate the relationship between protein aggregation and mitochondrial homeostasis, we employ fluorescence lifetime imaging microscopy to assess viscosity changes in protein aggregates under intracellular Zn2+ stress. This research provides insights into the dynamic behavior and spatial distribution of protein aggregates and mitochondria, contributing to a deeper understanding of their physiological roles in cellular processes and potential implications in disease pathology.

Tumor cell-intrinsic Piezo2 drives radioresistance by impairing CD8+ T cell stemness maintenance.

Changes in mechanosensitive ion channels following radiation have seldom been linked to therapeutic sensitivity or specific factors involved in antitumor immunity. Here, in this study, we found that the mechanical force sensor, Piezo2, was significantly upregulated in tumor cells after radiation, and Piezo2 knockout in tumor cells enhanced tumor growth suppression by radiotherapy. Specifically, loss of Piezo2 in tumor cells induced their IL-15 expression via unleashing JAK2/STAT1/IRF-1 axis after radiation. This increase in IL-15 activates IL-15Rα on tumor-infiltrating CD8+ T cells, thereby leading to their augmented effector and stem cell-like properties, along with reduced terminal exhausted feature. Importantly, Piezo2 expression was negatively correlated with CD8 infiltration, as well as with radiosensitivity of patients with rectum adenocarcinoma receiving radiotherapy treatment. Together, our findings reveal that tumor cell-intrinsic Piezo2 induces radioresistance by dampening the IRF-1/IL-15 axis, thus leading to impaired CD8+ T cell-dependent antitumor responses, providing insights into the further development of combination strategies to treat radioresistant cancers.

Methodology for assessing health risk behaviours among undergraduates in Sri Lanka: a literature review

It is imperative to learn more about the distinctive Health-Risk-Behaviours (HRB) that are culturally acceptable in the lower-resource settings. Therefore, the objective of this review is to identify tools measuring HRBs among undergraduates in Sri Lankan context. A literature review was conducted both manually and electronically through Google Scholar and Hinari and PubMed databases. Self-administered Questionnaires were used in National Surveys and individual studies. Youth-Risk Behaviour-Surveillance-System was the most commonly used comprehensive HRB assessment tool. The National College Health Risk Behaviour Survey, National College Health Assessment were other widely used instruments. There are few validated tools and multiple short scales or items combined like Health-Promotion-Lifestyle[1]Profile, Health-Behaviour-Questionnaire or Inventory, DOSPERT scale, Adolescent-Health-Attitude and Behaviour[1]Survey, Healthy-Lifestyle-Scale, Health-Behaviour-Scale and Health-Behaviour-Checklist. Objective methods for assessing high-risk behaviors (HRBs) include measures of personality and aggression, which have been used to critically quantify violence and accidental injury, as well as biochemical tests for alcohol, nicotine, and other drug use, mechanical or computer sensors, and biological tests such as urinary cultures for sexual risk behaviours. These tools had focused only on specific aspects of HRBs among undergraduates in Western countries and were not comprehensive assessments of HRBs of undergraduates in lower-resource settings. It was evident that there has been a deficit of choices for the adaptation of an HRB tool for undergraduates in lower-resource-settings and a new tool to be developed for Sri Lankan context.

Impact of pneumatic tube transportation on the aggregation of monoclonal antibodies in clinical practice

Postproduction handling and in-hospital transportation of antibody drugs cause mechanical stress, including interfacial and shear stress, that can induce antibody unfolding and aggregation. The handling practices differ significantly between hospitals and the impact on protein stability is unknown. For example, the mechanical stress caused by transport via pneumatic tube systems (PTS) on therapeutic antibody aggregation is a potential safety and quality gap.The aim of this study was to investigate whether mechanical stress and PTS transportation in a hospital cause aggregation of five commonly used antibody drugs diluted in infusion bags.Orthogonal analytical methods showed that the handling and PTS transportation in this hospital did not cause aggregation of the investigated mAbs. The absence of aggregation could be explained by the reduction of interfacial stress due to headspace removal from the infusion bags and a mechanical sensor indicated that there was also only a moderate amount of mechanical stress caused by transportation with this particular PTS.Although this case study focuses on five antibody drugs and the practices in one hospital, the work demonstrates how to evaluate whether other handling and transportation practices cause significant mechanical stress that could compromise the quality and safety of antibody drugs.

Sowing Depth Monitoring System for High-Speed Precision Planters Based on Multi-Sensor Data Fusion

High-speed precision planters are subject to high-speed (12~16 km/h) operation due to terrain undulation caused by mechanical vibration and sensor measurement errors caused by the sowing depth monitoring system’s accuracy reduction problems. Thus, this study investigates multi-sensor data fusion technology based on the sowing depth monitoring systems of high-speed precision planters. Firstly, a sowing depth monitoring model comprising laser, ultrasonic, and angle sensors as the multi-sensor monitoring unit is established. Secondly, these three single sensors are filtered using the Kalman filter. Finally, a multi-sensor data fusion algorithm for optimising four key parameters in the extended Kalman filter (EKF) using an improved sparrow search algorithm (ISSA) is proposed. Subsequently, the filtered data from the three single sensors are integrated to address the issues of mechanical vibration interference and sensor measurement errors. In order to ascertain the superiority of the ISSA-EKF, the ISSA-EKF and SSA-EKF are simulated, and their values are compared with the original monitoring value of the sensor and the filtered sowing depth value. The simulation test demonstrates that the ISSA-EKF-based sowing depth monitoring algorithm for high-speed precision planters, with a mean absolute error (MAE) of 0.083 cm, root mean square error (RMSE) of 0.103 cm, and correlation coefficient (R) of 0.979 achieves high-precision monitoring. This is evidenced by a significant improvement in accuracy when compared with the original monitoring value of the sensor, the filtered value, and the SSA-EKF. The results of a field test demonstrate that the ISSA-EKF-based sowing depth monitoring system for high-speed precision planters enhances the precision and reliability of the monitoring system when compared with the three single-sensor monitoring values. The average MAE and RMSE are reduced by 0.071 cm and 0.075 cm, respectively, while the average R is improved by 0.036. This study offers a theoretical foundation for the advancement of sowing depth monitoring systems for high-speed precision planters.

Design and fabrication of an accelerometer structure using glass fiber reinforced epoxy resin for seismic P-wave early warning

Earthquake early warning represents a vital and effective strategy for mitigating earthquake-related losses. Among the existing sensors for earthquake early warning, MEMS accelerometers involve complex manufacturing process, leading to high research and development costs and long cycles. Traditional mechanical sensors are bulky, costly, hence not suitable for large-scale, high-density monitoring network. In this study, a low-cost accelerometer using glass fiber reinforced epoxy resin is proposed for longitudinal seismic waves (P-waves) early warning. Both theorical and finite element analysis are carried out to define and optimize the initial structure of the accelerometer. A pre-deformation structure is implemented into the spring suspension system to offset the influence of the sensor’s gravity, so that a self-balanced state in the direction of gravity is achieved. The simulation results show that the accelerator can achieve an eigenfrequency of 12.67 Hz, a Q-value of 49.2, and mechanical thermal noise of 1.72×10-9g/Hz. Based on the simulation results, the accelerometer’s structure is processed using a computer numerical control (CNC) milling machine, and tested by collecting the voltage signals when the accelerometer’s structure undergoes an impact in the direction of the gravity. The measured eigenfrequency is around 10 Hz, and the signal attenuation rate closely aligns with the simulation results. The accelerometer structure has dimensions within 6 cm and a relatively simplified manufacturing process, making it a cost-effective solution for the development of large-scale, high-density earthquake early warning systems.

Active flux based adaptive and non-adaptive observer for sensorless interior permanent magnet synchronous machine drive

The use of the interior permanent magnet synchronous machine (IPMSM) drive has profoundly increased in a large number of applications due to numerous advantages. Owing to the disadvantages of mechanical sensors, sensorless control techniques are employed to enhance the performance of the IPMSM drive by removing the effect of noise and gain drift due to the sensor, increasing reliability, cost saving, and reducing overall size. This article presents the comparative analysis between the adaptive observer and non-adaptive extended electromotive force (EEMF) observer based on the active flux concept in a stationary reference frame (α–β). Moreover, the effect of slot harmonics and non-sinusoidal distribution of rotor flux is present in the three-phase IPMSM, this problem is considered as the control system disturbances in this article. Due to the non-sinusoidal distribution of flux and slot harmonics, the observer structure in the rotating reference frame (d–q) fails to estimate at the low-speed operation range. Comparative analysis between adaptive and non-adaptive observer structures is provided for a wide speed range. The effectiveness of the observer structures is examined using the classical field-oriented control scheme. In the end, simulation and experimental results are demonstrated to validate the performance of the sensorless control scheme using the adaptive and non-adaptive observer structures for the three-phase IPMSM drive setup.

Sensor‐Embedded Muscle for Closed‐Loop Controllable Actuation in Proprioceptive Biohybrid Robots

Biohybrid robots are soft robots that exploit unique characteristics of biological cells and tissues for motion generation. Skeletal muscle tissue‐based bioactuators respond to externally applied stimuli, such as electrical fields. However, current bioactuation systems rely on open‐loop control strategies that lack knowledge of the actuator's state. The regulation of output force and position of biohybrid robots requires self‐sensing control systems that combine bioactuators with sensors and control paradigms. Herein, a soft, fiber‐shaped mechanical sensor based on a piezoresistive composite is proposed that efficiently integrates with engineered skeletal muscle tissue and senses its contracting states in a cell culture environment in the presence of applied electrical fields. After testing the sensor's insulation and biocompatibility, its sensitivity for typical strains (<1%) is characterized, and its ability is proven to detect motions from contractile skeletal muscle tissue constructs. Finally, it is shown that the sensor response can feed an autonomous control system, thus demonstrating the first proprioceptive biohybrid robot that senses and responds to its contraction state. In addition to inspiring implantable systems, biomedical models, and other bioelectronic devices, the proposed technology will confer biohybrids with decisional autonomy, thus driving the paradigm shift between bioactuators and intelligent biohybrid robots.

Study On the Mechanical Device, Control System, and Sensor of Biaxial Actuated Artificial Anal Sphincter Actuator for Treating Fecal Incontinence

Abstract Artificial anal sphincter, Actuator, Mechanical device, Control system, Pressure sensor

SENSORLESS SPEED ESTIMATION OF THREE PHASE INDUCTION MOTORS BASED ON DYNAMIC MODEL

In speed control systems of induction motor electrical drives, real-time speed monitoring is necessary. Speed monitoring can be done using the direct method, which uses a mechanical sensor mounted on the motor shaft, or the indirect method, which is based on estimation, mainly from the dynamic model of the motor. Speed estimation based on the dynamic model of the motor in orthogonal coordinates is the most widespread method in sensorless speed control systems of three-phase squirrel cage induction motor electrical drives, especially those of high accuracy. This paper presents the open-loop speed estimator used for speed estimation in three-phase induction motors. The proposed speed estimators are based on the orthogonal coordinate’s dynamic model of an induction motor in a stator reference frame. This technical solution is simple and has a low cost. The currents and voltages of the two motor phases are the input variables of the estimator, while the output variable is the induction motor speed. The speed estimator model is built using LabVIEW software. The dynamics and accuracy of the estimator proposed in this paper have been tested experimentally. The speed measured by the industrial incremental encoder is compared with that of a speed estimator modeled in LabVIEW software. The obtained experimental results show a good match between the measured and estimated speeds under the step torque load changes of the induction motor.

Moisture-wicking Janus-structure electronic knitted fabric for multimodal wearable mechanical sensing

Multimodal mechanical sensors that can recognize bending direction and exhibit excellent wearable performance are crucial for the fields of physical exercise and healthcare. This study fabricated a knitted multimodal sensor with porous and wetting gradients using hydrophobic core-spun yarns and hydrophilic CNT/WPU conductive yarns in plain stitch and partial tuck stitch. The electronic fabric demonstrated reliable strain sensing unaffected by compression disturbances and displayed a selective response to directional bending. The sensor exhibits a 50% sensing range with a GFmax of −4.41 during strain deformation detection. In terms of bending detection, one side achieves a 10% sensing range (−51.68°) with a GFmax of −6.89, while the other side achieves a 20% sensing range (73.72°) with a GFmax of 8.64. Encouragingly, deep learning incorporated with the sensor achieves an impressive recognition rate of 98.16% for mixed signals with different force levels. Furthermore, it possesses excellent wearable properties such as breathability, moisture permeability, perspiration remove, quick-drying and washability, suitable for applications like activity monitoring, medical rehabilitation evaluation, and gesture recognition. This work presents a promising pathway for the advancement of next-generation multifunctional electronic textiles.

Wearable photonic crystal double network hydrogel sensor based on structural color analysis

Abstract This paper introduces a high-toughness photonic crystal (PhCs) dual-network hydrogel sensor designed for mechanical sensing, which enables quantitative analysis of structural color using the HSB color space. The hydrogel achieves a maximum tensile strain of 250% under a tensile stress of 3.5 MPa, thanks to its dual-network structure comprising a covalently cross-linked polyacrylamide (PAM) network and an ionically cross-linked sodium alginate (SA) network. At an 80% tensile strain, the PAM-SA photonic crystal hydrogel displays a blue shift in the bandgap wavelength of over 130 nm and demonstrates a sensitivity of 1.69 nm/%. The analysis of the force-induced color change in the PAM-SA photonic crystal hydrogel utilized both RGB and HSB color spaces. In the HSB color space, the hue component (H) exhibited a strong linear correlation with strain (R2>0.95), indicating the feasibility of quantitative structural color analysis using HSB. As a wearable sensor, the PAM-SA photonic crystal hydrogel precisely detects human motion via bandgap displacement (R2=0.989) and structural color change (R2=0.978). The PAM-SA PhCs hydrogel, featuring easily accessible color information and high sensitivity, has broad potential applications in wearable devices and mechanical sensors.

Development of an Underwater Adaptive Penetration System for In Situ Monitoring of Marine Engineering Geology.

In recent years, offshore wind farms have frequently encountered engineering geological disasters such as seabed liquefaction and scouring. Consequently, in situ monitoring has become essential for the safe siting, construction, and operation of these installations. Current technologies are hampered by limitations in single-parameter monitoring and insufficient probe-penetration depth, hindering comprehensive multi-parameter dynamic monitoring of seabed sediments. To address these challenges, we propose a foldable multi-sensor probe and establish an underwater adaptive continuous penetration system capable of concurrently measuring seabed elevation changes and sediment pore water pressure profiles. The reliability of the equipment design is confirmed through static analysis of the frame structure and sealed cabin. Furthermore, laboratory tests validate the stability and accuracy of the electrical and mechanical sensor measurements. Preliminary tests conducted in a harbor environment demonstrate the system's effectiveness.