Detected Research Articles

Flexible Strain Sensors with Ultra-High Sensitivity and Wide Range Enabled by Crack-Modulated Electrical Pathways

Abstract This study presents a breakthrough in flexible strain sensor technology with the development of an ultra-high sensitivity and wide-range sensor, addressing the critical challenge of reconciling sensitivity with measurement range. Inspired by the structure of bamboo slips, we introduce a novel approach that utilises liquid metal to modulate the electrical pathways within a cracked platinum fabric electrode. The resulting sensor demonstrates a gauge factor greater than 108 and a strain measurement capability exceeding 100%. The integration of patterned liquid metal enables customisable tuning of the sensor’s response, while the porous fabric structure ensures superior comfort and air permeability for the wearer. Our design not only optimises the sensor’s performance but also enhances the electrical stability that is essential for practical applications. Through systematic investigation, we reveal the intrinsic mechanisms governing the sensor’s response, offering valuable insights for the design of wearable strain sensors. The sensor’s exceptional performance across a spectrum of applications, from micro-strain to large-strain detection, highlights its potential for a wide range of real-world uses, demonstrating a significant advancement in the field of flexible electronics.

Pt/MOF-5 film-coated optical micro-nano fibre hydrogen sensor with humidity and temperature compensation functions

Pt/MOF-5 film-coated optical micro-nano fibre hydrogen sensor with humidity and temperature compensation functions

Design optimisation of rare earth metal doped polymer optical planar waveguide sensor for microplastics detection in water

Design optimisation of rare earth metal doped polymer optical planar waveguide sensor for microplastics detection in water

Enhanced Quantum Efficiency via Co‐Substitution in Red‐Emitting Phosphor Sr2[MgAl5N7] : Eu2+ for Advanced Spectroscopic Applications Including Laser Displays with Ultra‐High Luminescence Saturation Threshold

AbstractIn order to obtain novel and more efficient red light‐emitting materials, a series of Sr2[Mg1−xLixAl5−xSixN7] : 0.01Eu2+ (SMAN‐xLS, 0≤x≤0.5) red phosphors were devised and successfully synthesized via the high temperature solid state reaction and the effects of the co‐substitution of [Mg−Al]5+ by [Li−Si]5+ on structural and luminescence properties is investigated in detail. A series of powder XRD data and Rietveld refinement indicate that [Li−Si]5+ co‐substitution can successfully enter the Sr2[MgAl5N7] : 0.01Eu2+ (SMAN) lattice. With the entry of [Li−Si]5+ into the lattice, the substitution of Al3+ by Si4+ leads to the weakening of the nephelauxetic effect of the 5d level of Eu2+, which shifts the emission peak from 657 nm to 647 nm and reduces the excitation in the green region, i.e., lowers the absorption of green light. When the amount of [Li−Si]5+ co‐substitution is x=0.1, the luminescence intensity and thermal stability of the sample are enhanced, in which the external quantum efficiency (EQE), reflecting the luminescence intensity, is elevated by 49.6 %. The increase in lattice rigidity gives rise to higher luminescence intensity, and the introduced trap levels for the compensation of luminescence enhances the thermal stability. Under blue laser excitation, the SMAN‐0.1LS can achieve an ultra‐high luminescence saturation threshold of 52.22 W/mm2, which is remarkably superior to other existing red phosphors, a breakthrough performance that has enormous potential for application in high‐power laser display light sources. Cathodoluminescence (CL) characterization and measurements attest to the favorable CL properties of SMAN‐0.1LS. By measuring the pressure‐dependent luminescence of SMAN‐0.1LS, the emission peak can be shifted from 650 nm to 702 nm with the increase of pressure, and the sensitivity dλ/dP is 5.07 nm/GPa, which is indicative of the potential application of this system as an optical pressure sensor.

Application of UAVs and Remote Sensing Technologies for Atmospheric CO2 Capturing: A Study Application of UAVs and Remote Sensing in CO2 Reductions

Human activities are a significant contributor to climate change, with rising levels of CO₂ in the atmosphere. Several carbon capture and sequestration (CCS) methods have been developed to address this issue. Uncrewed Aerial Vehicles (UAVs) and remote sensing technologies are emerging as significant improvements to the efficiency and effectiveness of atmospheric carbon capture initiatives. This research examines using UAVs and remote sensing technologies to monitor, quantify, and manage atmospheric CO₂ levels. Furthermore, the study explores the implications of integrating robotic-drone technology, emphasizing their ability to contribute to a sustainable future. These technologies, incorporating modern data collection and analysis methodologies, provide promising answers for climate change mitigation and long-term environmental sustainability.

Implementation Of IoT-Based Optical Sensors For Real-Time Monitoring In Palm Oil Processing

Optical sensors are widely used in various industrial sectors, including petrochemical and medical industries, with applications ranging from oxygen level measurement, concentration of substances in a liquid, object detection, and more. Optical sensors can be used to detect the water content in oil, such as palm oil or other oils. In an industrial process, especially in the palm oil industry, the water content in oil must meet a maximum standard of 4.5%. Optical sensors can measure water content using various methods, such as Total Internal Reflection (TIR) or Mid-Infrared (MIR), and can be monitored in real-time using IoT-based applications. The utilization of sensitive optical technology takes advantage of changes in the refractive index caused by variations in water content in palm oil. The method employed involves the development of an optical sensor based on the Mid-Infrared principle, which measures the amount of light absorbed by water and the light reaching the sensor for comparison. The results of water content measurements in palm oil that have been conducted can only be implemented for water content measurements of 0-5% in palm oil, with a sensor response that is less than linear above 5% water content. By correcting the non-linearity error of the sensor, the data is reduced to produce measurement results that are closer to the actual water content in palm oil, which will be displayed on local monitoring and real-time or continuous monitoring through IoT using smartphones and PCs wirelessly via IoT-based applications

Light-Emitting Coordination Polymers: Stimuli-Responsive Gels, PMMA-Based Composite Films, and UV-Shielding.

Lanthanide-based light-emitting coordination polymers (CPs) and CP gels (CPGs) have significance for applications in optical systems, image processing/multiplexing, and optical sensors. In this study, we report two new luminescent CPs (EuL-CP (1) and TbL-CP (2)) and CPGs (EuL-gel (5) and TbL-gel (6)) using lanthanide(III) ions (Ln(III) = Eu(III) and Tb(III)) and 4-(4-carboxyphenyl)-2,2:6,2-terpyridine ligand (L) capable of forming stable thermoreversible gels. Probable structures of EuL-CP (1) and TbL-CP (2) and the formations of EuL-gel (5) and TbL-gel (6) are proposed based on adequate computational studies. The CPGs are stimuli-responsive and could be utilized as invisible security inks for encryption. Further, poly(methyl methacrylate) (PMMA) polymer doped with respective CPs (0.75 wt %) is found to be suitable for forming composite films with UV-shielding properties.

Membrane lipid nanodomains modulate HCN pacemaker channels in nociceptor DRG neurons.

Cell membranes consist of heterogeneous lipid nanodomains that influence key cellular processes. Using FRET-based fluorescent assays and fluorescence lifetime imaging microscopy (FLIM), we find that the dimension of cholesterol-enriched ordered membrane domains (OMD) varies considerably, depending on specific cell types. Particularly, nociceptor dorsal root ganglion (DRG) neurons exhibit large OMDs. Disruption of OMDs potentiated action potential firing in nociceptor DRG neurons and facilitated the opening of native hyperpolarization-activated cyclic nucleotide-gated (HCN) pacemaker channels. This increased neuronal firing is partially due to an increased open probability and altered gating kinetics of HCN channels. The gating effect on HCN channels is likely due to a direct modulation of their voltage sensors by OMDs. In animal models of neuropathic pain, we observe reduced OMD size and a loss of HCN channel localization within OMDs. Additionally, cholesterol supplementation inhibited HCN channels and reduced neuronal hyperexcitability in pain models. These findings suggest that disturbances in lipid nanodomains play a critical role in regulating HCN channels within nociceptor DRG neurons, influencing pain modulation.

Acoustofluidic tweezers via ring resonance.

Ring resonator (RR) devices are closed-loop waveguides where waves circulate only at the resonant frequencies. They have been used in sensor technology and optical tweezers, but controlling micron-scale particles with optical RR tweezers is challenging due to insufficient force, short working distances, and photodamage. To overcome these obstacles, an acoustofluidic RR-based tweezing method is developed to manipulate micro-sized particles that can enhance particle trapping through the resonance interaction of acoustic waves with high Q factor (>3000), more than 20 times greater than traditional acoustic transducers. Particles can be precisely manipulated within the RR by adjusting the signal phase, with trapping amplified by enlarging the connected waveguide. Rapid particle mixing is achieved when particles are placed between the waveguide and RR. The signal path is strengthened by strategically positioning the RR in a two-dimensional plane. Acoustofluidic RR tweezers have immense potential for advancing applications in biosensing, mechanobiology, lab-on-a-chip, and cell-cell communication research.

Medium-High-Frequency and High Sensitivity Fiber Optic Acceleration Sensor Based on F–P Interference

Medium-High-Frequency and High Sensitivity Fiber Optic Acceleration Sensor Based on F–P Interference

Oxygen optodes on oceanographic moorings: recommendations for deployment and in situ calibration

Increasing interest in the deployment of optical oxygen sensors, or optodes, on oceanographic moorings reflects the value of dissolved oxygen (DO) measurements in studies of physical and biogeochemical processes. Optodes are well-suited for moored applications but require careful, multi-step calibrations in the field to ensure data accuracy. Without a standardized set of protocols, this can be an obstacle for science teams lacking expertise in optode data processing and calibration. Here, we provide a set of recommendations for the deployment and in situ calibration of data from moored optodes, developed from our experience working with a set of 60 optodes deployed as part of the Gases in the Overturning and Horizontal circulation of the Subpolar North Atlantic Program (GOHSNAP). In particular, we detail the correction of drift in moored optodes, which occurs in two forms: (i) an irreversible, time-dependent drift that occurs during both optode storage and deployment and (ii) a reversible and pressure-and-time-dependent drift that is detectable in some optodes deployed at depths greater than 1,000 m. The latter is virtually unidentified in the literature yet appears to cause a low-bias in measured DO on the order of 1 to 3 µmol kg−1 per 1,000 m of depth, appearing as an exponential decay over the first days to months of deployment. Comparisons of our calibrated DO time series against serendipitous mid-deployment conductivity-temperature-depth (CTD)-DO profiles, as well as biogeochemical (BGC)-ARGO float profiles, suggest the protocols described here yield an accuracy in optode-DO of ∼1%, or approximately 2.5 to 3 µmol kg−1. We intend this paper to serve as both documentation of the current best practices in the deployment of moored optodes as well as a guide for science teams seeking to collect high-quality moored oxygen data, regardless of expertise.

A LiNbO3 Optical Sensor for Measurement of the 2-D Intensive Electric Field Vectors

A LiNbO₃ Optical Sensor for Measurement of the 2-D Intensive Electric Field Vectors

Stress Detection System using Machine Learning and Sensors

This project presents a novel stress detection system that leverages machine learning and sensor technology to monitor and assess stress levels in real-time. As stress has become a widespread concern affecting mental health, our system integrates wearable sensors—such as heart rate monitors, galvanic skin response sensors, and accelerometers—to capture physiological data indicative of stress. The project involves several key components: data collection and preprocessing, feature extraction, and the development of machine learning models capable of accurately classifying stress levels based on the sensor data. Various algorithms, including Support Vector Machines and Neural Networks, will be employed and optimized for performance. The system is designed to provide real-time feedback to users, offering insights and personalized recommendations for stress management based on detected levels. A user-friendly interface will enable individuals to track their stress over time, fostering greater awareness and encouraging proactive coping strategies

Mobile Phone Intelligent Recognition of Human Activity Based on Deep Neural Network

Abstract. Because of the rapid development of smartphone sensor technology and the continuous progress of machine learning algorithms, it has become possible to use smartphones for human activity recognition. Sensors such as accelerometers, gyroscopes, and magnetometers built into smartphones are able to collect human motion data in different activities, which provides a rich data source for activity recognition through mobile phones. In this paper, we change the activation function of the hidden layer of the neural network to observe the effect of this variable on the mobile phone to recognize human activities. Taking Rectified Linear Unit (ReLU)function and Sigmoid function as examples, it is found that the neural network using the ReLU function shows higher accuracy (0. 9518 and 0. 9332) and lower loss value in the early stage and middle to late stage of training. In addition, This paper finds that training for 100 epochs takes significantly less time than the model with the Sigmoid activation function (47. 041 seconds vs 179. 022 seconds). The neural network system built by the relu function has faster operation speed and better performance. This study shows that different hidden layer functions have great influence on the quality of the same neural network, and selecting the best hidden layer function will be an important point for the success of the study.

Precise Genotyping Via Surface‐Enhanced Raman Spectroscopy‐Based Optical Sensing Chip for Guiding Targeted Therapy in Lung Cancer

AbstractThe emergence of “precision medicine” marks a notable shift in cancer treatment, moving from a tumor type–oriented approach to a more targeted, gene‐oriented approach. Detecting low‐abundance mutant genes in blood is challenging but crucial for personalized treatment plans. Herein, a novel platform combining catalytic hairpin self‐assembly (CHA)‐mediated self‐calibrating surface‐enhanced Raman spectroscopy (SERS) with a high‐throughput Raman system (CCSPS) was designed. This platform enables ultrasensitive and rapid genotype analysis of gene mutations. The development of CCSPS specifically targets EGFR mutations, which serve as crucial therapeutic targets for precision therapy in lung cancer. This system shows excellent sensitivity and selectivity, capable of detecting multiple EGFR mutations (Del‐19, L858R, and T790M) with a detection limit as low as attomolar levels. Additionally, precise genotyping analysis was successfully conducted on 42 clinical samples using the CCSPS, yielding results consistent with those obtained through next‐generation sequencing. These results underscore the efficacy of the CCSPS in noninvasively identifying circulating tumor DNA (ctDNA) mutations, facilitating immediate therapeutic decision making at the bedside. In summary, the CCSPS is a fast, accurate, versatile, and compact testing system capable of precisely screening individuals who stand to benefit from targeted therapy, thus promoting personalized and precise healthcare.

Re-wilding the Night: Understanding How Darkness Is Valued Through the Nighttime Light Ecology of Bonn Botanical Gardens

Rewilding the Night is an interdisciplinary research project that aims to reimagine the urban night by capturing and communicating the qualities and rhythms of both artificial and natural light at night. Through a collaborative and experimental approach, the project seeks to make the urban night legible by employing sensor technologies and data visualization techniques, thus fostering a deeper engagement with and appreciation for urban darkness. The project has three aims—first, to capture and analyse environmental light data in Bonn Botanical Gardens, Germany to create an accessible understanding of the variations in natural and artificial nighttime light. Second, to use this groundwork to inform subsequent workshops to capture public perceptions and values regarding darkness; and third, to develop lighting prototypes that respond to light data and the insights gained through the workshops. Central to the project is the re-evaluation of urban darkness by questioning and expanding the normative frameworks surrounding urban lighting. The project underscores the importance of interdisciplinary research and design in addressing complex urban challenges, offering a model for future research aimed at creating more livable, sustainable, and inclusive urban night environments for both humans and non-humans.

Shape measurement by using multicore optical fiber sensor with asymmetric dual cores

Abstract Shape measurement by using multicore optical fiber sensor has attracted more attention in many fields due to the good consistency of the fiber cores. Three symmetrically arranged cores in multicore fiber are usually used for reconstructing shape by calculating the bending vectors, which will not be achieved when one of the cores is damaged or occupied in actual application. A shape measurement method using multicore optical fiber sensor with asymmetric dual cores is proposed in this paper. Based on analyzing the principle of shape reconstruction and the geometric relationship of asymmetric dual cores in multicore fiber sensor, the bending vector is decomposed. The mathematical expressions for bending curvature and orientation of asymmetric dual cores are derived. The two dimensional (2D) and three dimensional (3D) shape reconstruction results both in finite element modelling simulation and shape measurement experiment based on optical frequency domain reflectometry have shown that the proposed method using multicore fiber sensor with asymmetric dual cores is able to achieve shape measurement, and its performance is comparable and even equivalent to the traditional method by using three symmetrically arranged cores. In the experiment, the maximum relative errors of 2D and 3D reconstructed shapes are 2.653% and 5.139%, respectively. The proposed method, which only needs asymmetric dual cores in the multicore optical fiber sensor for shape reconstruction, will be conducive to solve the limitation of multicore optical fiber sensors in shape measurement applications.

Wavelength Locking and Calibration of Fiber-Optic Ultrasonic Sensors Using Single-Sideband-Modulated Laser

Implementation of edge-filter detection for interrogating optical interferometric ultrasonic sensors is often hindered by the lack of cost-effective laser sources with agile wavelength tunability and good noise performance. The detected signal can also be affected by optical power variations and locking-point drift, negatively affecting the sensor accuracy. Here, we report the use of laser single-sideband generation with a dual-parallel Mach–Zehnder interferometer (DP-MZI) for laser wavelength tuning and locking in edge-filter detection of fiber-optic ultrasonic sensors. We also demonstrate real-time in situ calibration of the sensor response to ultrasound-induced wavelength shift tuning. The DP-MZI is employed to generate a known wavelength modulation of the laser, whose response is used to gauge the sensor response to the ultrasound-induced wavelength shifts in real time and in situ. Experiments were performed on a fiber-optic ultrasonic sensor based on a high-finesse Fabry–Perot interferometer formed by two fiber Bragg gratings. The results demonstrated the effectiveness of the laser locking against laser wavelength drift and temperature variations and the effectiveness of the calibration method against optical power variations and locking-point drift. These techniques can enhance the operational robustness and increase the measurement accuracy of optical ultrasonic sensors.

Research on Voltage Self-Calibration Sensing Technology Based on Measurement Circuit Topology Changes

In capacitance-coupled voltage-sensing technology, the degree of coupling capacitance is affected by the sensing area, relative position deviation, and other factors, and thus the measurement coefficient is often difficult to determine accurately and presents greater implementation difficulties in actual deployment. This paper proposes a dynamic reconfiguration based on the measurement circuit topology of the voltage sensor adaptive calibration method in order to measure voltage sensor gain in the process of automatic measuring. Firstly, the basic principle of voltage measurement is introduced, and the self-calibration method is proposed, considering the influence of the sensing area and the relative position error on the change in the coupling capacitance. On this basis, the influence of calibration accuracy on sensor structure parameters is analyzed using network sensitivity analysis, and the parameter selection principle is given, according to which the selection criterion of parameter optimization is formulated to complete the sensor design. By analyzing the coupling effect of the three-phase measurement, the installation method of the sensing structure is proposed. An experimental platform is built to test the accuracy of the voltage measurement of the sensor under laboratory conditions. The experimental results show that the maximum relative error of the voltage measurement amplitude is 2.24%. In order to verify the feasibility of the sensor technology designed, the measurement models that integrate communication, acquisition, and processing are installed on both ends of the circuit breaker wire, and the voltage waveform generated during the circuit breaker closing process is recorded in real time. The experimental results show that the sensor technology can accurately record the voltage waveform of the signal to be measured, and the feasibility of its application in switchgear equipment signal measurement is preliminarily verified by the results.

Evaluation of BLE Star Network for Wireless Wearable Prosthesis/Orthosis Controller

Concomitant improvements in wireless communication and sensor technologies have increased capabilities of wearable biosensors. These improvements have not transferred to wireless prosthesis/orthosis controllers, in part due to strict latency and power consumption requirements. We used a Bluetooth Low Energy 5.3 (BLE) network to study the influence of the connection interval (10–100 ms) and event length (2500–7500 μs), ranges appropriate for real-time myoelectric prosthesis/orthosis control on the maximum network size, power consumption, and latency. The number of connections increased from 4 to 12 as the connection interval increased from 10 to 50 ms (event length of 2500 μs). For connection intervals ≤50 ms, the number of connections reduced by ≥50% with the increasing event length. At a connection interval of 100 ms, little change was observed in the number of connections vs. event length. Across event lengths, increasing the connection interval from 10 to 100 ms decreased the average power consumed by approximately 16%. Latency measurements showed that an average of one connection interval (maximum of just over two) elapses between the application of the signal at the peripheral node ADC input and its detection on the central node. Overall, reducing the latency using shorter connection intervals reduces the maximum number of connections and increases power consumption.