Temperature adaptation patterns in Chinese cattle revealed by TRPM2 gene mutation analysis

Cattle are sensitive to temperature fluctuations but adapt well to inclement weather conditions. When environmental temperatures exceed specific thresholds, heat stress becomes a critical concern for cattle. The TRPM2 gene, which resides on cattle chromosome 1 encodes a TRP channel protein, holding a unique capacity to sense temperature changes and facilitate rapid response to avoid heat stress. Here, we utilized the Bovine Genome Variation Database (BGVD) (http://animal.omics.pro/code/index.php/BosVar), and identified a missense mutation site, c.805A > G: p. Met269Val (rs527146862), within the TRPM2 gene. To elucidate the functional assessment of this mutation in temperature adaptation attributes of Chinese cattle, we genotyped 407 samples from 20 distinct breeds representing diverse climatic zones across China. The association analysis incorporates three temperature parameters and revealed compelling insights in terms of allele frequency. Interestingly, the prevalence of the wild-type allele A was notably higher among northern cattle breeds and this trend diminished gradually as observed in southern cattle populations. Conversely, the mutant-type allele G demonstrated a contrasting trend. Moreover, southern cattle exhibited markedly higher frequencies of GG and GA genotypes (P < 0.01). The presence of heterozygous and homozygous mutations appears to confer an enhanced capacity for adaptation to elevated temperatures. These results provide unequivocal correlation evidence between TRPM2 genotypes (AA, GA, GG) and environmental temperature parameters and comprehend the genetic mechanisms governing temperature adaptation in cattle. This provides valuable insights for strategic breed selection across diverse climatic regions, thereby aiding livestock production amid evolving climate challenges.

Design and Characterization of Surface Acoustic Wave-Based Wireless and Passive Temperature Sensing System

The surface acoustic wave (SAW) temperature sensor has received significant attention due to its wirelessly powered, battery-free, and chipless capabilities. This paper proposes a wireless sensing system comprising a one-port SAW resonator, helix antenna, and transceiver circuit. The SAW resonator used in this system is based on aluminum nitride (AlN) thin film, which exhibits high velocity and excellent piezoelectric properties. Simulations and experiments were conducted to investigate the performance of the designed SAW resonator. A helix antenna was also designed using finite element simulation to facilitate signal transmission between the SAW temperature sensor and the transceiver. An impedance-matching network was introduced between the helix antenna and the SAW resonator to optimize signal transmission. When the wireless SAW temperature sensor was placed within a certain distance of the mother antenna, the reflection peak of the SAW resonator was observed in the spectrum of the return signal. The frequency of the echo signal increased almost linearly as the temperature increased during the temperature tests. The fitted temperature coefficient of frequency (TCF) was -31.34 ppm/°C, indicating that the wireless temperature sensing system has high-temperature sensitivity.

Optimizing Greenhouse Design with Miniature Models and IoT (Internet of Things) Technology-A Real-Time Monitoring Approach

The market for smart greenhouses has been valued at USD 1.77 billion in 2022 and is expected to grow to 3.39 billion by 2030. In order to make this more efficient, with the help of Internet of Things (IoT) technology, it is desired to eliminate the problem of traditional agriculture, which has poor monitoring and accuracy control of the parameters of a culture. Climate control decisions in a greenhouse are made based on parameter monitoring systems, which can be remotely controlled. Instead of this adjustment of the measured parameters, it would be preferable from the point of view of energy consumption that they should be calculated at optimal values from the design phase of the greenhouse. For this reason, it would be better to perform an energy simulation of the greenhouse first. For the study carried out in this work, a small greenhouse (mini-greenhouse) was built. It was equipped with an IoT sensor system, which measured indoor climate parameters and could send data to the cloud for future recording and processing. A simplified mathematical model of the heat balance was established, and the measured internal parameters of the mini-greenhouse were compared with those obtained from the simulation. After validating the mathematical model of the mini-greenhouse, this paper aimed to find the optimal position for placing a normal-sized greenhouse. For this, several possible locations and orientations of the greenhouse were compared by running the mathematical model, with which the most unfavorable positions could be eliminated. Then, some considerably cheaper "mini-greenhouses" were made and placed in the locations with the desired orientations. Using sensor systems and technologies similar to those presented in this work, the parameters from all mini-greenhouses can be monitored in real time. This real-time monitoring allows for the simultaneous analysis of all greenhouses, without the disadvantages of data collection directly in the field, with all data being recorded in the cloud and other IoT-specific advantages being made use of. In the end, we can choose the optimal solution for the location of a real-size greenhouse.

Ionic Covalent Organic Framework as a Dual Functional Sensor for Temperature and Humidity

Visual sensing of humidity and temperature by solids plays an important role in the everyday life and in industrial processes. Due to their hydrophobic nature, most covalent organic framework (COF) sensors often exhibit poor optical response when exposed to moisture. To overcome this challenge, the optical response is set out to improve, to moisture by incorporating H-bonding ionic functionalities into the COF network. A highly sensitive COF, consisting of guanidinium and diformylpyridine linkers (TG-DFP), capable of detecting changes in temperature and moisture content is fabricated. The hydrophilic nature of the framework enables enhanced water uptake, allowing the trapped water molecules to form a large number of hydrogen bonds. Despite the presence of non-emissive building blocks, the H-bonds restrict internal bond rotation within the COF, leading to reversible fluorescence and solid-state optical hydrochromism in response to relative humidity and temperature.

Bubble Sensors for Temperature Measurements through a Colorimetric Approach

This paper introduces an innovative sensor utilizing bubbles coated with thermochromic paint, aiming to facilitate temperature measurements in challenging-to-reach locations without the requirement of an external power source. The research conducted is innovative in terms of both methodology and application. The characterization of the thermochromic properties of paints was, in fact, performed using spectroradiometric measurements by selecting a temperature range useful for applications in various fields including preventive conservation. The study encompasses two main objectives: (1) analyzing the color characteristics of thermochromic paint and plastic resin that forms the bubbles, and (2) assessing a temperature sensor comprising a thermochromic paint-coated bubble subjected to temperature variations. The thermochromic paint exhibits reversible color modifications in response to temperature changes, making it an ideal candidate for applications of this nature. The color characterization phase involves measurements using a spectroradiometer to compare the spectral reflectance factor (SRF%) of the colored plastic resin spread on canvas with that of the inflated bubbles. The sensor characterization entails evaluating color changes of the thermochromic paint on the bubble surface with varying temperatures. Experimental results indicate that the combination of a red (R) bubble and blue (B) thermochromic paint produces quantifiable color variations suitable for the proposed applications, whereas the alternative combination under examination, namely a blue bubble and red thermochromic paint, yields less accurate results. Considering that for both thermochromic paints the color change temperature is 35 °C, it is possible to see how, for B bubble with R thermochromic paint, the chromatic coordinates change value: C* = 3.14 ± 0.14 and h = 289.54 ± 11.58 at room temperature, while C* = 2.96 ± 0.12 and h = 304.20 ± 12.17 at 35 °C. The same is true for R bubble with B thermochromic paint where C* = 25.31 ± 1.01 and h* = 285.05 ± 11.40 at room temperature, while C* = 20.87 ± 0.85 and h = 288.37 ± 11.53 at 35 °C. The study demonstrates the potential of the approach and suggests further investigations into reproducibility and expanded color combinations. The results provide a promising basis for future improvements in temperature monitoring with thermochromic bubble sensors.

Materials and Device Designs for Wireless Monitoring of Temperature and Thermal Transport Properties of Wound Beds during Healing

Chronic wounds represent a major health risk for diabetic patients. Regeneration of such wounds requires regular medical treatments over periods that can extend for several months or more. Schemes for monitoring the healing process can provide important feedback to the patient and caregiver. Although qualitative indicators such as malodor or fever can provide some indirect information, quantitative measurements of the wound bed have the potential to yield important insights. The work presented here introduces materials and engineering designs for a wireless system that captures spatio-temporal temperature and thermal transport information across the wound continuously throughout the healing process. Systematic experimental and computational studies establish the materials aspects and basic capabilities of this technology. In vivo studies reveal that both the temperature and the changes in this quantity offer information on wound status, with indications of initial exothermic reactions and mechanisms of scar tissue formation. Bioresorbable materials serve as the foundations for versions of this device that create possibilities for monitoring on and within the wound site, in a way that bypasses the risks of physical removal.

Regeneration and Long-Term Stability of a Low-Power Eco-Friendly Temperature Sensor Based on a Hydrogel Nanocomposite

A water-processable and low-cost nanocomposite material, based on gelatin and graphene, has been used to fabricate an environmentally friendly temperature sensor. Demonstrating a temperature-dependent open-circuit voltage between 260 and 310 K, the sensor effectively detects subzero ice formation. Notably, it maintains a constant temperature sensitivity of approximately -19 mV/K over two years, showcasing long-term stability. Experimental evidence demonstrates the efficient regeneration of aged sensors by injecting a few drops of water at a temperature higher than the gelation point of the hydrogel nanocomposite. The real-time monitoring of the electrical characteristics during the hydration reveals the initiation of the regeneration process at the gelation point (~306 K), resulting in a more conductive nanocomposite. These findings, together with a fast response and low power consumption in the range of microwatts, underscore the potential of the eco-friendly sensor for diverse practical applications in temperature monitoring and environmental sensing. Furthermore, the successful regeneration process significantly enhances its sustainability and reusability, making a valuable contribution to environmentally conscious technologies.

Validation of Temperature Sensors to Monitor Thermoplastic Splint Wear in Hand Surgery Patients

BACKGROUND

The aim of this study was to validate the use of temperature sensors to accurately measure thermoplastic volar forearm splint wear in a healthy cohort of volunteers using 5- and 15-minute temperature measurement intervals.

METHODS

A prospective diagnostic study was performed to evaluate the diagnostic accuracy of temperature sensors in monitoring splint wear in 8 healthy volunteers between December 2022 and June 2023. Temperature sensors were molded into thermoplastic volar forearm splints. Volunteers who were familiar with the study aims were asked to keep an exact log of the time spent wearing the splint ("actual wear time"). Sensors recorded temperatures every 5 or 15 minutes, and separate algorithms were developed to determine the sensor-detected wear time compared with the actual wear time as the gold standard. The algorithms were then externally validated with the total population.

RESULTS

The 5-minute and 15-minute algorithms demonstrated excellent sensitivity (99.1% vs 96.6%), specificity (99.9% vs 99.9%), positive (99.4% vs 99.5%) and negative (99.9% vs 99.3%) predictive value, and diagnostic accuracy (99.8% vs 99.3%), respectively. The 5-minute algorithm recorded 99.5% of the total splint hours, whereas the 15-minute algorithm recorded 96.1%. There was no significant difference between the actual time per wear session (5.4 ± 2.7 hours) and the time estimated by the 5-minute algorithm (5.4 ± 2.6 hours; P = .40), but there was a significant difference for the 15-minute algorithm (5.2 ± 2.6 hours; P < .001).

CONCLUSION

Temperature sensors can be used to accurately monitor thermoplastic volar forearm splint wear.

LEVEL OF EVIDENCE

Diagnostic II.

Multifunction Applications of Filtering Dielectric Resonator Antenna Based on Liquid Crystal

In this paper, a new type of multifunctional device is realized by designing a filtering dielectric resonator antenna (FDRA) with liquid crystal (LC). The LC is encapsulated by glass plates and placed between the feeding network and the ground. Firstly, the resonance frequencies of the hairpin bandpass filter (|S11| is less than -10 dB) move simultaneously when the dielectric constant of LC changes at different temperatures. Then, the hairpin bandpass filter is extended to an FDRA, and the influence of the dielectric constant of LC on the antenna performance parameters is realized to the function of the temperature sensor. The results show that the dielectric constant of LC has an approximately linear relationship with the resonance frequencies of the FDRA. Simultaneously, the axial ratio, gain, antenna efficiency, E-field distribution, and pattern of the FDRA have changed significantly. Furthermore, the FDRA mainly works in the frequency range of 4.65~5.53 GHz, which has good antenna performance and filtering characteristics. Taking resonance frequency fx as an example, its sensitivity, maximum FOM, minimum detection limit, and minimum resolution are determined to be 95 GHz/RIU, 0.5, 0.1, and 9.68, respectively. The multifunctional device provides a novel approach and solution for the transmission of antenna signals and temperature measurements.

Purposive Design of Stretchable Composite Electrodes for Strain-Negative, Strain-Neutral, and Strain-Positive Ionic Sensors

Soft ionic sensors have emerged as a promising device form to accommodate various future electronic applications. One of the hurdles in ionic sensors is that the sensing signals by mechanical deformation and other stimuli are mixed up. Although the performance of the ionic sensors is highly dependent on the structure of electrodes, systematic investigation of purposive electrode design has been rarely explored. This study proposes a simple strategy for designing stretchable composite electrodes which make the ionic sensor strain-negative, strain-neutral, and strain-positive. This study reveals that such strain-responses can be obtained by adjusting the surface coverage of the electrically-effective conductive fillers. On the basis of the concept, deposition of a Au film on an elastomer composite and crack formation of the Au film are presented for the practical fabrication of a highly reproducible strain-neutral ionic sensor. A completely strain-independent temperature sensor is demonstrated by using the Au crack-based ionic sensor. In addition, this study demonstrates a two-terminal shear sensor capable of recognizing shear directions by combining the strain-positive and strain-negative electrodes.

Reaction Induced Conformational Change in Polyindole: Polyindole/PVA Film as Biomimetic Sensors of Temperature and Electrical Energetic Conditions

Conducting polymers can mimic the sensing characteristics of biological muscles through utilizing their unique electrochemical reactions. As these reactions occur, alterations in composition prompt changes in biomimetic properties, such as shifts in volume, brought about by the insertion of anions and solvent molecules, resulting in conformational movements. Similar to biological muscles, these electrochemical reaction senses the working variables affecting the reaction rate, through the same two connecting wires. The influence of working temperature and electrical energetic condition on the conformational movements of polyindole manifested as the cooperative actuation of the polymer chain is verified here using a polyindole-coated polyvinyl alcohol (PIN/PVA) film. Cyclic voltammetric (CV) studies revealed that the extent of reaction of polyindole varies linearly with temperature and scan rate. The logarithmic dependence of redox charge obtained from coulovoltammogram with inverse of temperature further proved the temperature sensing characteristics and the influence of temperature on the cooperative actuation of the film. The conformational relaxation increases as the temperature increases through hosting higher number of counter anions with the solvent molecule. The extension of the redox reaction was found to decrease as the scan rate increases. The double logarithmic relation between the consumed redox charge and the scan rate has proved that the electrical energetic condition can influence the conformational movement in a reversible manner. It is also verified from Chronopotentiometric (CP) studies that the consumed electrical energy during the reaction varies linearly with the change in temperature. The results suggest that the PIN/PVA film can act as a biomimetic macro molecular sensor of working temperature and electrical energetic condition as biological muscles do.

Eco-friendly alkali lignin-assisted water-based graphene oxide ink and its application as a resistive temperature sensor

Inkjet-printable ink formulated with graphene oxide (GO) offers several advantages, including aqueous dispersion, low cost, and environmentally friendly production. However, water-based GO ink encounters challenges such as high surface tension, low wetting properties, and reduced ink stability over prolonged storage time. Alkali lignin, a natural surfactant, is promising in improving GO ink's stability, wettability, and printing characteristics. The concentration of surfactant additives is a key factor in fine-tuning GO ink's stability and printing properties. The current study aims to explore the detailed effects of alkali lignin concentration and optimize the overall properties of graphene oxide (GO) ink for drop-on-demand thermal inkjet printing. A meander-shaped temperature sensor electrode was printed using the optimized GO ink to demonstrate its practical applicability for commercial purposes. The sensing properties are evaluated using a simple experimental setup across a range of temperatures. The findings demonstrate a significant increase in zeta potential by 25% and maximum absorption by 84.3%, indicating enhanced stability during prolonged storage with an optimized alkali lignin concentration compared to the pure GO dispersions. The temperature sensor exhibits a remarkable thermal coefficient of resistance of 1.21 within the temperature range of 25 °C-52 °C, indicative of excellent sensitivity, response, and recovery time. These results highlight the potential of alkali lignin as a natural surfactant for improving the performance and applicability of inkjet-printable GO inks in various technological applications.

An Antisweat Interference and Highly Sensitive Temperature Sensor Based on Poly(3,4-ethylenedioxythiophene)-Poly(styrenesulfonate) Fiber Coated with Polyurethane/Graphene for Real-Time Monitoring of Body Temperature

Body temperature is an important indicator of human health. The traditional mercury and medical electronic thermometers have a slow response (≥1 min) and can not be worn for long to achieve continuous temperature monitoring due to their rigidity. In this work, we prepared a skin-core structure polyurethane (PU)/graphene encapsulated poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) temperature-sensitive fiber in one step by combining wet spinning technology with impregnation technology. The composite fiber has high sensitivity (-1.72%/°C), super-resolution (0.1 °C), fast time response (17 s), antisweat interference, and high linearity (R2 = 0.98) in the temperature sensing range of 30-50 °C. The fiber is strong enough to be braided into the temperature-sensitive fabric with commercial cotton yarns. The fabric with good comfort and durability can be arranged in the armpit position of the cloth to realize real-time body temperature monitoring without interruption during daily activities. Through Bluetooth wireless transmission, body temperature can be monitored in real-time and displayed on mobile phones to the parents or guardians. Overall, the fiber-based temperature sensor will significantly improve the practical applications of wearable temperature sensors in intelligent medical treatment due to its sensing stability, comfort, and durability.

In-Bulk Temperature Profile Mapping Using Fiber Bragg Grating in Fluids

The capabilities of Fiber Bragg Grating (FBG) sensors to measure temperature variations in the bulk of liquid flows were considered. In the first step of our research project, reported in this paper, we investigated to what extent the use of thin glass fibers without encapsulation, which only minimally disturb a flow, can fulfill the requirements for robustness and measurement accuracy. Experimental tests were performed in a benchmark setup containing 24 FBG measuring positions, which were instrumented in parallel with thermocouples for validation. We suggest a special assembly procedure in which the fiber is placed under a defined tension to improve its stiffness and immobility for certain flow conditions. This approach uses a single FBG sensor as a reference that measures the strain effect in real time, allowing accurate relative temperature measurements to be made at the other FBG sensor points, taking into account an appropriate correction term. Absolute temperature readings can be obtained by installing another well-calibrated, strain-independent thermometer on the reference FBG. We demonstrated this method in two test cases: (i) a temperature gradient with stable density stratification in the liquid metal GaInSn and (ii) the heating of a water column using a local heat source. In these measurements, we succeeded in recording both spatial and temporal changes in the linear temperature distribution along the fiber. We present the corresponding results from the tests and, against this background, we discuss the capabilities and limitations of this measurement technique with respect to the detection of temperature fields in liquid flows.

Simultaneous Measurement of Microdisplacement and Temperature Based on Balloon-Shaped Structure

An optical fiber sensor for the simultaneous measurement of microdisplacement and temperature based on balloon-shaped single-mode fibers cascaded with a fiber Bragg grating with two core-offset joints is proposed. The interference between the core mode and cladding mode is caused by the stimulation of the cladding mode by the core-offset joints' structure. The cladding of the core has a distinct refractive index, which causes optical path differences and interference. The balloon-shaped structure realizes mode selection by bending. As the displacement increases, the radius of the balloon-shaped interferometer changes, resulting in a change in the interference fringes of the interferometer, while the Bragg wavelength of the fiber grating remains unchanged. Temperature changes will cause the interference fringes of the interferometer and the Bragg wavelength of the fiber grating to shift. The proposed optical fiber sensor allows for the simultaneous measurement of microdisplacement and temperature. The results of the experiment indicate that the sensitivity of the interferometer to microdisplacement is 0.306 nm/µm in the sensing range of 0 to 200 μm and that the temperature sensitivity is 0.165 nm/°C, respectively. The proposed curvature sensor has the advantages of a compact structure, extensive spectrum of dynamic measurement, high sensitivity, and simple preparation, and has a wide range of potential applications in the fields of structural safety monitoring, aviation industry, and resource exploration.

Preparation and Performance Analysis of 3D Thermoformed Fluidic Polymer Temperature Sensors for Aquatic and Terrestrial Applications

Employing a combination of Polyethylene terephthalate (PET) thermoforming and 3D-printed cylindrical patterns, we carefully engineer a linear resistive temperature sensor. This intricate process involves initial PET thermoforming, yielding a hollow cylindrical chamber. This chamber is then precisely infused with a composite fluid of graphite and water glue. Ensuring electrical connectivity, both ends are affixed with metal wires and securely sealed using a hot gun. This cost-effective, versatile sensor adeptly gauges temperature shifts by assessing composite fluid resistance alterations. Its PET outer surface grants immunity to water and solubility concerns, enabling application in aquatic and aerial settings without extra encapsulation. Rigorous testing reveals the sensor's linearity and stability within a 10 °C to 60 °C range, whether submerged or airborne. Beyond 65 °C, plastic deformation arises. To mitigate hysteresis, a 58 °C operational limit is recommended. Examining fluidic composite width and length effects, we ascertain a 12 Ω/°C sensitivity for these linear sensors, a hallmark of their precision. Impressive response and recovery times of 4 and 8 s, respectively, highlight their efficiency. These findings endorse thermoforming's potential for fabricating advanced temperature sensors. This cost-effective approach's adaptability underscores its viability for diverse applications.

Twisted Optical Micro/Nanofibers Enabled Detection of Subtle Temperature Variation

The detection of subtle temperature variation plays an important role in many applications, including proximity sensing in robotics, temperature measurements in microfluidics, and tumor monitoring in healthcare. Herein, a flexible miniaturized optical temperature sensor is fabricated by embedding twisted micro/nanofibers in a thin layer of polydimethylsiloxane. Enabled by the dramatic change of the coupling ratio under subtle temperature variation, the sensor exhibits an ultrahigh sensitivity (-30 nm/°C) and high resolution (0.0012 °C). As a proof-of-concept demonstration, a robotic arm equipped with our sensor can avoid undesired collisions by detecting the subtle temperature variation caused by the existence of a human. Moreover, benefiting from the miniaturized and engineerable sensing structure, real-time measurement of subtle temperature variation in microfluidic chips is realized. These initial results pave the way toward a category of optical sensing devices ranging from robotic skin to human-machine interfaces and implantable healthcare sensors.

A Design and Implementation Using an Innovative Deep-Learning Algorithm for Garbage Segregation

A startling shift in waste composition has been brought on by a dramatic change in lifestyle, the quick expansion of consumerism brought on by fierce competition among producers of consumer goods, and revolutionary advances in the packaging sector. The overflow or overspill of garbage from the bins causes poison to the soil, and the total obliteration of waste generated in the area or city is unknown. It is challenging to pinpoint with accuracy the specific sort of garbage waste; predictive image classification is lagging, and the existing approach takes longer to identify the specific garbage. To overcome this problem, image classification is carried out using a modified ResNeXt model. By adding a new block known as the "horizontal and vertical block," the proposed ResNeXt architecture expands on the ResNet architecture. Each parallel branch of the block has its own unique collection of convolutional layers. Before moving on to the next layer, these branches are concatenated together. The block's main goal is to expand the network's capacity without considerably raising the number of parameters. ResNeXt is able to capture a wider variety of features in the input image by using parallel branches with various filter sizes, which improves performance on image classification. Some extra dense and dropout layers have been added to the standard ResNeXt model to improve performance. In order to increase the effectiveness of the network connections and decrease the total size of the model, the model is pruned to make it smaller. The overall architecture is trained and tested using garbage images. The convolution neural Network is connected with a modified ResNeXt that is trained using images of metal, trash, and biodegradable, and ResNet 50 is trained using images of non-biodegradable, glass, and hazardous images in a parallel way. An input image is fed to the architecture, and the image classification is achieved simultaneously to identify the exact garbage within a short time with an accuracy of 98%. The achieved results of the suggested method are demonstrated to be superior to those of the deep learning models already in use when compared to a variety of existing deep learning models. The proposed model is implemented into the hardware by designing a three-component smart bin system. It has three separate bins; it collects biodegradable, non-biodegradable, and hazardous waste separately. The smart bin has an ultrasonic sensor to detect the level of the bin, a poisonous gas sensor, a stepper motor to open the lid of the bin, a solar panel for battery storage, a Raspberry Pi camera, and a Raspberry Pi board. The levels of the bin are maintained in a centralized system for future analysis processes. The architecture used in the proposed smart bin properly disposes of the mixed garbage waste in an eco-friendly manner and recovers as much wealth as possible. It also reduces manpower, saves time, ensures proper collection of garbage from the bins, and helps attain a clean environment. The model boosts performance to predict waste generation and classify it with an increased 98.9% accuracy, which is more than the existing system.

Intrinsically Stretchable Conductive Self-Healable Organogels for Strain, Pressure, Temperature, and Humidity Sensing

Intrinsically stretchable conductive self-healable organogels containing poly(lipoic acid), Al3+ ion, tannic acid, and reduced graphene oxide are produced in this report. These noncovalent networks interlocked through physical (hydrogen and coordination) bonds offered high stretchabilities and mechanical strengths as well as fast self-healing behaviors. The optimum organogel-based sensor showed outstanding pressure sensitivities (0.94 kPa-1 up to 10 and 1.07 kPa-1 for 10-50 kPa) and high strain responses (corresponding gauge factors of 1.1 and 0.4 for 0-50 and 50-100% stretching ratios). This organogel also revealed high stabilities at ambient atmosphere due to the presence of binary solvents of dimethyl sulfoxide and glycerol. Additionally, this stretchable thermistor displayed remarkable two-stage sensitivities of -2.6 and -0.4%/°C ranging over 0-30 and 30-80 °C, respectively. Besides, the signal variations of water droplet addition and removal with different temperatures were recorded by the organogel sensor to elucidate the practical applicabilities as a temperature sensor. Moreover, the organogel was utilized to demonstrate humidity sensing, where individual sensitivities of 0.89 and 0.55 were obtained in the respective relative humidity ranges of 10-30 and 40-90%. In the meanwhile, the sensor device illustrated distinct humidity signals during respiration monitoring of nose and mouth breathing detection. Accordingly, these quad-functional sensor applications in strain, pressure, temperature, and humidity detection enable this gel to act as a promising material for future multifunctional flexible electronics.

Photonic Integrated Circuit Based Temperature Sensor forOut-of-Autoclave Composite Parts Production Monitoring

The use of composite materials has seen widespread adoption in modern aerospace industry. This has been facilitated due to their favourable mechanical characteristics, namely, low weight and high stiffness and strength. For broader implementation of those materials though, the out-of-autoclave production processes have to be optimized, to allow for higher reliability of the parts produced as well as cost reduction and improved production speed. This optimization can be achieved by monitoring and controlling resin filling and curing cycles. Photonic Integrated Circuits (PICs), and, in particular, Silicon Photonics, owing to their fast response, small size, ability to operate at higher temperatures, immunity to electromagnetic interference, and compatibility with CMOS fabrication techniques, can offer sensing solutions fulfilling the requirements for composite material production using carbon fibres. In this paper, we demonstrate a passive optical temperature sensor, based on a 220 nm height Silicon-on-Insulator platform, embedded in a composite tool used for producing RTM-6 composite parts of high quality (for use in the aerospace industry). The design methodology of the photonic circuit as well as the experimental results and comparison with the industry standard thermocouples during a thermal cycling of the tool are presented. The optical sensor exhibits high sensitivity (85 pm/°C), high linearity (R2 = 0.944), and is compatible with the RTM-6 production process, operating up to 180 °C.

High-Linearity Wireless Passive Temperature Sensor Based on Metamaterial Structure with Rotation-Insensitive Distance-Based Warning Ability

A wireless passive temperature sensor based on a metamaterial structure is proposed that is capable of measuring the temperature of moving parts. The sensor structure consists of an alumina ceramic substrate with a square metal double split-ring resonator fixed centrally on the ceramic substrate. Since the dielectric constant of the alumina ceramic substrate is temperature sensitive, the resonant frequency of the sensor is altered due to changes in temperature. A wireless antenna is used to detect the change in the resonant frequency of the sensor using a wireless antenna, thereby realizing temperature sensing operation of the sensor. The temperature sensitivity of the sensor is determined to be 205.22 kHz/°C with a strong linear response when tested over the temperature range of 25-135 °C, which is evident from the R2 being 0.995. Additionally, the frequency variation in this sensor is insensitive to the angle of rotation and can be used for temperature measurement of rotating parts. The sensor also has a distance warning functionality, which offers additional safety for the user by providing early warning signals when the heating equipment overheats after operating for extended durations.

Temperature Sensors Integrated with an Electrochromic Readout toward Visual Detection

Temperature sensors have attracted great attention for personal health care and disease diagnosis in recent years. However, it is still a great challenge to fabricate reliable and highly sensitive temperature sensors that can convert physiological signals into easily readable signals in a convenient way. Herein, an integrated smart temperature sensor system based on a traditional temperature sensor and electrochromic display is proposed for real-time visual detection of temperature. Significantly, a voltage-regulated electrochromic device (ECD) based on tungsten oxide (WO3) and polyaniline (PANI) as the real-time visualization window was integrated into the platform to provide feedback on the temperature change. The ECD would change its color from green to blue based on the electrical signal of the temperature sensor, resulting in a visualized readout that can be monitored through our naked eye. Additionally, the smart temperature sensor system possesses an extremely durable property and cycle stability, remaining around 90% of the initial value even after 15,000 s continuous cycle. Thus, the novel design and low power consumption advantages make it a good candidate to pave the way for developing interactive wearable electronics and intelligent robots as real-time temperature feedback systems.

Objective Methods of Monitoring Usage of Orthotic Devices for the Extremities: A Systematic Review

Orthoses are commonly prescribed to relieve symptoms for musculoskeletal and neurological conditions; however, patients stop wearing orthoses as recommended for many reasons. When considering the effectiveness of orthoses, there needs to be an objective way to monitor whether participants wear the orthosis as instructed, because if this is not followed, the orthoses will not work as intended. This review aimed to identify, summarise, and compare objective methods used to measure compliance with orthoses applied to the extremities. Databases (Scopus, Web of Science, Embase, CINAHL, and MEDLINE) were searched for eligible studies. Twenty-three studies were accepted in the final review, including five studies that employed upper limb orthoses, two that employed hip orthoses, and fifteen that employed lower limb orthoses. To measure compliance objectively, studies utilised temperature sensors, pressure sensors, accelerometers, a step counter, or a combination of sensors. All sensor types have their own advantages and disadvantages and should be chosen based on study-specific parameters. Sensor-derived monitoring provides quantitative, objective data that are beneficial in both clinical and research settings. The ideal solution to monitoring compliance would consist of both objective and user-reported aspects that, in combination, would provide an all-encompassing picture of the orthotic treatment prescribed.

Machine-Learning-Based Calibration of Temperature Sensors

Temperature sensors are widely used in industrial production and scientific research, and accurate temperature measurement is crucial for ensuring the quality and safety of production processes. To improve the accuracy and stability of temperature sensors, this paper proposed using an artificial neural network (ANN) model for calibration and explored the feasibility and effectiveness of using ANNs to calibrate temperature sensors. The experiment collected multiple sets of temperature data from standard temperature sensors in different environments and compared the calibration results of the ANN model, linear regression, and polynomial regression. The experimental results show that calibration using the ANN improved the accuracy of the temperature sensors. Compared with traditional linear regression and polynomial regression, the ANN model produced more accurate calibration. However, overfitting may occur due to a small sample size or a large amount of noise. Therefore, the key to improving calibration using the ANN model is to design reasonable training samples and adjust the model parameters. The results of this study are important for practical applications and provide reliable technical support for industrial production and scientific research.

Ultracompact MXene V2C-Improved Temperature Sensor by a Runway-Type Microfiber Knot Resonator

We demonstrate an all-fiber, compact-structure, high-sensing-efficiency temperature sensor using a resonator structure sensor device of a runway type and MXene V2C. The high-quality functional material MXene V2C, synthesized by a simple two-step method, has excellent photothermal conversion performance. As-prepared MXene V2C is integrated into the runway section of a runway-type microfiber knot resonator based on the coupling mechanism between the surface near the field of the fiber and materials. When the temperature variation range is ~25-70 °C, the corresponding transmission light intensity variation is linear, and the maximum normalized sensing efficiency is 2.21 dB/°C/mm. Our work demonstrates that the runway-type structure ensures the compactness of the sensor device and enhances the interaction distance between the material and the microfiber, which provides additional integration strategies for functional material-based sensor devices.

Flexible Wet-Spun PEDOT:PSS Microfibers Integrating Thermal-Sensing and Joule Heating Functions for Smart Textiles

Multifunctional fiber materials play a key role in the field of smart textiles. Temperature sensing and active thermal management are two important functions of smart fabrics, but few studies have combined both functions in a single fiber material. In this work, we demonstrate a temperature-sensing and in situ heating functionalized conductive polymer microfiber by exploiting its high electrical conductivity and thermoelectric properties. The conductive polymer microfibers were prepared by wet-spinning the PEDOT:PSS aqueous dispersion with ionic liquid additives, which was used to enhance the electrical and mechanical properties of the final microfibers. The thermoelectric properties of these microfibers were further studied. Due to their excellent flexibility and mechanical properties, these fibers can be easily integrated into commercial fabrics for the manufacture of smart textiles through knitting. We further demonstrated a smart glove with integrated temperature-sensing and in situ heating functions, and further explored thermoelectric fiber-based temperature-sensing array fabric. These works combine the thermoelectric properties and heating function of conductive polymer fibers, providing new insights that enable further development of high-performance, multifunctional wearable smart textiles.

Enhanced Photovoltaic Effect in n-3C-SiC/p-Si Heterostructure Using a Temperature Gradient for Microsensors

The development of fifth-generation (5G) communications and the Internet of Things (IoT) has created a need for high-performance sensing networks and sensors. Improving the sensitivity and reducing the energy consumption of these sensors can improve the performance of the sensing network and conserve energy. This paper reports a large enhancement of the photovoltaic effect in a 3C-SiC/Si heterostructure and the tunability of the photovoltage under the impact of a temperature gradient, which has the potential to increase the sensitivity and reduce the energy consumption of microsensors. To start with, cubic silicon carbide (3C-SiC) was grown on a silicon wafer, and a micro-3C-SiC/Si heterostructure device was then fabricated using standard photolithography. The result revealed that the sensor could either capture light energy, transform it into electrical energy for self-power purposes, or detect light with intensities of 1.6 and 4 mW/cm2. Under the impact of the temperature gradient induced by conduction heat transfer from a heater, the measured photovoltage was improved. This thermo-phototronic coupling enhanced the photovoltage up to 51% at a temperature gradient of 8.73 K and light intensity of 4 mW/cm2. Additionally, the enhancement can be tuned by controlling the direction of the temperature gradient and the temperature difference. These findings indicate the promise of the temperature gradient in SiC/Si heterostructures for developing high-performance temperature sensors and self-powered photodetectors.

Integrated Fiber Ring Laser Temperature Sensor Based on Vernier Effect with Lyot-Sagnac Interferometer

The Vernier effect created using an incorporated Lyot-Sagnac loop is used to create an ultra-high sensitivity temperature sensor based on a ring laser cavity. Unlike standard double Sagnac loop systems, the proposed sensor is fused into a single Sagnac loop by adjusting the welding angle between two polarization-maintaining fibers (PMFs) to achieve effective temperature sensitivity amplification. The PMFs are separated into two arms of 0.8 m and 1 m in length, with a 45° angle difference between the fast axes. The sensor's performance is examined both theoretically and experimentally. The experimental results reveal that the Vernier amplification effect can be achieved via PMF rotating shaft welding. The temperature sensitivity in the laser cavity can reach 2.391 nm/°C, which is increased by a factor of more than eight times compared with a single Sagnac loop structure (0.298 nm/°C) with a length of 0.8 m without the Vernier effect at temperatures ranging from 20 °C to 30 °C. Furthermore, unlike traditional optical fiber sensing that uses a broadband light source (BBS) for detection, which causes issues such as low signal-to-noise ratio and broad bandwidth, the Sagnac loop can be employed as a filter by inserting itself into the fiber ring laser (FRL) cavity. When the external parameters change, the laser is offset by the interference general modulation, allowing the external temperature to be monitored. The superior performance of signal-to-noise ratios of up to 50 dB and bandwidths of less than 0.2 nm is achieved. The proposed sensor has a simple structure and high sensitivity and is expected to play a role in biological cell activity monitoring.

Highly Sensitive Temperature Detection Based on a Frost- and Dehydration-Resistive Ion-Doped Hydrogel-MXene Composite

Wearable temperature sensors with high sensitivity and stability hold great potential for human health monitoring. However, hydrogels, which are commonly used for wearable devices, often show poor thermal and electrical conductivity and are susceptible to dehydration and freezing. Herein, we developed a frost- and dehydration-resistive temperature sensor based on Fe²⁺/Ti₂CT_x/κ-carrageenan (CA)-polyacrylamide (PAM) hydrogel. The Fe²⁺ ions within the hydrogel existed in two forms: as free ions and bonded ions. The free Fe²⁺ ions could complex with water molecules, resulting in the improved resistance to dehydration and freezing, as well as enhanced ionic conductivity in the hydrogel. On the other hand, the remaining Fe²⁺ ions acted as linkers to form coordination bonds with the sulfate groups of CA chains, resulting in the greatly enhanced mechanical strength of the hydrogel. In addition, the Ti₂CT_x nanosheet-based fillers formed a well-defined porous laminar structure, which reduced the phonon scattering and improved the phonon adsorption within the hydrogel. The Fe²⁺/Ti₂CT_x/CA-PAM hydrogel sensor exhibited excellent temperature sensing performance including a good linearity (R² = 0.998) within a broad working range (-10 to 60 °C), high resolution (0.1 °C), and good repeatability. Furthermore, the sensor was integrated into a wireless system for continuous monitoring of body temperature, demonstrating its potential in healthcare monitoring, electronic skins, and intelligent robots.

A Circuit-Level Solution for Secure Temperature Sensor

Temperature sensors play an important role in modern monitoring and control applications. When more and more sensors are integrated into internet-connected systems, the integrity and security of sensors become a concern and cannot be ignored anymore. As sensors are typically low-end devices, there is no built-in defense mechanism in sensors. It is common that system-level defense provides protection against security threats on sensors. Unfortunately, high-level countermeasures do not differentiate the root of cause and treat all anomalies with system-level recovery processes, resulting in high-cost overhead on delay and power consumption. In this work, we propose a secure architecture for temperature sensors with a transducer and a signal conditioning unit. The proposed architecture estimates the sensor data with statistical analysis and generates a residual signal for anomaly detection at the signal conditioning unit. Moreover, complementary current-temperature characteristics are exploited to generate a constant current reference for attack detection at the transducer level. Anomaly detection at the signal conditioning unit and attack detection at the transducer unit make the temperature sensor attack resilient to intentional and unintentional attacks. Simulation results show that our sensor is capable of detecting an under-powering attack and analog Trojan from a significant signal vibration in the constant current reference. Furthermore, the anomaly detection unit detects anomalies at the signal conditioning level from the generated residual signal. The proposed detection system is resilient against any intentional and unintentional attacks, with a detection rate of 97.73%.

Stretchable and Skin-Mountable Temperature Sensor Array Using Reduction-Controlled Graphene Oxide for Dermatological Thermography

Since thermometry of human skin is critical information that provides important aspects of human health and physiology, accurate and continuous temperature measurement is required for the observation of physical abnormalities. However, conventional thermometers are uncomfortable because of their bulky and heavy features. In this work, we fabricated a thin, stretchable array-type temperature sensor using graphene-based materials. Furthermore, we controlled the degree of graphene oxide reduction and enhanced the temperature sensitivity. The sensor exhibited an excellent sensitivity of 2.085% °C^-1. The overall device was designed in a wavy meander shape to provide stretchability for the device so that precise detection of skin temperature could be performed. Furthermore, polyimide film was coated to secure the chemical and mechanical stabilities of the device. The array-type sensor enabled spatial heat mapping with high resolution. Finally, we introduced some practical applications of skin temperature sensing, suggesting the possibility of skin thermography and healthcare monitoring.

Effect of One Step Solid State Reaction Route on the Semiconductor Behavior of the Spinel (NI, Co, and Mn)O4 to Be Used as Temperature Sensor

Achieving carbon neutrality is important to solve environmental problems and thus requires decarbonizing manufacturing processes to reduce greenhouse gas emissions. The firing of ceramics, including calcination and sintering, is a typical fossil fuels-driven manufacturing process that requires large power consumption. Although the firing process in manufacturing ceramics cannot be eliminated, an effective firing strategy to reduce processing steps can be a choice to lower power consumption. Herein, we suggest a one-step solid solution reaction (SSR) route to manufacture (Ni, Co, and Mn)O₄ (NMC) electroceramics for their application in temperature sensors with negative temperature coefficient (NTC). Additionally, the effect of the one-step SSR route on the electrical properties of the NMC is investigated. Similar to the NMC prepared using the two-step SSR route, spinel structures with dense microstructure are observed in the NMC prepared via the one-step SSR route. Based on the experimental results, the one-step SSR route can be considered as one of the effective processing techniques with less power consumption to manufacture electroceramics.

A Temperature-to-Frequency Converter-Based On-Chip Temperature Sensor with an Inaccuracy of +0.65 °C/-0.49 °C

This paper proposes a temperature sensor based on temperature-frequency conversion using 180 nm CMOS technology. The temperature sensor consists of a proportional-to-absolute temperature (PTAT) current generating circuit, a relaxation oscillator with oscillation frequency proportional to temperature (OSC-PTAT), a relaxation oscillator with oscillation frequency independent of temperature (OSC-CON), and a divider circuit cascaded with D flip-flops. Using BJT as the temperature sensing module, the sensor has the advantages of high accuracy and high resolution. An oscillator that uses PTAT current to charge and discharge capacitors to achieve oscillation, and utilizes voltage average feedback (VAF) to enhance the frequency stability of the oscillator is tested. Through the dual temperature sensing process with the same structure, the influence of variables such as power supply voltage, device, and process deviation can be reduced to a certain extent. The temperature sensor in this paper was implemented and tested with a temperature measurement range of 0-100 °C, an inaccuracy of +0.65 °C/-0.49 °C after two-point calibration, a resolution of 0.003 °C, a resolution Figure of Merit (FOM) of 6.7 pJ/K², an area of 0.059 mm², and a power consumption of 32.9 μW.

A CMOS Temperature Sensor with a Smart Calibrated Inaccuracy of ±0.11 (3σ)

This paper presents a BJT-based smart CMOS temperature sensor. The analog front-end circuit contains a bias circuit and a bipolar core; the data conversion interface features an incremental delta-sigma analog-to-digital converter. The circuit utilizes the chopping, correlated double sampling, and dynamic element matching techniques to mitigate the effects of process bias and nonideal device characteristics on measurement accuracy. Furthermore, based on the principle of charge conservation, the dynamic range utilization of the ADC increases. We propose a neural network that uses a multilayer convolutional perceptron to calibrate the sensor output results. Using the algorithm, the sensor achieves an inaccuracy of ±0.11 °C (3σ), exceeding the accuracy of ±0.23 °C (3σ) achieved without calibration. We implement the sensor in a 0.18 µm CMOS process, occupying an area of 0.42 mm². It achieves a resolution of 0.01 °C and has a conversion time of 24 ms.

Flexible and Wearable Strain-Temperature Sensors Based on Chitosan/Ink Sponges

A simple and economic strategy to construct a chitosan-ink carbon nanoparticle sponge sensor was proposed by freeze-drying of chitosan and Chinese ink mixture solution. The microstructure and physical properties of the composite sponges with different ratios are characterized. The interfacial compatibility of chitosan and carbon nanoparticles in ink is satisfied, and the mechanical property and porosity of chitosan was increased by the incorporation of carbon nanoparticles. Due to excellent conductivity and good photothermal conversion effect of the carbon nanoparticles in ink, the constructed flexible sponge sensor has satisfactory strain and temperature sensing performance and high sensitivity (133.05 ms). In addition, these sensors can be successfully applied to monitor the large joint movement of the human body and the movement of muscle groups near the esophagus. Dual functionally integrated sponge sensors show great potential for strain and temperature detection in real time. The prepared chitosan-ink carbon nanoparticle composite shows promising applications in wearable smart sensors.

Flexible and Transparent Electronic Skin Sensor with Sensing Capabilities for Pressure, Temperature, and Humidity

Inspired by the interlocked biological geometry of human skin, herein, we design a flexible and transparent sensor with interlocked square column arrays with composites of Ag nanoparticles (AgNPs), citric acid (CA), and poly(vinyl alcohol) (PVA), which exhibit multisensory capabilities for pressure, temperature, and humidity. As a flexible pressure sensor, the interlocked AgNPs/CA/PVA sensor possesses a high sensitivity (-1.82 kPa^-1), low detection limit (10 Pa), fast response (75 ms), and outstanding stability due to the high sensitivity of the contact resistance of the interlocked square column arrays to pressure. Because of the rigid dependence of the resistance of the AgNPs/CA/PVA composite on temperature, the interlocked AgNPs/CA/PVA sensor can also act as a temperature sensor, which exhibits high resolution (0.1 °C) and reliability in detecting ambient temperature. In addition, it is found that the amount of water molecules adsorbed by PVA and CA changes with the ambient humidity. Therefore, the interlocked AgNPs/CA/PVA sensor is also able to detect humidity in real time. This work proposes a simple but useful route to fabricate a flexible and transparent electrical skin sensor, which has great potential in the perception of pressure, temperature, and humidity.

Distributed Intelligent Battery Management System Using a Real-World Cloud Computing System

In this work, a decentralized but synchronized real-world system for smart battery management was designed by using a general controller with cloud computing capability, four charge regulators, and a set of sensorized battery monitors with networking and Bluetooth capabilities. Currently, for real-world applications, battery management systems (BMSs) can be used in the form of distributed control systems where general controllers, charge regulators, and smart monitors and sensors are integrated, such as those proposed in this work, which allow more precise estimations of a large set of important parameters, such as the state of charge (SOC), state of health (SOH), current, voltage, and temperature, seeking the safety and the extension of the useful life of energy storage systems based on battery banks. The system used is a paradigmatic real-world example of the so-called intelligent battery management systems. One of the contributions made in this work is the realization of a distributed design of a BMS, which adds the benefit of increased system security compared to a fully centralized BMS structure. Another research contribution made in this work is the development of a methodical modeling procedure based on Petri Nets, which establishes, in a visible, organized, and precise way, the set of conditions that will determine the operation of the BMS. If this modeling is not carried out, the threshold values and their conditions remain scattered, not very transparent, and difficult to deal with in an aggregate way.

Thermally Triggered Multilevel Diffractive Optical Elements Tailored by Shape-Memory Polymers for Temperature History Sensors

The morphological transitions induced by external stimuli in shape-memory polymers (SMPs) can be exploited with the real-time response of far-field diffraction patterns in diffractive optical elements (DOEs). In this paper, we combine the temperature characteristics of SMPs and the display characteristics of DOEs to obtain an optical temperature sensing film where the temperature information is taken as a change of far-field diffraction images. This process was achieved by imprinting the micropatterns of the DOEs on the epoxy-based SMP film, which can be programmed to hold a temporary optical image and revert to its original image upon exposure to a specific temperature. Furthermore, the specific temperature at which the image transformation occurs can be customized by varying the chain flexibility of the SMP. Based on a range of transition points, by imprinting the desired combination of SMP-DOEs on a film, a sensor that can record and inform the temperature history is demonstrated. As for the feasible application of this technique, it can be used for the compact and reliable optical temperature indicators, which can be applied in temperature-sensitive industries such as food and pharmaceuticals.

Fabrication of Temperature Sensors with High-Performance Uniformity through Thermal Annealing

It is considered to be of great significance to monitor human health and track the effect of drugs by measuring human temperature mapping through flexible temperature sensors. In this work, we found that the thermal annealing of flexible temperature sensors based on graphite-acrylate copolymer composites can not only improve the temperature coefficient of resistance (TCR) values of the devices, but also greatly improve the uniformity of the performance of the devices prepared in parallel. The best results were obtained when the devices were annealed at 100 °C, which is believed to be due to the rearrangement of graphite particles to generate more uniform and numerous conductive channels within the conductive composite. We believe this finding might promote the practical development of flexible temperature sensors in body temperature sensing for health maintenance and medical applications.

Highly sensitive temperature sensor using one-dimensional Bragg Reflector for biomedical applications

A theoretical investigation of multi-layer Bragg Reflector (BR) structure to design highly sensitive temperature sensor is proposed to measure the temperature over a wide range. Characteristic-Matrix (CM) mathematical tool is used to design and analyse the proposed temperature sensor. A 1D Distributed Bragg Reflector multi-layer structure is used to design and analyse the sensing characteristics of the proposed sensor. Periodic modulation in the Refractive-Index (RI) of the two materials, high and low, forms DBR multi-layer structure. Germanium and air are used as the two alternate materials of BR for high and low dielectric layers respectively. Parameters of many semiconductor materials, including germanium, varies with temperature. Here we have considered RI variation of germanium with the temperature to model and design the proposed sensor. A defect layer is introduced at the center of multi-layer structure to obtain the resonating mode for an incident electromagnetic wave. The sensor can detect temperature over a wide range from 100 to 550 K. A resonating mode, shifting towards different wavelength region is observed for the temperature variations. The influence of increase in the DBR layers (N) and defect cavity geometrical length (l_D) is studied. The obtained results conclude that the cavity defect length and BR layers affects the sensing parameters of the designed sensor. The obtained RI sensitivity, Q-factor, temperature sensitivity and detection limit of the sensor are 2.323 μm/RIU, 115,000, 1.18 nm/K and 9.024 × 10^-6 RIU respectively. Theoretically obtained transmission spectrum was validated using Monte Carlo simulation.

Calligraphy and Kirigami/Origami-Inspired All-Paper Touch-Temperature Sensor with Stimulus Discriminability

The use of cost-effective renewable raw materials to develop electronic devices has been strongly demanded for sustainable and biodegradable green electronics. Here, by taking inspiration from the traditional calligraphy and kirigami/origami arts, we show a novel cuttable and foldable all-paper touch-temperature sensors fabricated by simply brushing the carbon black ink onto the cellulose paper followed by a layer-layer lamination strategy. The use of environmentally friendly common commodities in daily life including carbon black ink and cellulose paper as the main component materials of sensors effectively lowers the cost and has positive impacts on the environment and health. The sensors can be freely cut or folded into the targeted shapes and can even reversibly morph between 2D and 3D configurations without affecting device function. Additionally, the sensors show a discrimination capability toward pressure and temperature. Our fabrication strategy provides a promising approach for creating the low-cost eco-friendly sensors with a versatile pattern design and a morphing shape without sacrificing the global structural integrity and device functionality.

Layer-by-Layer Deposited Multi-Modal PDAC/rGO Composite-Based Sensors

Different environmental parameters, such as temperature and humidity, aggravate food spoilage, and different volatile organic compounds (VOCs) are released based on the extent of spoilage. In addition, a lack of efficient monitoring of the dosage of pesticides leads to crop failure. This could lead to the loss of food resources and food production with harmful contaminants and a short lifetime. For this reason, precise monitoring of different environmental parameters and contaminations during food processing and storage is a key factor for maintaining its safety and nutritional value. Thus, developing reliable, efficient, cost-effective sensor devices for these purposes is of utmost importance. This paper shows that Poly-(diallyl-dimethyl ammonium chloride)/reduced Graphene oxide (PDAC/rGO) films produced by a simple Layer-by-Layer deposition can be effectively used to monitor temperature, relative humidity, and the presence of volatile organic compounds as indicators for spoilage odors. At the same time, they show potential for electrochemical detection of organophosphate pesticide dimethoate. By monitoring the resistance/impedance changes during temperature and relative humidity variations or upon the exposure of PDAC/rGO films to methanol, good linear responses were obtained in the temperature range of 10-100 °C, 15-95% relative humidity, and 35 ppm-55 ppm of methanol. Moreover, linearity in the electrochemical detection of dimethoate is shown for the concentrations in the order of 10² µmol dm^-3. The analytical response to different external stimuli and analytes depends on the number of layers deposited, affecting sensors' sensitivity, response and recovery time, and long-term stability. The presented results could serve as a starting point for developing advanced multi-modal sensors and sensor arrays with high potential for analytical applications in food safety and quality monitoring.

Ratiometric Temperature Sensing Using Highly Coupled Seven-Core Fibers

In this paper, a ratiometric approach to sensing temperature variations is shown using specialty fiber optic devices. We analyzed the transmission response of cascaded segments of multicore fibers (MCFs), and dissimilar lengths were found to generate an adequate scheme for ratiometric operation. The perturbation of optical parameters in the MCFs translates to a rich spectral behavior in which some peaks increase their intensity while others decrease their intensity. Thus, by selecting opposite-behavior peaks, highly sensitive ratiometric measurements that provide robustness against spurious fluctuations can be performed. We implemented this approach using seven-core fiber (SCF) segments of 5.8 cm and 9.9 cm. To test the system's response under controlled perturbations, we heated one of the segments from ambient temperature up to 150 °C. We observed defined peaks with opposite behavior as a function of temperature. Two pairs of peaks within the interrogation window were selected to perform ratiometric calculations. Ratiometric measurements exhibited sensitivities 6-14 times higher than single-wavelength measurements. A similar trend with enhanced sensitivity in both peak pairs was obtained. In contrast to conventional interferometric schemes, the proposed approach does not require expensive facilities or micrometric-resolution equipment. Moreover, our approach has the potential to be realized using commercial splicers, detectors, and filters.

An Ultrahigh Linear Sensitive Temperature Sensor Based on PANI:Graphene and PDMS Hybrid with Negative Temperature Compensation

The detection of human body temperature is one of the important indicators to reflect the physical condition. In order to accurately judge the state of the human body, a high-performance temperature sensor with fast response, high sensitivity, and good linearity characteristics is urgently needed. In this paper, the positive temperature characteristics of graphene-polydimethylsiloxane (PDMS) composite with high sensitivity were studied. Besides, doping polyaniline (PANI) with special negative temperature characteristics as the temperature compensation of the composite finally creatively solved the problem of sensor nonlinearity from the material level. Thus, the PANI:graphene and PDMS hybrid temperature sensor with extraordinary linearity and high sensitivity is realized by establishing the space-gap model and mathematical theoretical analysis. The prepared sensor exhibits high sensitivity (1.60%/°C), linearity (R² = 0.99), accuracy (0.3 °C), and time response (0.7 s) in the temperature sensing range of 25-40 °C. Based on this, the fabricated temperature sensor can combine with the read-out circuit and filter circuit with a high-precision analog digital converter (ADC) to monitor real-time skin temperature, ambient temperature, and respiratory rate, et al. This high-performance temperature sensor reveals its great potential in electronic skin, disease diagnosis, medical monitoring, and other fields.

Melt Temperature Estimation by Machine Learning Model Based on Energy Flow in Injection Molding

Highly reliable and accurate melt temperature measurements in the barrel are necessary for stable injection molding. Conventional sheath-type thermocouples are insufficiently responsive for measuring melt temperatures during molding. Herein, machine learning models were built to predict the melt temperature after plasticizing. To supply reliably labeled melt temperatures to the models, an optimized temperature sensor was developed. Based on measured high-quality temperature data, three machine learning models were built. The first model accepted process setting parameters as inputs and was built for comparisons with previous models. The second model accepted additional measured process parameters related to material energy flow during plasticizing. Finally, the third model included the specific heat and part weights reflecting the material energy, in addition to the features of the second model. Thus, the third model outperformed the others, and its loss decreased by more than 70%. Meanwhile, the coefficient of determination increased by about 0.5 more than those of the first model. To reduce the dataset size for new materials, a transfer learning model was built using the third model, which showed a high prediction performance and reliability with a smaller dataset. Additionally, the reliability of the input features to the machine learning models were evaluated by shapley additive explanations (SHAP) analysis.

Smartphone-Based Optical Fiber Fluorescence Temperature Sensor

Optical fiber sensors are one preferred solution for temperature sensing, especially for their capability of real-time monitoring and remote detection. However, many of them still suffer from a huge sensing system and complicated signal demodulate process. In order to solve these problems, we propose a smartphone-based optical fiber fluorescence temperature sensor. All the components, including the laser, filter, fiber coupler, batteries, and smartphone, are integrated into a 3D-printed shell, on the side of which there is a fiber flange used for the sensing probe connection. The fluorescence signal of the rhodamine B solution encapsulated in the sensing probe can be captured by the smartphone camera and extracted into the R value and G value by a self-developed smartphone application. The temperature can be quantitatively measured by the calibrated G/R-temperature relation, which can be unified using the same linear relationship in all solid-liquid-gas environments. The performance verifications prove that the sensor can measure temperature in high accuracy, good stability and repeatability, and has a long conservation time for at least 3 months. The proposed sensor not only can measure the temperature for remote and real-time detection needs, but it is also handheld with a small size of 167 mm × 85 mm × 75 mm supporting on-site applications. It is a potential tool in the temperature sensing field.

In-Line Mach Zehnder Interferometer Based on Ytterbium Doped Fiber with Up-Taper Structure in Fiber Ring Laser and Its Application in Sensing

We report an ytterbium (Yb) doped fiber Mach Zehnder interferometer (MZI) based on the up-taper fiber structure in a fiber ring laser (FRL) cavity. Different from the traditional FRL sensing system, in which additional filters are required, the designed structure simultaneously acts as a filter, sensor and gain medium. Furthermore, thanks to the high thermal-optical coefficient of Yb doped fiber, the temperature sensitivity of 0.261 nm/°C can be achieved in the range of 10-50 °C. In addition, benefiting from the unique characteristics of the laser system itself, the designed structure has a narrower linewidth (-0.2 nm) and a higher signal-to-noise ratio (SNR) (-40 dB) than the sensor system based on a broadband light source (BBS). Meanwhile, the refractive index (RI) response and stability of the system are measured. The RI sensitivity is up to 151 nm/RIU, and the wavelength fluctuation range within two hours is less than 0.2 nm. Therefore, the designed structure is expected to play a significant role in human life safety monitoring, aircraft engine temperature monitoring, etc.

Thermal-Resistance Effect of Graphene at High Temperatures in Nanoelectromechanical Temperature Sensors

Graphene membranes act as temperature sensors in nanoelectromechanical devices due to their excellent thermal and high-temperature resistance properties. Experimentally, reports on the sensing performance of graphene mainly focus on the temperature interval under 400 K. To explore the sensing performance of graphene temperature sensors at higher temperature intervals, micro-fabricated single-layer graphene on a SiN_X substrate is presented as temperature sensors by semiconductor technology and its electrical properties were measured. The results show that the temperature coefficient of the resistance value is 2.07 × 10^-3 in the temperature range of 300-450 K and 2.39 × 10^-3 in the temperature range of 450-575 K. From room temperature to high temperature, the "metal" characteristics are presented, and the higher TCR obtained at higher temperature interval is described and analyzed by combining Boltzmann transport equation and thermal expansion theory. These investigations provide further insight into the temperature characteristics of graphene.

Wedged Fiber Optic Surface Plasmon Resonance Sensor for High-Sensitivity Refractive Index and Temperature Measurements

Here, we experimentally demonstrate a wedged fiber optic surface plasmon resonance (SPR) sensor enabling high-sensitivity temperature detection. The sensing probe has a geometry with two asymmetrical bevels, with one inclined surface coated with an optically thin film supporting propagating plasmons and the other coated with a reflecting metal film. The angle of incident light can be readily tuned through modifying the beveled angles of the fiber tip, which has a remarkable impact on the refractive index sensitivity of SPR sensors. As a result, we measure a high refractive index sensitivity as large as 8161 nm/RIU in a wide refractive index range of 1.333-1.404 for the optimized sensor. Furthermore, we carry out a temperature-sensitivity measurement by packaging the SPR probe into a capillary filled with n-butanol. This showed a temperature sensitivity reaching up to -3.35 nm/°C in a wide temperature range of 20 °C-100 °C. These experimental results are well in agreement with those obtained from simulations, thus suggesting that our work may be of significance in designing reflective fiber optic SPR sensing probes with modified geometries.

Flat Photonic Crystal Fiber Plasmonic Sensor for Simultaneous Measurement of Temperature and Refractive Index with High Sensitivity

A compact temperature-refractive index (RI) flat photonic crystal fiber (PCF) sensor based on surface plasmon resonance (SPR) is presented in this paper. Sensing of temperature and RI takes place in the x- and y- polarization, respectively, to avoid the sensing crossover, eliminating the need for matrix calculation. Simultaneous detection of dual parameters can be implemented by monitoring the loss spectrum of core modes in two polarizations. Compared with the reported multi-function sensors, the designed PCF sensor provides higher sensitivities for both RI and temperature detection. A maximum wavelength sensitivity of -5 nm/°C is achieved in the temperature range of -30-40 °C. An excellent optimal wavelength sensitivity of 17,000 nm/RIU is accomplished in the RI range of 1.32-1.41. The best amplitude sensitivity of RI is up to 354.39 RIU^-1. The resolution of RI and temperature sensing is 5.88 × 10^-6 RIU and 0.02 °C, respectively. The highest value of the figure of merit (FOM) is 216.74 RIU^-1. In addition, the flat polishing area of the gold layer reduces the manufacturing difficulty. The proposed sensor has the characteristics of high sensitivity, simple structure, good fabrication repeatability, and flexible operation. It has potential in medical diagnosis, chemical inspection, and many other fields.