Dye Modification of Nanofibrous Silicon Oxide Membranes for Colorimetric HCl and NH3 Sensing

Colorimetric sensors for monitoring and visual reporting of acidic environments both in water and air are highly valuable in various fields, such as safety and technical textiles. Until now sol‐gel‐based colorimetric sensors are usually nonflexible bulk glass or thin‐film sensors. Large‐area, flexible sensors usable in strong acidic environments are not available. Therefore, in this study organically modified silicon oxide nanofibrous membranes are produced by combining electrospinning and sol‐gel technology. Two pH‐indicator dyes are immobilized in the nanofibrous membranes: methyl yellow via doping, methyl red via both doping, and covalent bonding. This resulted in sensor materials with a fast response time and high sensitivity for pH‐change in water. The covalent bond between dye and the sol‐gel network showed to be essential to obtain a reusable pH‐sensor in aqueous environment. Also a high sensitivity is obtained for sensing of HCl and NH₃ vapors, including a memory function allowing visual read‐out up to 20 min after exposure. These fast and reversible, large‐area flexible nanofibrous colorimetric sensors are highly interesting for use in multiple applications such as protective clothing and equipment. Moreover, the sensitivity to biogenic amines is demonstrated, offering potential for control and monitoring of food quality.     

Colorimetric Nanofibers as Optical Sensors

Sensors play a major role in many applications today, ranging from biomedicine to safety equipment, where they detect and warn us about changes in the environment. Nanofibers, characterized by high porosity, flexibility, and a large specific surface area, are the ideal material for ultrasensitive, fast‐responding, and user‐friendly sensor design. Indeed, a large specific surface area increases the sensitivity and response time of the sensor as the contact area with the analyte is enlarged. Thanks to the flexibility of membranes, nanofibrous sensors cannot only be applied in high‐end analyte detection, but also in personal, daily use. Many different nanofibrous sensors have already been designed; albeit, the most straightforward and easiest‐to‐interpret sensor response is a visual change in color, which is of particular interest in the case of warning signals. Recently, many researchers have focused on the design of so‐called colorimetric nanofibers, which typically involve the incorporation of a colorimetric functionality into the nanofibrous matrix. Many different strategies have been used and explored for colorimetric nanofibrous sensor design, which are outlined in this feature article. The many examples and applications demonstrate the value of colorimetric nanofibers for advanced optical sensor design, and could provide directions for future research in this area.     

Miniaturized Electronic Nose System Based on a Personal Digital Assistant

A small electronic nose (E‐Nose) system has been developed using an 8‐channel vapor detection array and personal digital assistant (PDA). The sensor array chip, integrated on a single microheater‐embedded polyimide substrate, was made of carbon black‐polymer composites with different kinds of polymers and plasticizers. We have successfully classified various volatile organic compounds such as methanol, ethanol, i‐propanol, benzene, toluene, n‐hexane, n‐heptane, and c‐hexane with the aid of the sensor array chip, and have evaluated the resolution factors among them, quantitatively. To achieve a PDA‐based E‐Nose system, we have also elaborated small sensor‐interrogating circuits, simple vapor delivery components, and data acquisition and processing programs. As preliminary results show, the miniaturized E‐Nose system has demonstrated the identification of essential oils extracted from mint, lavender, and eucalyptus plants.     

Methane Detection with a Tungsten-Calix[4]arene-Based Conducting Polymer Embedded Sensor Array

The detection of methane is important for industry, environment, and our daily life, but is made challenging by its small size, high volatility, and nonpolar nature. Herein, a tungsten-capped calix[4]arene-based p-doped conducting polymer with hexafluorophosphate or perchlorate counter-anions as a transducer is used to detect methane in dry air. The host–guest interaction between calixarene moieties within the polymer chain and methane molecules leads to the resistance variation of the polymer. The experimental limit of detection (LoD) of methane for the polymer-based sensor is demonstrated to be less than 50 ppm at room temperature, and the extrapolated theoretical LoD of 2 ppm represents exceptional sensitivity to methane. Furthermore, the discrimination of methane from interfering volatile organic compounds is achieved by exploiting a sensor array using complementary chemiresistors and principal component analysis.     

Highly Sensitive and Selective Biosensors Based on Organic Transistors Functionalized with Cucurbit[6]uril Derivatives

Biosensors based on a field‐effect transistor platform allow continuous monitoring of biologically active species with high sensitivity due to the amplification capability of detected signals. To date, a large number of sensors for biogenic substances have used high‐cost enzyme immobilization methods. Here, highly sensitive organic field‐effect transistor (OFET)‐based sensors functionalized with synthetic receptors are reported that can selectively detect acetylcholine (ACh⁺), a critical ion related to the delivery of neural stimulation. A cucurbit[6]uril (CB[6]) derivative, perallyloxyCB[6] ((allyloxy)₁₂CB[6], AOCB[6]), which is soluble in methanol but insoluble in water, has been solution‐deposited as a selective sensing layer onto a water‐stable p‐channel semiconductor, 5,5′‐bis‐(7‐dodecyl‐9H‐fluoren‐2‐yl)‐2,2′‐bithiophene layer. The OFET‐based sensors exhibit a detection limit down to 1 × 10^–12 m of ACh⁺, which is six orders of magnitude lower than that of ion‐selective electrode‐based sensors. Moreover, these OFET‐based sensors show highly selective discrimination of ACh⁺ over choline (Ch⁺). The findings demonstrate a viable method for the fabrication of OFET‐based biosensors with high sensitivity and selectivity, and allow for practical applications of OFETs as high‐performance sensors for biogenic substances.     

Nanoscale Graphene Doped with Highly Dispersed Silver Nanoparticles: Quick Synthesis,Facile Fabrication of 3D Membrane‐Modified Electrode,and Super Performance for Electrochemical Sensing

The performance of graphene‐based hybrid materials greatly depends on the dispersibility of nanoscale building blocks on graphene sheets. Here, a quick green synthesis of nanoscale graphene (NG) nanosheets decorated with highly dispersed silver nanoparticles (AgNPs) is demonstrated, and then the electrospinning technique to fabricate a novel nanofibrous membrane electrode material is utilized. With this technique, the structure, mechanical stability, biochemical functionality, and other properties of the fabricated membrane electrode material can be easily controlled. It is found that the orientations of NG and the dispersity of AgNPs on the surface of NG have significant effects on the properties of the fabricated electrode. A highly sensitive H₂O₂ biosensor is thus created based on the as‐prepared polymeric NG/AgNP 3D nanofibrous membrane‐modified electrode (MME). As a result, the fabricated biosensor has a linear detection range from 0.005 to 47 × 10^?3m (R = 0.9991) with a supralow detection limit of 0.56 × 10^?6m (S/N = 3). It is expected that this kind of nanofibrous MME has wider applications for the electrochemical detection and design of 3D functional nanomaterials in the future.     

MXene Functionalized,Highly Breathable and Sensitive Pressure Sensors with Multi-Layered Porous Structure

Breathable, flexible, and highly sensitive pressure sensors have drawn increasing attention due to their potential in wearable electronics for body-motion monitoring, human-machine interfaces, etc. However, current pressure sensors are usually assembled with polymer substrates or encapsulation layers, thus causing discomfort during wearing (i.e., low air/vapor permeability, mechanical mismatch) and restricting their applications. A breathable and flexible pressure sensor is reported with nonwoven fabrics as both the electrode (printed with MXene interdigitated electrode) and sensing (coated with MXene/silver nanowires) layers via a scalable screen-printing approach. Benefiting from the multi-layered porous structure, the sensor demonstrates good air permeability with high sensitivity (770.86–1434.89 kPa⁻¹), a wide sensing range (0–100 kPa), fast response/recovery time (70/81 ms), and low detection limit (≈1 Pa). Particularly, this sensor can detect full-scale human motion (i.e., small-scale pulse beating and large-scale walking/running) with high sensitivity, excellent cycling stability, and puncture resistance. Additionally, the sensing layer of the pressure sensor also displays superior sensitivity to humidity changes, which is verified by successfully monitoring human breathing and spoken words while wearing a sensor-embedded mask. Given the outstanding features, this breathable sensor shows promise in the wearable electronic field for body health monitoring, sports activity detection, and disease diagnosis.     

A fault-tolerant structural health monitoring protocol using wireless sensor networks

In wireless sensor network-based event detection approaches, when the decision is taken based on the measurements of sensors, sensor-fault and noise-related measurement error should be taken into account. Using Bayesian approach to form a judgment is problematic without additional information or assumptions (for example, the difficulty of knowing prior probabilities in practice). In making the final decision using the majority decision rule (as well as the k-out-of-n rule), measurement of every sensor is considered as fully reliable. However, due to sensor fault and environmental noise, the preciseness of all measurements may not be guaranteed in real-life applications. This paper presents a Dempster–Shafer theory of evidence-based structural health monitoring protocol using wireless sensor networks that overcome these limitations. Our proposal effectively discounts the unreliable observer’s (sensor’s) measurements. Extensive simulations show significant improvement in terms of detection accuracy as compared to other well-known approaches.     

A Self-Powered,Rechargeable, and Wearable Hydrogel Patch for Wireless Gas Detection with Extraordinary Performance

Flexible gas sensors play an indispensable role in diverse applications spanning from environmental monitoring to portable medical electronics. Full wearable gas monitoring system requires the collaborative support of high-performance sensors and miniaturized circuit module, whereas the realization of low power consumption and sustainable measurement is challenging. Here, a self-powered and reusable all-in-one NO₂ sensor is proposed by structurally and functionally coupling the sensor to the battery, with ultrahigh sensitivity (1.92%/ppb), linearity (R² = 0.999), ultralow theoretical detection limit (0.1 ppb), and humidity immunity. This can be attributed to the regulation of the gas reaction route at the molecular level. The addition of amphiphilic zinc trifluoromethanesulfonate (Zn(OTf)₂) enables the H₂O-poor inner Helmholtz layer to be constructed at the electrode–gel interface, thereby facilitating the direct charge transfer process of NO₂ here. The device is then combined with a well-designed miniaturized low-power circuit module with signal conditioning, processing and wireless transmission functions, which can be used as wearable electronics to realize early and remote warning of gas leakage. This study demonstrates a promising way to design a self-powered, sustainable, and flexible gas sensor with high performance and its corresponding wireless sensing system, providing new insight into the all-in-one system of gas detection.     

Graphene Enabled Low-Noise Surface Chemistry for Multiplexed Sepsis Biomarker Detection in Whole Blood

Affinity-based electrochemical (EC) sensors offer a potentially valuable approach for point-of-care (POC) diagnostics applications, and for the detection of diseases, such as sepsis, that require simultaneous detection of multiple biomarkers, but their development has been hampered due to biological fouling and EC noise. Here, an EC sensor platform that enables detection of multiple sepsis biomarkers simultaneously by incorporating a nanocomposite coating composed of crosslinked bovine serum albumin containing a network of reduced graphene oxide nanoparticles that prevents biofouling while maintaining electroconductivity is described. Using nanocomposite coated planar gold electrodes, a sensitive procalcitonin (PCT) sensor is constructed and validated in undiluted serum, which produced an excellent correlation with a conventional ELISA (adjusted r²  = 0.95) using clinical samples. A single multiplexed platform containing sensors for three different sepsis biomarkers—PCT, C-reactive protein, and pathogen-associated molecular patterns—is also developed, which exhibits specific responses within the clinically significant range without any cross-reactivity. This platform enables sensitive simultaneous EC detection of multiple analytes in human whole blood, and it can be applied to detect any target analyte with an appropriate antibody pair. Thus, this nanocomposite-enabled EC sensor platform may offer a potentially valuable tool for development of a wide range of clinical POC diagnostics.     

Strain Sensors with a High Sensitivity and a Wide Sensing Range Based on a Ti3C2Tx (MXene) Nanoparticle–Nanosheet Hybrid Network

A high sensitivity and large stretchability are desirable for strain sensors in wearable applications. However, these two performance indicators are contradictory, since the former requires a conspicuous structural change under a tiny strain, whereas the latter demands morphological integrity upon a large deformation. Developing strain sensors with both a high sensitivity (gauge factor (GF) > 100) and a broad strain range (>50%) is a considerable challenge. Herein, a unique Ti₃C₂T_x MXene nanoparticle–nanosheet hybrid network is constructed. The migration of nanoparticles leads to a large resistance variation while the wrapping of nanosheet bridges the detached nanoparticles to maintain the connectivity of the conductive pathways in a large strain region. The synergetic motion of nanoparticles and nanosheets endows the hybrid network with splendid electrical–mechanical performance, which is reflected in its high sensitivity (GF > 178.4) over the entire broad range (53%), the super low detection limit (0.025%), and a good cycling durability (over 5000 cycles). Such high performance endows the strain sensor with the capability for full‐range human motion detection.     

Exploiting Reactive Mobility for Collaborative Target Detection in Wireless Sensor Networks

Recent years have witnessed the deployments of wireless sensor networks in a class of mission-critical applications such as object detection and tracking. These applications often impose stringent Quality-of-Service requirements including high detection probability, low false alarm rate, and bounded detection delay. Although a dense all-static network may initially meet these Quality-of-Service requirements, it does not adapt to unpredictable dynamics in network conditions (e.g., coverage holes caused by death of nodes) or physical environments (e.g., changed spatial distribution of events). This paper exploits reactive mobility to improve the target detection performance of wireless sensor networks. In our approach, mobile sensors collaborate with static sensors and move reactively to achieve the required detection performance. Specifically, mobile sensors initially remain stationary and are directed to move toward a possible target only when a detection consensus is reached by a group of sensors. The accuracy of final detection result is then improved as the measurements of mobile sensors have higher Signal-to-Noise Ratios after the movement. We develop a sensor movement scheduling algorithm that achieves near-optimal system detection performance under a given detection delay bound. The effectiveness of our approach is validated by extensive simulations using the real data traces collected by 23 sensor nodes.     

Nonstationary thermoelectric power in multilayered structures with p-n junctions

It is shown that the nonstationary thermoelectric power with characteristic rise and fall times of the order of seconds in multilayered structures with p-n junctions can be several orders of magnitude greater than the stationary thermoelectric power in a homogeneous semiconductor. This effect can be observed in polycrystalline films and artificially produced multilayer structures with p-n junctions and thin layers. It can be used to produce ultrasensitive temperature sensors. Fiz. Tekh. Poluprovodn. 31, 920–921 (August 1997)     

Expected k-coverage in wireless sensor networks

We are concerned with wireless sensor networks where n sensors are independently and uniformly distributed at random in a finite plane. Events that are within a fixed distance from some sensor are assumed to be detectable and the sensor is said to cover that point. In this paper, we have formulated an exact mathematical expression for the expected area that can be covered by at least k out of n sensors. Our results are important in predicting the degree of coverage a sensor network may provide and in determining related parameters (sensory range, number of sensors, etc.) for a desired level of coverage. We demonstrate the utility of our results by presenting a node scheduling scheme that conserves energy while retaining network coverage. Additional simulation results have confirmed the accuracy of our analysis.     

A Survey of Energy-Efficient Scheduling Mechanisms in Sensor Networks

Sensor networks have a wide range of potential, practical and useful applications. However, there are issues that need to be addressed for efficient operation of sensor network systems in real applications. Energy saving is one critical issue for sensor networks since most sensors are equipped with non-rechargeable batteries that have limited lifetime. To extend the lifetime of a sensor network, one common approach is to dynamically schedule sensors' work/sleep cycles (or duty cycles). Moreover, in cluster-based networks, cluster heads are usually selected in a way that minimizes the total energy consumption and they may rotate among the sensors to balance energy consumption. In general, these energy-efficient scheduling mechanisms (also called topology configuration mechanisms) need to satisfy certain application requirements while saving energy. In this paper, we provide a survey on energy-efficient scheduling mechanisms in sensor networks that have different design requirements than those in traditional wireless networks. We classify these mechanisms based on their design assumptions and design objectives. Different mechanisms may make different assumptions about their sensors including detection model, sensing area, transmission range, failure model, time synchronization, and the ability to obtain location and distance information. They may also have different assumptions about network structure and sensor deployment strategy. Furthermore, while all the mechanisms have a common design objective to maximize network lifetime, they may also have different objectives determined by their target applications. A preliminary was presented in BROADNETS 2006 [29]     

Surface Plasmon Resonance Sensors Based on Polymer Optical Fiber

Surface Plasmon Resonance （SPR） is a powerful technique for directly sensing in biological studies, chemical detection and environmental pollution monitoring. In this paper, we present polymer optical fiber application in SPR sensors, including wavelength interrogation surface enhanced Raman scattering SPR sensor and surface enhanced Raman scattering （SERS） probe.
Long-period fiber gratings are fabricated on single mode polymer optical fiber （POF） with 120 μm period and 50% duty cycle. The polarization characteristic of this kind of birefringent grating is studied. Theoretical analysis shows it will be advantageous in SPR sensing applications.     

RFID sensors based on ubiquitous passive 13.56‐MHz RFID tags and complex impedance detection

Passive radio frequency identification (RFID) sensors are attractive in diverse applications where sensor performance is needed at a low cost and when battery‐free operation is critical. We developed a general approach for adapting ubiquitous and cost‐effective passive 13.56‐MHz RFID tags for diverse sensing applications. In developed RFID sensors, the complex impedance of the RFID resonant antenna is measured and correlated to physical, chemical, or biological properties of interest. In contrast to known wireless sensors, developed RFID sensors combine several measured parameters from the resonant sensor antenna with multivariate data analysis and deliver unique capability for multianalyte sensing and rejection of environmental interferences with a single sensor. Theoretical calculations and experiments in an anechoic chamber demonstrate that the developed RFID sensors are immune to common electromagnetic interferences and the sensor/reader system operates within regulated emission levels. Performance of developed RFID sensors is illustrated in measurements of toxic industrial chemicals (TICs) in air with the detection limit (DL) of 80 parts per billion and in a non‐invasive monitoring of milk spoilage. Sensors selectivity is demonstrated in the detection of different vapors with individual sensors. Copyright © 2008 John Wiley & Sons, Ltd.     

Nanoparticle-Based Strain Gauges: Anisotropic Response Characteristics,Multidirectional Strain Sensing,and Novel Approaches to Healthcare Applications

Directional strain sensing is essential for advanced sensor applications in the field of human-machine interfaces and healthcare. Here, the angle dependent anisotropic strain sensitivity caused by charge carriers percolating through cross-linked gold nanoparticle (GNP) networks is studied and these versatile materials are used for the fabrication of wearable triaxial pulse and gesture sensors. More specifically, the anisotropic response of 1,9-nonanedithiol cross-linked GNP films is separated into geometric and piezoresistive contributions by fitting the measured data with an analytic model. Hereby, piezoresistive coefficients of g₁₁ ∼ 32 and g₁₂ ∼ 21 are extracted, indicating a slightly anisotropic response behavior of the GNP-based material. To use the material for healthcare applications, arrangements of three GNP transducers are patterned lithographically and fully embedded into a highly flexible silicone polymer (Dragon Skin 30). The new encapsulation method ensures good and robust electrical contacts and enables facile handling and protection from external influences. A facile read-out with wireless data transmission using off-the-shelf electrical components underlines the great potential of these devices for applications as skin-wearable healthcare sensors.     

Connectivity properties of large-scale sensor networks

In wireless sensor networks, both nodes and links are prone to failures. In this paper we study connectivity properties of large-scale wireless sensor networks and discuss their implicit effect on routing algorithms and network reliability. We assume a network model of n sensors which are distributed randomly over a field based on a given distribution function. The sensors may be unreliable with a probability distribution, which possibly depends on n and the location of sensors. Two active sensor nodes are connected with probability p _e (n) if they are within communication range of each other. We prove a general result relating unreliable sensor networks to reliable networks. We investigate different graph theoretic properties of sensor networks such as k-connectivity and the existence of the giant component. While connectivity (i.e. k = 1) insures that all nodes can communicate with each other, k-connectivity for k > 1 is required for multi-path routing. We analyze the average shortest path of the k paths from a node in the sensing field back to a base station. It is found that the lengths of these multiple paths in a k-connected network are all close to the shortest path. These results are shown through graph theoretical derivations and are also verified through simulations.     

Isomorphous mixing of mesogenic anions and uncharged analogues in organised poly(ehtylene oxide)-alkali salt complexes

The preparation and characterisation of novel ionic polymer liquid crystal complexes of poly(ethylene oxide)–Na⁺ with mesogenic anions and their uncharged structural analogues in homogeneous mixtures are described. The systems discused most fully are the anion of the phenolic mesogen 4-n-hexyloxybenzylidene-4-hydroxy aniline (1 ) with its uncharged analogue 4-n-hexyloxybenzylidene aniline (1a ) and the anion of 5-(4-n-octyloxy-2,3-dicyanophenyleneoxycarbonyl)benzimidazo-le (2 ) and its uncharged analogue 4-octyloxy-2,3-dicyanophenyloxybenzoyl (2 ). Differential scanning calorimetry, wide angle x-ray diffraction and polarised light microscopy show that PEO–Na1 /1a and PEO–Na2 /2a are homogeneous mesogenic phases when Na1 or Na2 are present at 50% or less of the stoichiometric composition in complexes (EO : salt = 3 : 1) and the shortfall is made up from 1a or 2a uncharged analogues of 1a and related systems substituted by methoxy rather than hydrogen do not form homogeneous mixtures.