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A novel wireless microstrip-based RF sensor designed for detecting changes in the ionic content of water and the addition of solid contaminant objects is proposed and demonstrated for the purpose of water conservation and green cleaning. The sensor can be installed on the exterior wall of dielectric containers and customized according to the material of the container (such as porcelain) to enable wireless sensing inside the container. Its operation within the lower microwave frequency range (670–730 MHz) serves to minimize signal attenuation in water and streamline circuitry design. The most significant feature of this sensor is its unique design, rendering it impervious to its surrounding environment. This not only shields it from environmental noise but also maximizes its sensitivity by efficiently utilizing incoming power for sensing purposes. The sensor exhibits remarkable sensitivity, capable of detecting solute concentrations as low as 3.125 $ \times$ 10-3 M in water inside the container. It can also detect the insertion of foreign solid objects into the container from the exterior wirelessly and distinguish them from liquids being added. As a proof-of-concept demonstration, the sensor in this study was built for a porcelain wall of 10-12 mm thickness. The sensor's small size and the materials used for its fabrication make it an ideal choice for various smart bathroom applications, where accurate and reliable water use monitoring is essential for efficient water conservation and green cleaning. The sensor's ability to distinguish between the added solid objects and liquid electrolytes in the container provides the necessary sensing data for running water-saving and efficient washing mechanisms in bathrooms.

In this paper, the design considerations and basic equations related to thick-film screen-printed sensing devices are included. The geometry of the device and the patterns of the functional sensing film, or of the electrodes are taken into account for the determination of the operational frequency, noise voltage, quality factor and other key parameters, related to the proper work of the resistive, capacitive and surface acoustic wave based sensors. The determination of some parasitic components and possible errors is also provided. The focus is put on the most widely spread coating patterns related to this technology – meander and comb-shaped. The technology flow chart of the screen-printing technology is given and the approaches for fine-tuning the resistance at the thick-film resistive sensors are discussed. Comparison of the typically used materials for substrates, resistive, conductive, and dielectric coatings is made. Criteria for the selection of the different pastes or inks for specific applications are mentioned. [ABSTRACT FROM AUTHOR]

Silicon photonic micro-ring resonators (MRR) developed on the silicon-on-insulator (SOI) platform, owing to their high sensitivity and small footprint, show great potential for many chemical and biological sensing applications such as label-free detection in environmental monitoring, biomedical engineering, and food analysis. In this tutorial, we provide the theoretical background and give design guidelines for SOI-based MRR as well as examples of surface functionalization procedures for label-free detection of molecules. After introducing the advantages and perspectives of MRR, fundamentals of MRR are described in detail, followed by an introduction to the fabrication methods, which are based on a complementary metal-oxide semiconductor (CMOS) technology. Optimization of MRR for chemical and biological sensing is provided, with special emphasis on the optimization of waveguide geometry. At this point, the difference between chemical bulk sensing and label-free surface sensing is explained, and definitions like waveguide sensitivity, ring sensitivity, overall sensitivity as well as the limit of detection (LoD) of MRR are introduced. Further, we show and explain chemical bulk sensing of sodium chloride (NaCl) in water and provide a recipe for label-free surface sensing. [ABSTRACT FROM AUTHOR]

This tutorial explores the many different ways that electrical resistance can be used to sense changes in the environment. Resistance-based sensors span a wide spectrum of transfer characteristics from the linear to the non-linear and from small, sub-Ohm changes to changes in resistance that span many orders of magnitude. Electronic interface circuits suitable for measuring these resistances range from those that convert sensor resistance to an analog voltage to those that generate a square wave whose frequency, duty cycle, or phase indicates resistance. In this tutorial, voltage dividers, Wheatstone bridges, current sources, and current pumps are discussed to represent the broad choices for converting resistance to an analog voltage. Oscillators, resistance-to-phase converters, direct interface circuits, and analog to digital converter circuits that convert signals directly from resistance to digital signals are also discussed. This tutorial seeks to provide the novice circuit or sensor designer with a place to start in selecting the right interface circuit for processing signals from resistance-based sensors. It also offers some additional interface circuit alternatives to the more experienced engineer. [ABSTRACT FROM AUTHOR]

Metal-organic frameworks (MOFs), a newer class of crystalline nanoporous materials, have been in the limelight owing to their exceptional tunability for structures and physicochemical properties, and have found successful applications in gas storage, gas separation, and catalysis. The mesmerizing properties of MOFs, especially the extensive and tunable porosity and chemical selectivity, also make them an excellent candidate class as chemo-sensory materials. Moreover, MOF-based sensors have attracted considerable attention in the past decade. Recent literature reviews focused on the progress of MOF-based electronic sensors and luminescent MOF sensors, while sensors exploiting the dielectric properties (refractive index) of MOFs were also demonstrated and discussed very recently. The motivation of this report is to provide, for the first time, a general review on such MOF sensors with a particular focus on miniature optical fiber (OF) based MOF sensors and to demonstrate the promising potential of MOFs as dielectric coatings on OF for highly sensitive chemical sensing. The fundamental principle of OF-MOF sensors relies on the tunability of the refractive index of a MOF, which is dependent on the amount and type of adsorbed guest molecules in the MOF pores. MOF sensors based on different optical sensing principles are reviewed; challenges and perspectives on further research into the field of OF-MOF sensors are also discussed. [ABSTRACT FROM AUTHOR]

Background: Abnormally low or high blood iron levels are common health conditions worldwide and can seriously affect an individual’s overall well-being. A low-cost point-of-care technology that measures blood iron markers with a goal of both preventing and treating iron-related disorders represents a significant advancement in medical care delivery systems. Methods: A novel assay equipped with an accurate, storable, and robust dry sensor strip, as well as a smartphone mount and (iPhone) app is used to measure total iron in human serum. The sensor strip has a vertical flow design and is based on an optimized chemical reaction. The reaction strips iron ions from blood-transport proteins, reduces Fe(III) to Fe(II), and chelates Fe(II) with ferene, with the change indicated by a blue color on the strip. The smartphone mount is robust and controls the light source of the color reading App, which is calibrated to obtain output iron concentration results. The real serum samples are then used to assess iron concentrations from the new assay, and validated through intra-laboratory and inter-laboratory experiments. The intra-laboratory validation uses an optimized iron detection assay with multi-well plate spectrophotometry. The inter-laboratory validation method is performed in a commercial testing facility (LabCorp). Results: The novel assay with the dry sensor strip and smartphone mount, and App is seen to be sensitive to iron detection with a dynamic range of 50 – $300~\mu \text{g}$ /dL, sensitivity of 0.00049 a.u/ $\mu \text{g}$ /dL, coefficient of variation (CV) of 10.5%, and an estimated detection limit of $\sim 15~\mu \text{g}$ /dL These analytical specifications are useful for predicting iron deficiency and overloads. The optimized reference method has a sensitivity of 0.00093 a.u/ $\mu \text{g}$ /dL and CV of 2.2%. The correlation of serum iron concentrations (N = 20) between the optimized reference method and the novel assay renders a slope of 0.95, and a regression coefficient of 0.98, suggesting that the new assay is accurate. Last, a spectrophotometric study of the iron detection reaction kinetics is seen to reveal the reaction order for iron and chelating agent. Conclusion: The new assay is able to provide accurate results in intra- and inter- laboraty validations, and has promising features of both mobility and low-cost manufacturing suitable for global healthcare settings.

The increasing complexity of modern industrial production and potential threats of chemical or biological pollution due to accidents, transport incidents or terrorist attacks require the continuous monitoring of changes occurring in complex gas mixtures to eliminate effects such changes in a timely fashion. To make adequate decisions ina short timeframe, it is necessary to have complete information about a wide range of potential xenobiotics within the monitoring area. In this study, such an important scientific and practical problem is solved by the formation of a network of e-nose intelligent analyzers based on a cross-reactive array of chemical sensors using piezoelectric elements of a quartz crystal microbalance (QCM) as physical transducers connected by means of telecommunication protocols. A distributed remote-controlled sensor network provides operational control of the perimeter of a protected and/or dangerous zone by monitoring the gaseous environment, and can be used for the control of technological processes, a security alarm forhigh-risk objects andthe generation of information about danger in order to prevent personnel from entering a workingarea with a potentially hazardous atmosphere.

The use of optical fibers has evolved from an optical transmission waveguide to a more intricated device for bio-chemical sensing. The possibility of measuring target substances with rapid and low-cost tools is still a main challenge in different application fields, from environmental monitoring to the medical-diagnostic sector. In recent decades, plasmonic fiber-optic sensors have gained great interest due to their excellent sensitivity and compactness, allowing the possibility of remote sensing for different target analytes that is real-time and label-free. Such sensors have constantly evolved over time. In this work, a short overview on plasmonic optical fiber sensors is presented, including illustrations that focus on the applications and achievements so far. [ABSTRACT FROM AUTHOR]

Advancement in novel materials for sensing application has revolutionized the field of biological and chemical sensors. Nanomaterials such as nanowires, nanorods, nanobelts, carbon nanotubes, graphene, and MXenes have served as the building blocks in the fabrication of a variety of sensor technologies using both bottom-up and top-down approaches. Nanomaterials continue to be attractive for the development of high−performance sensors due to their extraordinary electrical and physical properties deriving from their 1D and 2D structures. These properties can be tuned through experimentation to achieve the desired sensor characteristics and sensing performance. This review will discuss the advances in sensor fabrication technology that rely on nanomaterials, their synthesis, properties, and applications. The current limitations of these nanomaterials and their prospects as sensing materials are also discussed. [ABSTRACT FROM AUTHOR]

High-sensitivity fiber-optic interferometric refractive index sensors (FIRSs) have been of interest to researchers due to their potential to fabricate specific physical, chemical, and biological sensors. Fabricating interferometers working near the dispersion turning point (DTP) is an effective approach to improve the sensitivity of FIRSs. However, the group effective refractive index (RI) difference approaching 0 and the ratio of the variation of the effective RI difference to the external RI change being −1 cannot be simultaneously realized in low RI sensing, which restricts the further improvement of sensing sensitivity. Here, dual-path Mach-Zehnder interferometers (MZIs) with unequal geometrical path length are proposed for ultrasensitive RI sensing. The dual-path MZIs contain fiber path and sample path of different geometrical lengths to form the optical path difference. The dual-path MZIs can not only show a turning point where the sensing sensitivity tends to be infinite, which is similar to the previously reported DTP, but also get the constant value −1 for the RI response factor, leading to the result that the dips within an over-500-nm band width around the turning point can achieve high sensitivity reaching 105 nm/RIU level or higher. Ultrahigh sensitivity of −1.26 × 106 nm/RIU has been experimentally demonstrated at the RI around 1.35022. The dual-path MZIs proposed here may enlighten new ideas for developing high-sensitivity FIRSs. [ABSTRACT FROM AUTHOR]

This paper presents a new fully integrated CMOS capacitance sensor chip with a wider input dynamic range (IDR) compared to the state-of-the-art, suitable for a variety of life science applications. With the novel differential capacitance to current conversion topology, it achieves an IDR of about seven times higher compared to the previous charge based capacitive measurement (CBCM) circuits and about three times higher compared to the CBCM with cascode current mirrors. It also features a calibration circuitry consisting of an array of switched capacitors, interdigitated electrodes (IDEs) realized on the topmost metal layer, a current-controlled 300 MHz oscillator, and a counter-serializer to create digital output. The proposed sensor, fabricated in AMS 0.35 μm CMOS technology, enables a high-resolution measurement, equal to 416 aF, of physiochemical changes in the IDE with up to 1.27 pF input offset adjustment range (IOAR). With a measurement speed of 15 μs, this sensor is among the fast CMOS capacitive sensors in the literature. In this paper, we demonstrate its functionality and applicability and present the experimental results for monitoring 2 μL evaporating droplets of chemical solvents. By using samples of solvents with different conductivity and relative permittivity, a wide range of capacitance and resistance variations in the sample-IDE interface electric equivalent model can be created. In addition, the evaporating droplet test has inherently fast dynamic changes. Based on the results, our proposed device addresses the challenge of detecting small capacitance changes despite large parasitic elements caused by the ions in the solution or by remnants deposited on the electrode. [ABSTRACT FROM AUTHOR]

This paper proposes a novel readout methodology for improving the performance of Refractive Index (RI) based photonic transducers. Specifically, the authors focus on an optical transducer reported recently in the literature, the so-called Resonant Nano-Pillars (RNPs) transducer. The readout signal for this transducer is usually obtained based on the Wavelength Shift of the Resonant Mode (WSRM), which identifies a single point from the signal, such as the minimum of a resonant mode, whose wavelength shift or intensity value has a correlation with the RI of the media, and, therefore, with the monitored chemical component. This work proposes a novel spectral analysis through Principal Component Analysis (PCA), later inferring the property of interest by regression techniques. To evaluate the performance of the proposal, the authors mimic an agro-food experiment emulating a fermentation process as a proof of concept by measuring the ethanol concentration over time in two liquids: Deionized Water (DIW) and White Wine (WW). The authors compare both methods by inferring the ethanol concentration in the two experiments. As a result, the authors demonstrated experimentally that the proposal significantly outperformed the WSRM method, reporting an improvement of the Limit of Detection (LoD) of up to 140 times. Moreover, this PCA method can be also applied to many other biochemical sensing systems and transducers.

Despite the recent interest in organic electrochemical transistors (OECTs) as chemical and biological sensors, little is known about the role that device architecture and materials parameters play in determining sensor performance. We use numerical modeling to establish design rules in two regimes of operation: We find that for operation as an ion-to-electron converter, the response of OECTs is maximized through the use of a gate electrode that is much larger than the channel or through the use of a nonpolarizable gate electrode. Improving the conductivity of the polymer and using a channel geometry that maximizes channel width and thickness, and minimizes channel length helps increase the response. For operation as an electrochemical sensor, the sensitivity is maximized in OECTs with gate electrodes that are smaller than their channels. The sensitivity can be improved by increasing the charge carrier mobility and the capacitance per unit area of the conducting polymer, and also its ability to be penetrated by ions from the electrolyte. A channel geometry that maximizes channel width and minimizes channel length also improves sensitivity. © 2010 Wiley Periodicals, Inc.

COVID-19 has been declared a global pandemic which has brought the world economy and the society to a standstill. The current emphasis of testing is on detection of genetic material of SARS-CoV-2. Such tests are useful for assessing the current state of a subject: Infected or not infected. In addition to such tests, antibody testing is necessary to stratify the population into three groups: never exposed, infected, and immune. Such a stratification is necessary for safely reopening the society and remobilizing the economy. The aim of this review article is to inform the audience of the current diagnostic and surveillance technologies that are being employed for the detection of SARS-CoV-2 antibodies along with their shortcomings, and to highlight microfluidic sensors and devices that show promise of being commercialized for detection and quantification of SARS-CoV-2 antibodies in low-resource and Point-of-Care (POC) settings. [ABSTRACT FROM AUTHOR]

Water quality assessment has undeniable value for humanity’s well-being. Despite that, most of the existing techniques struggle to measure the quality of running water due to costly infrastructure or large evaluation time. Recently, quality measurement has been demonstrated using spectrum analysis. However, these modern systems need complicated signal processing algorithms and high processor capabilities for decision making, have elaborate optical assemblies and sizable power requirement making them bulky and expensive to operate. Thus, a refined technique with simplified implementation, low cost, and reliable long-time operation is essential to address this challenge. We present, for the first time to our knowledge, a holistic approach towards a simple and rapid method for determination of water quality parameters in flowing water. This is based on the selection of characteristic wavelengths for the parameters considered and usage of narrowband LEDs as the inspection light source. Thereby incorporating the benefits of optical sensing such as electromagnetic immunity, selectivity, sensitivity, etc. The specific wavelengths of 560nm, 860nm, and 635nm have been demonstrated to have a dominant effect due to pH, turbidity, and total dissolved solids (TDS) respectively, from regression analysis. Using only these wavelengths, an evaluation system capable of determining the light absorption after passing through water has been designed and developed. The obtained optical responses are subsequently related to water parameters, specifically pH, TDS, and turbidity. Experiments were performed to evaluate samples and then validate this technique against standard instruments for both flowing and sampled water setups. It is shown from the measurement results that pH, turbidity, and TDS have linear regression coefficients of 0.9773, 0.9617, 0.8271 and 0.9691, 0.9729, 0.76 for flowing and sampled water arrangements, respectively. [ABSTRACT FROM AUTHOR]

Entities throughout the world face the problem of detecting hidden explosives, where human and canine inspection might not be a viable solution. Therefore, it is important to develop fast, reliable, and portable integrated inspection systems by means of automated methods, such as electronic noses. The goal of the work presented here is to develop an accurate, fast and light-weight machine/deep learning classification model to be used in a MOX chemical sensors array (electronic nose), in order to identify explosive substances. For this paper, 140 samples were taken, combining TNT or gunpowder with either soap or toothpaste, or acquiring raw samples of those substances in amounts ranging from 0.1 g to 2 g. For the classification problem, among the different options in machine learning techniques, five models were evaluated. The implemented LSTM version of a LeNet-5 based network, classifies accurately the compounds in 100% of the cases when using only 30 seconds from the 360 obtained by the sensor array per each sample. The results of this work indicate that the proposed LSTM-based deep learning model could be easily implemented into an embedded system. [ABSTRACT FROM AUTHOR]

This paper presents a novel mismatching fused Mach-Zehnder interferometer (MFMZI) for noncontacted steel corrosion monitoring in real time. Without sputtering or contacting any steel film on the surface of the MFMZI, the corrosion rate of the steel bars can be evaluated with ultrasensitivity even when the concentration of the NaCl solution is only 0.05 wt%. Moreover, simulations have been carried out with variations in the water-based solution to understand the sensitivity response as a function of the effective refractive index (RI). The simulation and experimental results reveal that the sensitivity is up to 10372 nm/RIU, and the speeds of the wavelength shift in 0.05 wt%, 0.1 wt% and 0.2 wt% NaCl solutions are 0.08, 0.12 and 0.17 nm/min under the dynamic corrosion process, respectively. [ABSTRACT FROM AUTHOR]

This article proposes a sensor signal processing method for removing baseline drifts in multimodal chemical sensors. Sensitivity and baseline drift are the primary reasons for inaccurate readings from low-cost sensors. The prediction errors from the state-of-the-art multivariate regression algorithms have been high due to the drifts. The response of a sensor is modeled as an autoregressive (AR) process associated with an observation zero-mean Gaussian noise. The parameters of the state-space model are learned using the calibration data. The variance of the Gaussian noise is estimated using an adaptive online method. The AR process equation and the observation equation are used to construct the adaptive Kalman filter. Each sensor response is passed through a separate Kalman filter, and then, a regression technique is used to predict the sensor response. The proposed model is applied to a standard air quality data set to demonstrate its efficacy in removing drifts in sensors. [ABSTRACT FROM AUTHOR]

The detection of ionic variation patterns could be a significant marker for the diagnosis of neurological and other diseases. This paper introduces a novel idea for training chemical sensors to recognise patterns of ionic variations. By using an external voltage signal, a sensor can be trained to output distinct time-series signals depending on the state of the ionic solution. Those sequences can be analysed by a relatively simple readout layer for diagnostic purposes. The idea is demonstrated on a chemical sensor that is sensitive to zinc ions with a simple goal of classifying zinc ionic variations as either stable or varying. The study features both theoretical and experimental results. By extensive numerical simulations, it has been shown that the proposed method works successfully in silico. Distinct time-series signals are found which occur with a high probability under only one class of ionic variations. The related experimental results point in the right direction. [ABSTRACT FROM AUTHOR]

This letter reports a multi-spectral infrared chemical sensor based on a virtual array of bulk acoustic wave resonators with different frequencies. The plasmonic metasurfaces with different patterns on the top surface of resonators provide high IR absorption without degradation of resonating performance. The metasurfaces enhance the frequency responses of the resonant sensor to the specific infrared by about ten times. In a demonstration, four kinds of polymers and their mixtures were detected by the sensor to show its capability for distinguishing unknown compounds. The proposed chemical sensor shows great potential for fast, accurate and portable infrared spectrum microsystems for chemical composition analysis. [ABSTRACT FROM AUTHOR]

Objective: Hemolysis is one of the main reasons for blood sample rejection in clinical laboratories. The scope of this study is to develop a simple, sensitive, and cost-effective method for hemolysis detection in presence of interferants like bilirubin, and lipids in sub-microliter volumes of blood plasma. Methods: Experimental samples were prepared in plasma extracted from whole blood. These samples were typically mixtures of hemoglobin, bilirubin, and lipids of varying concentrations. A multispectral optical setup was devised to probe these samples without any optical filters or moving parts. Results: The hemoglobin content in the samples were measured within the range of 0 mg/dL to 400 mg/dL concentration using <1 μL of detection volume. Detection sensitivity of >90% accuracy and ∼10% coefficient of variation across 27 unknown samples. The optical attenuation path length used was merely ∼150 micrometers. The spectral interference due to overlapping absorption spectrum of bilirubin and scattering spectrum of lipids are resolved using linear matrix algebra algorithms. Conclusion: Hemolysis can lead to spurious measurements of key clinical parameters such as Potassium, Lactate Dehydrogenase, Aspartic Acid Transferase, and other diagnostic biomarkers. Commonly used visual inspection of blood plasma coloration is prone to variability. Description of the sample preparation, calibration and verification of the experimental setup and linear matrix algebra algorithm for analyte interference determination is reported here. Significance: Owing to the sub-microliter detection volume and high sensitivity, the system has realistic potential to be implemented in point of care medical devices that demands such low volumes of clinical specimen. [ABSTRACT FROM AUTHOR]

Coffee and its primary ingredient, caffeine, have been used as solar absorbers and also to increase the thermal stability and efficiency of perovskite solar cells. In this work, we have reported the generation of an optical absorption band in the near-UV region in colloidal coffee solution at extremely alkaline pH values. This generation of absorption band could be explained by the orientation of various induced dipole-dipole interactions arising from varying pH. The said generation is due to narrowing of direct as well as indirect bandgaps from 4 eV→2.8 eV & 3.4 eV→2.5 eV, respectively. Additionally, we have estimated the changes in optical energy storage efficiency, inferring it to be highest for pH 11 having the highest intensity of the generated absorption band (λabs≈360 nm). With these observations and further deductions, the work reported in this paper would be of immense interest to the researchers working in the field of development of novel UV absorbers and also in the development of chemical pH sensors. [ABSTRACT FROM AUTHOR]

This article proposes a sensor signal processing method for removing baseline drifts in multimodal chemical sensors. Sensitivity and baseline drift are the primary reasons for inaccurate readings from low-cost sensors. The prediction errors from the state-of-the-art multivariate regression algorithms have been high due to the drifts. The response of a sensor is modeled as an autoregressive (AR) process associated with an observation zero-mean Gaussian noise. The parameters of the state-space model are learned using the calibration data. The variance of the Gaussian noise is estimated using an adaptive online method. The AR process equation and the observation equation are used to construct the adaptive Kalman filter. Each sensor response is passed through a separate Kalman filter, and then, a regression technique is used to predict the sensor response. The proposed model is applied to a standard air quality data set to demonstrate its efficacy in removing drifts in sensors. [ABSTRACT FROM AUTHOR]

This paper describes the development of an autonomous chemical-sensing aerial robotic system for environmental monitoring in urban and suburban areas. The robot is equipped with a high-performance chemical sensor that identifies and quantifies chemical agents, enabling applications, such as chemical mapping, source localization, and estimation. To enable collision-free monitoring in areas with obstacles, such as in urban and suburban environments where buildings, trees, and other structures pose a challenge, a potential-field algorithm that incorporates past actions is used. A custom-designed ground station for controlling the robot, and planning and visualizing environmental data in real time is described. An empirical method is used to maximize the robot's flight time for improved effective operating range and to provide a safe operating standoff distance. Finally, two outdoor chemical dispersion experiments are conducted to demonstrate the capabilities of the autonomous airborne chemical-sensing system, where results show effective mapping of a propane gas leak. [ABSTRACT FROM AUTHOR]

Applied methods for detecting water impurities in organic solvents, such as Fischer titration, include wayward equipment and toxic reagents. This method is inapplicable for detecting H2O in D2O, but suitable techniques like NMR-, IR-, and mass-spectrometry are costly. We report a low-cost, novel luminescent sensor material based on terbium-europium 3D MOF compound developed for facile, portable, and disposable monitoring of water quantities. Our sensor is able to determine water traces in D2O and aprotic organic solvents. Treating the material to solvent leads to the change in intensities ratio of terbium and europium bands in emission spectra depending of water content and nature of solvent. For D2O calibrating plot $\text{I}_{\mathrm {Eu}}/\text{I}_{\mathrm {Tb}}$ –%H2O is linear whereas for dioxane and acetonitrile the dependence becomes linear in the coordinates $\text{I}_{\mathrm {Eu}}/\text{I}_{\mathrm {Tb}}$ -ln(%H2O). The results reveal the potential application of developed sensor for ratiometric quantitation of H2O admixtures in D2O, organic solvents, transformer oil, etc. [ABSTRACT FROM AUTHOR]

Approaches to provide chip-scale aqueous chemical sensing for environmental and health monitoring via a photonic integrated circuit (PIC) technology are showing promise. To meet future U.S. Army demand, we have investigated waveguide structures compatible with feature sizes offered by modern mass-manufacturing PIC foundries. We have found that wide subwavelength grating (SWG) waveguide structures can maximally interact with an encapsulating analyte capture material with low propagation loss. We describe the analyte/light interaction component of our general integrated photonics chemical detector sensitivity model and use it to compare the effectiveness of waveguide geometries for sensing. The structures we have investigated afford superior detection to strip and slot waveguides. Finally, we introduce a novel tapered SWG waveguide geometry with improved transmission and similar sensitivity to nontapered SWG designs. [ABSTRACT FROM AUTHOR]

This paper proposes a fully reconfigurable universal sensor analog front-end for the Internet of Things era. It is implemented to be able to process different types (R, C, V, and I) of sensor output by using a single input bond pad and a single reconfigurable analog front-end. In addition, a reconfigurable acquisition mode selection method is applied to measure a wide magnitude range of sensor output. Furthermore, the compensation method for the baseline of the sensor is proposed, which can suppress the saturation of the circuit and improve the sensitivity of the sensor output. Also, the correlated double sampling technique is adopted to reduce the low-frequency noise that can affect the sensor output. The proposed system can detect within a relative error of about 1% by using only one input bond pad and analog front-end for the target sensor output range. The proposed system is implemented using TSMC 0.25- $\mu \text{m}$ CMOS process. [ABSTRACT FROM AUTHOR]

The possibility of measuring in real time the different types of analytes present in food is becoming a requirement in food industry. In this context, biosensors are presented as an alternative to traditional analytical methodologies due to their specificity, high sensitivity and ability to work in real time. It has been observed that the behavior of the analysis curves of the biosensors follow a trend that is reproducible among all the measurements and that is specific to the reaction that occurs in the electrochemical cell and the analyte being analyzed. Kinetic reaction modeling is a widely used method to model processes that occur within the sensors, and this leads to the idea that a mathematical approximation can mimic the electrochemical reaction that takes place while the analysis of the sample is ongoing. For this purpose, a novel mathematical model is proposed to approximate the enzymatic reaction within the biosensor in real time, so the output of the measurement can be estimated in advance. The proposed model is based on adjusting an exponential decay model to the response of the biosensors using a nonlinear least-square method to minimize the error. The obtained results show that our proposed approach is capable of reducing about 40% the required measurement time in the sample analysis phase, while keeping the error rate low enough to meet the accuracy standards of the food industry.

We present a D-shaped photonic crystal fiber (PCF) plasmon sensor based on a large-hole self-reference channel for applications in biological and chemical sensing. Both the Plasmon’s fundamental linear-polarization LP01 and high-order LP11 modes are excited at the interface between the analyte and the silver film based on results of the numerical calculation method. We obtained the transmitted spectrum of the guided mode LP01 in the D-shaped PCF. We found that the peak spectral wavelength of the sensor increases when the refractive index of the analyte increases. The spectral sensitivity clearly increases with the silver film’s thickness on the sensor’s platform, although it is unaffected by other variations of the PCF’s geometry. We obtained an optimal spectral sensitivity for the sensor of 3191.43nm/RIU for a silver film thickness of 50nm. [ABSTRACT FROM AUTHOR]

Integrated biochemical sensors based on Mach-Zehnder interferometers (MZIs) rely on the evanescent field detection principle to monitor the phase shift induced by a refractive index change on the surface of the sensing arm, providing a high sensitivity thanks to the long interaction length with the analyte. This paper presents an integrated refractive index and biochemical sensor based on a pair of balanced MZIs realized on silicon-on-insulator. The device includes a thermal phase modulator in one of the branches of each MZI to extract univocally the induced phase change by applying active phase detection based on the phase generated carrier technique. The direct modulation of the MZI results in a simple configuration of the sensor, only requiring a fixed wavelength laser and a photodetector, enabling the possibility of full monolithic integration. The results of refractive index measurements show a detection limit down to 4.88 × 10–7 RIU. Additionally, an immunoassay reports the binding of anti-bovine serum albumin (BSA) to BSA, with anti-BSA concentrations down to 33.33 nM. [ABSTRACT FROM AUTHOR]

Magnetic imagers, which utilize magnetic nanoparticles as labels to realize biodetection assays, hold significant promise for deployment at the point-of-use. Resonance-shift-based sensors can be realized in standard CMOS processes without post-process modifications and offer great sensitivity at low price tags. Unfortunately, CMOS resonant-shift magnetic sensors suffer significant degradation in SNR and long-term stability due to low on-chip inductor quality factors and significant noise introduced from active devices and thermal variations. This makes standard resonant-shift-based imagers undesirable for use in low-signal biodetection assays. Furthermore, and most importantly, the significant long-term drift due to slow-varying noise sources and temperature changes makes these sensors inadequate for bioexperiments which may take timescales on the order of hours to reach completion. In this paper, we propose a transformer-based approach which enables sub-parts-per-million (PPM) signal detection without the need for any thermal compensation. The approach is self-referencing, leading to significant savings in chip area by removing the need for replica reference cells. We analyze the performance of the transformer-based circuit compared to the original second-order system and demonstrate its superiority for rejecting system noise. A proof-of-concept design of a fully integrated $2 \times 2$ CMOS transformer-based magnetic sensor array is presented which achieves reference-free, sub-PPM detection of magnetic signals. The system can be powered and operated completely from a laptop USB interface and each sensing cell can consume less than 3 mW of DC power. Finally, we show the results of an initial DNA biodetection experiment which confirms the capability of the sensor to be used for realistic bioassays. [ABSTRACT FROM AUTHOR]

This paper models the effect of surface stress on the cantilever flexural vibrations based on the balance equations for the transverse forces and bending moments, and seeks solutions within normal mode representation. The purpose is to resolve certain ambiguities and inconsistencies in the existing models, and to present an accurate description. The work is important for interpretation of data from the chemical and biological micro/nano cantilever sensors where the transduction processes are dominated by the changes in surface stress associated with the analyte sorption/binding. Modeling these effects up to second order in the beam slope it is found that the primary effect is an equivalent axial load similar to previous theories with some correction. However, there occurs second order effects associated with the shearing and bending influences of the axial load due to finite beam curvature. In normal sensing conditions with small amplitude oscillations these second order influences are negligibly small. However, in operations under externally imposed static bending and/or large amplitudes the latter may influence changes in resonance frequency by a few percent. [ABSTRACT FROM AUTHOR]

Previous laboratory results have suggested that unheated TiO2 nanowire arrays provide a means to detect trace level concentrations of nitro-group containing compounds in the gas phase with fast response and high chemical selectivity. The detection method is based on the chemiresistive effect, where an electron-deficient compound adsorbed to the surface of an n-type semiconductor causes a surface charge deficit on the semiconductor leading to an increase in its resistance. However, a major issue with this method is that chemiresistive sensors based on TiO2 are also sensitive to the presence of water vapor, and this cross-sensitivity could lead to artifacts for sensors used under environmental conditions. Results are presented here, where thin planar arrays of TiO2 nanowires were tested to determine the sensitivity towards water vapor, along with the detection limits and response times towards several nitro-containing organic molecules as a function of gas-phase water vapor concentration. When water vapor concentrations were carefully controlled to ensure they remain constant throughout the testing cycle, it was found that TiO2 nanowire devices could detect 2,4,6-trinitrotoluene at a concentration as low as a few tens of part per trillion by volume with a response time in the range of $10^{2}$ – $10^{3}$ s, depending on experimental conditions. [ABSTRACT FROM AUTHOR]

RF resonant polymer-coated sensors are a proven effective approach to enhance the sensitivity of polymeric sensing materials. However, the level of sensitivity improvement offered by an RF resonant sensor is directly proportional to the quality factor (Q) of the resonator—the larger the Q-factor, the higher the sensitivity enhancement is. This paper first presents a miniature polymer-based dielectric resonant (DR) sensor design operated at its fundamental mode (TEH) at 24 GHz demonstrating a measured Q-factor of 3820. The sensor is coated with a (per)nigraniline-based conductive sensing material for detections of acetone and isopropanol volatile organic compounds and has a small footprint of $4.5\,\,\text {mm} \times 4.5$ mm. The sensor has demonstrated a low-ppm detection capability for acetone and isopropanol gases with a response onset time less than 15 s. This paper further demonstrates a novel airborne carcinogenic agent sensor array implemented with a single dielectric resonator operating in dual mode (HEH) at 27 GHz. It is functionalized by placing two carcinogen sensing materials—polyhydroxyethyl-methacrylate (PHM) and fluoroalcohol polysiloxanes (FAPS)—at the optimal geometrical locations on the DR, such that the polymers would independently affect the resonant frequencies of the two orthogonal HEH degenerate modes. By monitoring $\Delta f_{0}$ and $\Delta S_{11}$ near $f_{0,\mathrm {HEH1}}$ and $f_{0,\mathrm {HEH2}}$ , both the concentrations and the response signatures of the airborne carcinogenic agents can be detected. The measurement results indicate that the HEH-mode two-sensor array carrying PHM and FAPS is successful in identifying and differentiating two carcinogenic agents—dioxane and benzene—and their respective concentrations. [ABSTRACT FROM AUTHOR]

Chemical sensors play an important role in a variety of civilian and military domains. In these contexts, the ability to accurately and quickly identify chemical agents is of utmost importance. In practice, constraints on physical footprint, power consumption, ease of use, and time required for accurate detection often restrict the utility of sensors, particularly in remote and isolated regions. One solution to address this problem is the engineering of advanced signal processing techniques, which decrease the time required for accurate detection. This allows software to facilitate the construction of hardware that meet stringent power and concept of operations guidelines. In this paper, we propose the Kalman filter as a preprocessing technique applicable to chemical sensor time series data for downstream machine learning. Using data collected from a sensor array of multiple unique polymer-graphene nanoplatelet coated electrodes, we show accurate and early detection of both organophosphates and interferents is improved when the Kalman filter is used as a preprocessing technique. In particular, within two seconds of analyte exposure to the sensor array, classification using Kalman filtered first derivative estimates achieve an error of less than 10%. By comparison, the non-Kalman filtered data set has a classification error rate above 40% within this time. An advantage of our approach is classification does not depend on a set parameter, such as maximum resistance change, or a pre-determined exposure time, and which allows rapid classification immediately after analyte introduction. [ABSTRACT FROM AUTHOR]

Focusing on the interplay between interface chemistry, electrochemistry, and integrated electronics, we show a novel low-cost and flexible biosensing platform for continuous glucose monitoring. The amperometric biosensing system features a planar three-electrode structure on a plastic substrate, and a wireless near-field communication-powered electronic system performing sensor analog front-end, A/D conversion, digital control, and display tasks. The working electrode is made of electropolymerized poly (3,4-ethylenedioxythiophene) film onto a polyethylene terephthalate/gold electrode followed by immobilization of cross-linked glucose oxidase by glutaraldehyde. The advantages offered by such a device, including low-cost materials and instrumentation as well as the good sensitivity of 9.24 \mu \textA/(\mathrm mM \cdot \mathrm cm^2) are promising tools for point-of-care monitoring. It is demonstrated that the devices are good candidates for the development of advanced sensing approaches based on the investigation of the noise produced during operation (fluctuation-enhanced sensing). [ABSTRACT FROM PUBLISHER]

In this study, the design of refractive index sensor with high sensitivity would be provided. This consists of a metal substrate with two metal-insulator-metal waveguide and an array of hexagonal nanoholes. Using the refractive index model obtained for different blood groups A, B, and O, we show that the structure can be used as a sensor to determine a human blood group. We used the array of nanoholes due to the unique optical properties, which leads to nanoscale confinement, high sensitivity to surface, and low propagation losses. Based on the results, resonance wavelength has a linear relationship with the refractive index of a material that is placed inside the nanohole; this feature makes it easy to identify the material. Considering a tradeoff between the transmitted power, structure size, and sensitivity, finite-difference time-domain simulations show that the sensitivity can be as large as 3172 nm per refractive index unit. In general, our plasmonic sensor can promote the sensitivity through the phenomenon of plasmon exciting on the surface of the nanoholes and would have useful applications in the medical field such as determining blood group, hemoglobin, and deoxyribonucleic acid (DNA) quantification. [ABSTRACT FROM AUTHOR]

Intelligent buildings are typically endowed with sensing devices that are able to measure the concentration of specific contaminants in relevant zones. The collected measurements are subsequently processed by intelligent algorithms in order to enable the prompt detection and isolation of contaminant sources inside the building. Unfortunately, in real-world conditions, these sensing devices may suffer from faults affecting the sensors or the embedded electronics. Such faults, generally result in perturbed or missed data in the acquired data-stream, that can induce false alarms (or possibly missed alarms) and compromise the contaminant detection and isolation ability. This paper proposes a three-layer cognitive monitoring system for the detection and isolation of both contaminants and sensor faults in intelligent buildings. The first two layers are designed for the prompt detection of small variations in the concentration of a specific contaminant, while reducing the possible occurrence of false alarms. At the third layer, a cognitive mechanism employing a propagation model for the contaminant, which is based on the airflows between the building zones, allows to isolate the source zone and discriminate between sensor faults and the presence of a contaminant source. The proposed method is validated using a realistic 14-zone building scenario. [ABSTRACT FROM PUBLISHER]

In this paper, we have developed a miniaturized a chemical sensor based on a new nanostructured Co-phthalocyanine (Co(II)Pc-PAA) derivative functionalized Au microelectrodes for perchlorate ClO−4 detection. The morphological properties of the sensitive layer have been characterized by contact angle measurement. The response of the obtained sensor-based CoPc/Au microelectrodes has been investigated by electrochemical impedance spectroscopy measurements. The experimental impedance data of the sensor device were analyzed by an equivalent electrical circuit using a modified Randles model for better understanding the phenomena present at the sensing membrane/electrolyte interface. Therefore, under optimized working conditions in terms of polarization and frequency, best performances have been achieved when compared with those obtained in the literature for Au electrodes-based devices functionalized with the same molecule. The present chemical sensor has provided a lower detection limit (17.3 pM), the lowest achieved until now to our knowledge, with a larger linear range from 1.73 10−11 to 10−1 M. The selectivity of the sensor has been also studied by evaluating the response towards ClO−4 with other interfering anions. The measurement were stable after ten days of the chemical sensor storage at room temperature. This is very promising for environmental application using rapid analyses and low-cost chemical sensors. Perspectives for a potentiometric sensor at higher concentrations were also assessed. [ABSTRACT FROM PUBLISHER]

This work develops the first frequency-dependent small-signal model for graphene electrolyte-gated field-effect transistors (EGFETs). Graphene EGFETs are microfabricated to measure intrinsic voltage gain, frequency response, and to develop a frequency-dependent small-signal model. The transfer function of the graphene EGFET small-signal model is found to contain a unique pole due to a resistive element, which stems from electrolyte gating. Intrinsic voltage gain, cutoff frequency, and transition frequency for the microfabricated graphene EGFETs are approximately 3.1 V/V, 1.9 kHz, and 6.9 kHz, respectively. This work marks a critical step in the development of high-speed chemical and biological sensors using graphene EGFETs. [ABSTRACT FROM AUTHOR]

A process for the fabrication and further characterization of ion-sensitive capacitive sensors is reported. This process is based on a standard 5- \mu \textm complementary metal-oxide–semiconductor process, which has been designed to employ a single metal level. These sensors were fabricated with atomic layer deposited thin films of Al2O3, used as the ion-sensitive dielectric. In addition, these devices were designed with a serial capacitive arrangement in order to provide an additional capacitive response. From the electrochemical characterization, it is shown that the capacitive sensors have a sensitivity in terms of the shift in the flat-band voltage of nearly 30- \text mV \cdot \text pH^-1 , and a sensitivity in the maximum capacitance displacement of 0.6- \text pF \cdot \text pH^-1 . It is shown that with these modifications, this kind of sensors are able to provide a response to the pH of a solution as a change in the maximum capacitance, or as a shift in the flat-band voltage while maintaining a simpler fabrication process in comparison with other technologies. [ABSTRACT FROM PUBLISHER]

The detection of early corrosion is a key issue to mitigate the damage induced by metal corrosion. This paper presents a corrosion sensor for steel based on an iron film-coated optical fiber polarizer. The polarizer is fabricated by sputtering a Fe-C film on a side-polished single mode fiber. The new fabricated polarizer shows highly birefringence, indicated by the difference of the transmission between the TE and TM modes, as well as the extinction ratio (ER). A series of simulations has been performed based on two models. The influences of the parameters of the sensor fabrication, the surrounding media, and film composition on the ER ratio and leakage are studied by the simulations. The accelerated corrosion experiments by immersing the polarizer into NaCl solution show that the polarizers become weakly birefringent after exposure. The results show that the ER and measured optical power decrease gradually during the corrosion process. The proposed polarizer can be used for monitoring the early stage of steel corrosion by building the relationship between the corrosion status and the polarization characteristics. [ABSTRACT FROM PUBLISHER]

High density, vertical well-aligned p-type, n-type, and core-shell p-n homojunction Si nanowires were synthesized on p-Si substrate. The morphology, crystalline structure, composition, and doping ratio of these Si nanowires were investigated via field emission scanning electron microscope, Raman spectra, and X-ray photoelectron spectroscopy. The pH sensors were fabricated with the typical extended-gate field-effect transistor method. The core-shell p-n junction Si nanowires samples had the best performance for pH sensitivity at 68 mV/pH compared with the p-Si NWs and n-Si NWs pH sensors. Furthermore, the pH sensing current of the core-shell p-n junction Si NWs sensor featured rapid response, good repeatability, and stability. The built-in potential Vbi of the core-shell p-n homojunction Si nanowires is ~0.78 V, which improved the pH sensitivity. [ABSTRACT FROM PUBLISHER]

In this paper, a novel technique using an ultra-sensitive optical resonator based on whispering gallery modes (WGM) is proposed to detect the diffusion of organic solvents. The sensor configuration is a micro-cavity made of polymeric material. When the solvent starts to diffuse, the polymer of the cavity starts to swallow that solvent. A swollen elastomer is in fact a solution, except that its mechanical response is now elastic rather than viscous. As solvents fill the network, chains are extended. In turn, that leads to the change of the morphology and mechanical properties of the sensing element. These changes could be measured by tracking the WGM shifts. Several experiments were carried out to measure that swelling force. Ethanol and methanol are used in this paper as candidates to study their driving force of diffusion (concentration gradient) on the cavity. Additionally, this sensing design can be used for biological sensing application. Breath diagnosis can use this configuration in diabetes diagnosis since a solvent like acetone concentration in human breath leads to a quick, convenient, accurate, and painless breath diagnosis of diabetes. The optical resonator results are verified through two different analyses: theoretical and experimental modeling. These micro-optical cavities have been examined using preliminary experiments to fully investigate their response and to verify the numerical analysis. Results show that the proposed sensor yields sensitivity for the driving force of diffusion (concentration gradient) (9.405 _ 1013 pm/N) with a measurement precision of ~3.6 fN. [ABSTRACT FROM AUTHOR]

Over the past decade, electrical detection of chemical and biological species using novel nanostructure-based devices has attracted significant attention for chemical, genomics, biomedical diagnostics, and drug discovery applications. The use of nanostructured devices in chemical/biological sensors in place of conventional sensing technologies has advantages of high sensitivity, low decreased energy consumption and potentially highly miniaturized integration. Owing to their particular structure, excellent electrical properties and high chemical stability, carbon nanotube and graphene based electrical devices have been widely developed for high performance label-free chemical/biological sensors. Here, we review the latest developments of carbon nanostructure-based transistor sensors in ultrasensitive detection of chemical/biological entities, such as poisonous gases, nucleic acids, proteins and cells.

Since they were discovered in 1991 [2], CARBON nanotubes (CNTs) have attracted enormous attention because of their remarkable properties [1], such as high electrical conductivity, ultrasmall diameter, and large aspect ratio. In addition, CNTs exhibit significant electromechanical properties [3] that could be useful in applications for piezoresistive-type sensors such as strain gauges, pressure sensors, chemical and biological sensors, microelectronic devices, and structural condition monitoring through strain sensing [4]. In addition to the application of a single CNT in various nanoelectromechanical applications, CNT researchers have gradually moved toward potential applications of CNTs as filler candidates in various types of multifunctional material systems, representing a new direction with broad applications [5], [6]. [ABSTRACT FROM PUBLISHER]