Use Of Sensor Arrays Research Articles

Explosives Detection Using Octanethiol Gold Nanoparticle Inkjet Printed Devices

This study focuses on implementing 1-octanethiol gold nanoparticles (OT-AuNPs) as chemiresistive sensors and comparing fabrication by inkjet-printing with conventional drop-casting to detect volatile organic compounds (VOCs) and explosives including HMTD, PETN, KClO3, TATP, RDX, TNT, and UN. Inkjet-printing technology potentially offers more controlled deposition of OT-AuNPs and more uniform sensor properties compared to a drop-casting process. Using inkjet-printing, we found that a minimum of 600 OT-AuNPs printed layers with 2.4[Formula: see text]pL drop volume, 9 drops per layer, and 60[Formula: see text][Formula: see text]m drop spacing was sufficient to reduce chemiresistor device baseline resistances to around [Formula: see text] and obtain more consistent responses. By contrast, 12[Formula: see text][Formula: see text]L OT-AuNPs drop-casting yielded device resistances spread over a range of [Formula: see text] due to uneven deposition. For inkjet-printed devices, higher response magnitudes with lower variability were achieved for explosive vapor detection whereas a larger spread was observed for drop casting. The improved uniformity of baseline resistances and sensor responses indicates inkjet-printed devices were more reproducible and repeatable than drop-casting. In addition, inkjet-printing consumes lower amounts of OT-AuNPs for material and cost savings. The results demonstrate that inkjet-printed devices are promising for use in sensor arrays to fabricate electronic noses for VOCs and explosives detection.

Nanozyme colorimetric sensor array based on monatomic cobalt for the discrimination of sulfur-containing metal salts

The identification of sulfur-containing metal salts (SCMs) is of great interest because they play an important role in many biological processes and diseases. Here, we constructed a ternary channel colorimetric sensor array to detect multiple SCMs simultaneously, relying on monatomic Co embedded in nitrogen-doped graphene nanozyme (CoN4-G). Due to the unique structure, CoN4-G exhibits activity similar to native oxidases, capable of catalysing directly the oxidization of 3,3′,5,5′-tetramethylbenzidine (TMB) by O2 molecules independent of H2O2. Density functional theory (DFT) calculations suggest that CoN4-G has no potential barrier in the whole reaction route, thus presenting higher oxidase-like catalytic activity. Based on different degrees of TMB oxidation, different colorimetric response changes are obtained as "fingerprints" on the sensor array. The sensor array can discriminate different concentrations of unitary, binary, ternary, and quaternary SCMs and has been successfully applied to detect six real samples (soil, milk, red wine and egg white). To advance the field detection of the above four types of SCMs, we creatively propose a smartphone-based autonomous detection platform with a linear range of 1.6–320 μM and a limit of detection of 0.0778–0.218 μM, which demonstrates the potential use of sensor arrays in the application of disease diagnosis and food and environment monitoring.

Optical spatial filtering with plasmonic directional image sensors.

Photonics provides a promising approach for image processing by spatial filtering, with the advantage of faster speeds and lower power consumption compared to electronic digital solutions. However, traditional optical spatial filters suffer from bulky form factors that limit their portability. Here we present a new approach based on pixel arrays of plasmonic directional image sensors, designed to selectively detect light incident along a small, geometrically tunable set of directions. The resulting imaging systems can function as optical spatial filters without any external filtering elements, leading to extreme size miniaturization. Furthermore, they offer the distinct capability to perform multiple filtering operations at the same time, through the use of sensor arrays partitioned into blocks of adjacent pixels with different angular responses. To establish the image processing capabilities of these devices, we present a rigorous theoretical model of their filter transfer function under both coherent and incoherent illumination. Next, we use the measured angle-resolved responsivity of prototype devices to demonstrate two examples of relevant functionalities: (1) the visualization of otherwise invisible phase objects and (2) spatial differentiation with incoherent light. These results are significant for a multitude of imaging applications ranging from microscopy in biomedicine to object recognition for computer vision.

An FPGA-Based Machine Learning Tool for In-Situ Food Quality Tracking Using Sensor Fusion.

The continuous development of more accurate and selective bio- and chemo-sensors has led to a growing use of sensor arrays in different fields, such as health monitoring, cell culture analysis, bio-signals processing, or food quality tracking. The analysis and information extraction from the amount of data provided by these sensor arrays is possible based on Machine Learning techniques applied to sensor fusion. However, most of these computing solutions are implemented on costly and bulky computers, limiting its use in in-situ scenarios outside complex laboratory facilities. This work presents the application of machine learning techniques in food quality assessment using a single Field Programmable Gate Array (FPGA) chip. The characteristics of low-cost, low power consumption as well as low-size allow the application of the proposed solution even in space constrained places, as in food manufacturing chains. As an example, the proposed system is tested on an e-nose developed for beef classification and microbial population prediction.

Selectivity and Cross-Sensitivity of Transfer-Free Fabricated Nanocrystalline Graphene Field-Effect Gas Sensors

In the course of an increasing awareness for the protection of public health a higher demand for environmental gas sensors, especially for the detection of volatile organic compounds and toxic gases, has been noted. Reasonably-priced devices to cover this demand can be solid-state gas sensors that can be easily fabricated and scaled using planar processing. Furthermore, an appropriate choice of materials may enable the possibility of monolithic integration within silicon CMOS circuitry thus providing the chance of co-integrating read-out and signal processing electronics on the same chip. As a two-dimensional carbon nanomaterial graphene shows a high surface-to-volume ratio and promising electronic properties for the detection of gaseous species. Detection capabilities down to a single molecule have been demonstrated by Schedin et al. [1], using a pristine graphene flake made from mechanical cleavage of highly ordered pyrolytic graphite. In this contribution we port on a novel method for graphene-based sensor fabrication. By means of a CMOS compatible method we have fabricated hundreds of transfer-free nanocrystalline graphene field-effect transistors (ncGFETs) on silicon dioxide [2], which can be used for detection of gaseous species. Under application of a HP4156A semiconductor parameter analyzer the gaseous sensitivity of our ncGFETs is electrically characterized in terms of backgate FET input characteristics as well as in a resistive configuration. For the resistive configuration the backgate bias has been fixed near the charge neutrality point of our nanocrystalline graphene devices at VBG = 0V. All measurements were done using our self-constructed vacuum probing station that can be systematically flooded with calibrated gas mixtures. The gas concentration is then derived from the vacuum pressure using the ideal gas law. Sensitivities of our ncGFETs to different volume concentrations of various toxic gases including ammonia (NH3), nitrogen dioxide (NO2), and carbon monoxide (CO) will be presented. E.g. for devices heated to 425K a sensitivity S of roughly 80% is S = (G-G0)/G0 achieved for 4 parts-per-million-volume (ppmv) of ammonia whereat NO2 already shows a sensitivity of 100% for a concentration of 4 parts-per-trillion-volume (pptv = 10-6 ppmv). The higher sensitivity of our ncGFETs compared to other graphene devices is attributed to modifications of grain boundary potential barriers, which is the dominating mechanism in e.g. SnO2-based Taguchi-type sensors [3]. Furthermore, the influence of water vapor (H2O (g)) on our devices is discussed. Nevertheless, the cross-sensitivity of Taguchi-type sensors, like our ncGFETs, remains a problem. Speciation of gas molecules is feasible by the use of sensor arrays consisting of devices with different sensitivities and electronic characteristics towards different gas species. Therefore, in order to modify the sensitivities towards the different gas species of our ncGFETs towards the different gas species we have characterized the sensitivity and responsivity at various temperatures. Furthermore, during exposure to the different gases the analysis of the backgate ncGFET input characteristics shows shifts of the charge neutrality point, as well as changes in the hysteresis of our devices. A novel method to selectively discriminate between various gaseous species, which is based on the analysis of the hysteresis in the ncGFETs will be presented and discussed. [1]F. Schedin, A. K. Geim, S. V. Morozov, E. W. Hill, P. Blake, M. I. Katsnelson and K. S. Novoselov, Nat Mater, 6, 652 (2007). [2] D. Noll and U. Schwalke, 2017 12th Ieee International Conference on Design & Technology of Integrated Systems in Nanoscale Era (Dtis 2017) (2017). [3] R. K. Srivastava, P. Lal, R. Dwivedi and S. K. Srivastava, Sensor Actuat B-Chem, 21, 213 (1994). Figure 1

Is determination of the hip rotation center during computer-assisted surgery influenced by the pinless femoral sensor attachment method? An in vitro preliminary study comparing osseous pin fixation

IntroductionComputer-assisted surgery improves the positioning of hip prostheses but requires use of transosseous pins requiring a complementary approach exposing the patient to rare but at times serious complications. The use of sensor arrays attached to the skin could advantageously replace pins provided that comparable results are obtained, but their validity has not yet been assessed. We conducted a prospective in vitro study to: measure the possible error of a cutaneous versus transosseous fixation to determine the hip rotation center (HRC) position and determine the inter- and intraobserver reproducibility of the cutaneous versus the transosseous fixation. HypothesisUse of cutaneous sensor arrays while recording the HRC is sufficiently reliable for its calculation algorithm to provide measurement accuracy within 5mm. Materials and methodsA rigid array attached with either a silicone strap or an adhesive were compared to a transosseous array. Four series of 96 HRC measurements were collected by four operators on two cadavers, half with an array attached with a strap and half with an adhesive. The results were compared to those obtained by a sensor attached with transosseous pins. ResultsOn condition that the hip-knee is mobilized in extension, a sensor array attached with an adhesive gives results with comparable accuracy (standard deviation [SD]: 2.89mm [1.9–4.8]) to the results obtained with a transosseous fixation (SD: 1.2mm [0.9–1.6]), with no significant inter- or intraobserver variation (0.97<ICC<0.99). If the knee was flexed, accuracy was within more than 1cm, or twice the predetermined limit. Only the adhesive array gave measurements systematically within the limits established with the data spread (8.7%) close to that obtained with a pin (6%). DiscussionAn adhesive array seems to be a reliable alternative to transosseous pins to evaluate HRC and provides a three-dimensional landmark, indispensable to total hip arthroplasty navigation. These preliminary results confirm our hypothesis but should be validated in vivo. Level of evidenceLevel III, comparative prospective in vitro study.

Filtering Wind in Infrasound Data by Non-Negative Matrix Factorization

Infrasonic data at volcanoes have been increasingly analyzed to get information about eruptive activity. Wind noise is an important problem, which cannot be solved using more classical seismological techniques such as deconvolution (Robinson, 1967), as the interaction between wind and original signal cannot be modeled simply as a convolution. The problem has therefore been tackled with a wide spectrum of original approaches, from the use of sensor arrays (Ripepe and Marchetti, 2002; Matoza et al. , 2011), to spatial filters consisting of a network of pipes (Hedlin et al. , 2003) or the location of the sensors in a densely forested area (Garces et al. , 2003). For arrays of infrasonic sensors, a pure state data‐adaptive polarization filter has been proposed by Olson (1982), dependent upon a measure of the multivariate coherence. This cannot, however, be applied to single sensor time series, whereas for monitoring purposes the availability of a single sensor very close to the crater is very important, as it was demonstrated, for example, in the 2011 Shinmoe‐dake eruption. To enhance the recognition of infrasound signals of small amplitude produced during that eruption, Ichihara et al. (2012) proposed a method for exploiting the use of a co‐located seismometer through the cross‐correlation function with seismic data. The appearance of characteristic patterns indicates an infrasound signal possibly originated at the volcanic vent. An alternative strategy was adopted in Cannata et al. (2013) to detect explosive activity of Mt. Etna; in that case the method is based on joint analysis of seismic and infrasonic data by wavelet transform coherence. Here, we apply the wind noise reduction procedure recently proposed by Cabras et al. (2014) for seismic data, based on non‐negative matrix factorization (NMF) with sparse coding (SC; Hoyer, …

Design and analysis of nanowire sensor array for prostate cancer detection

Prostate cancer is one of the major cancer affecting men in India. After lung cancer, prostate cancer has caused large number of deaths in India. Nanowire is the biosensor used for detection of cancer. In this paper, we present a design of nanowire array sensor for prostate cancer detection. A sensor array of 8 × 8 elements is designed to capture the PSA present in the blood that helps in detecting the presence of prostate cancer. An experimental setup has been developed using the biosensors lab from Nanohub.org. Based on the experimental setup the nanowire sensor is characterised for PSA detection. The sensitivity of detection is increased by use of sensor array.

Gas sensing properties of electrically conductive Cu(I) compounds at elevated temperatures

Changes in the electrical conductance at 240 °C of a number of copper(I) compounds including CuI, CuBr, Cu 2Te, Cu 12Sb 4S 13, (CuI) 2P 14, and of NiO were measured following the exposure to the gases ammonia, nitrogen dioxide, nitrous oxide, carbon monoxide, carbon dioxide, and propane. Analytical sensitivity and kinetic parameters were compared quantitatively. The high diversity of sensitivity patterns makes these compounds promising candidates for use in sensor arrays. Principal component analysis of the data obtained with a virtual sensor array enabled highly selective sensing of five of the six analytes studied using only two principle components. Activation energies of the charge transport in the materials were determined.

Immobilization of cholesterol oxidase in LbL films and detection of cholesterol using ac measurements

The preserved activity of immobilized biomolecules in layer-by-layer (LbL) films can be exploited in various applications, including biosensing. In this study, cholesterol oxidase (COX) layers were alternated with layers of poly(allylamine hydrochloride) (PAH) in LbL films whose morphology was investigated with atomic force microscopy (AFM). The adsorption kinetics of COX layers comprised two regimes, a fast, first-order kinetics process followed by a slow process fitted with a Johnson–Mehl–Avrami (JMA) function, with exponent ~ 2 characteristic of aggregates growing as disks. The concept based on the use of sensor arrays to increase sensitivity, widely employed in electronic tongues, was extended to biosensing with impedance spectroscopy measurements. Using three sensing units, made of LbL films of PAH/COX and PAH/PVS (polyvinyl sulfonic acid) and a bare gold interdigitated electrode, we were able to detect cholesterol in aqueous solutions down to the 10 − 6 M level. This high sensitivity is attributed to the molecular-recognition interaction between COX and cholesterol, and opens the way for clinical tests to be made with low cost, fast experimental procedures.

Pattern‐Based Peptide Recognition

AbstractChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 200 leading journals. To access a ChemInform Abstract, please click on HTML or PDF.

Pattern‐Based Peptide Recognition

Nature's use of sensor arrays in the mammalian olfactory and gustatory systems has encouraged supramolecular chemists to take a new approach to molecular recognition. Pattern-based recognition involves the use of sensor arrays to create fingerprints for analytes. The use of sensing arrays has paved the way for systems capable of identifying biological analytes that would have been difficult targets using the traditional "lock-and-key" approach to sensor design.

Plasma wave source location using CLUSTER as a spherical wave telescope

The use of sensor arrays in space opens up the possibility to investigate the source location of plasma waves. In order to do so, we generalize the wave telescope technique to use spherical waves instead of plane waves. The new tool determines the center of the wavefronts locally measured by the sensor array. This virtual source can be related with the position of the source generating the detected waves provided the wave propagation mode and medium properties are known. Moreover, the motion of the source region can be derived, as well as its basic geometrical characteristics. In this work we give the theoretical background for the new tool and examples of location analysis based on synthetic data. An example based on CLUSTER magnetic field data in the dayside magnetosheath reveals a virtual source region elongated in the magnetic field direction, moving with the plasma flow in the vicinity of the spacecraft configuration.

The Recognition of Growth Conditions and Metabolic Type of Plants by a Potentiometric Electronic Tongue

AbstractThe application of a potentiometric electronic tongue for the recognition and classification of plant samples is presented. Homogenates from the leaves of various plants subtypes (maize and guinea grass) were measured with the use of sensor array based on ion‐selective and partially selective electrodes. It was found that this device is capable of recognizing with high correctness, the type of plant metabolism (distinguishing between two types of cereals) and the factors affecting nutritional values of plants such as cultivation time and light intensity during growth. The obtained results led to the conclusion that the presented system can be used for the monitoring of crops and estimation of the quality of plants.

Inductive and capacitive array imaging of buried objects

Despite ongoing research and development efforts, landmine and unexploded ordnance infestation continues to be a problem. Remediation efforts typically utilise inexpensive hand-held metal detectors that rely on the principle of electromagnetic induction. While these devices often detect all relevant metal objects, they generally cannot discriminate between harmful objects and harmless clutter. False indications continue to far outnumber verified detections. One promising method for improving the discrimination between harmful and harmless objects is the use of sensor arrays that provide images of hidden objects and complementary information about the buried object from a variety of angles. This paper will review the progress of high-resolution inductive and capacitive sensing array development for buried object detection. These sensor arrays use unique designs incorporating a single drive with multiple sense elements. The drive creates a shaped magnetic or electric field pattern that concentrates the field energy into longer wavelength spatial modes with 'focused' penetration into the ground. Images obtained from scans over buried objects provide a basis for spatial filtering and signal processing while multiple sensor arrays placed at different positions within the drive provide different 'views' of buried objects and clutter. Model-based grid measurement methods will also be reviewed as a real-time method for multiple property measurements, and real-time data analysis/image generation.

Quantification of Quaternary Mixtures of Low Alcohols in Water: Temporal-Resolved Measurements with Microporous and Hyperbranched Polymer Sensors for Reduction of Sensor Number

The focus of this study is the quantification of multianalyte mixtures in water by the use of sensor arrays based on polymer layers. Reflectometric interference spectroscopy is used as a optical sensor system for temporal-resolved measurements of the interaction kinetics of analytes in water with the polymer layers. The principles and widespread possibilities of this approach are demonstrated using the quantification of quaternary aqueous mixtures of low alcohols from methanol up to 1-butanol. The sensitive layers consist of two hyperbranched polyesters and one microporous polyimide. Different time-dependent sensor signals are evaluated by artificial neural networks. Because the kinetics of sorption and desorption of the analytes differ significantly, the number of sensors needed for a quantification of analytes in mixtures can be reduced. A feature extraction allows identification of the most important differences of kinetic patterns of the analytes and allows improvement of the multivariate calibration. It is shown that a quantification of quaternary mixtures of methanol, ethanol, 1-propanol, and 1-butanol is possible on the basis of only two polymer sensors.

위상변화를 이용한 표면탄성파 가스센서

This paper describes the development of a surface acoustic wave gas sensor that is designed to detect volatile gas by monitering phase change of output signal as a function of time. The sensor consists of SAW oscillators with a center frequency of 100 MHz fabricated on <TEX>$128^{\circ}$</TEX> Y-Z <TEX>$LiNbO_{3}$</TEX> substrates. Experimental results, which show the phase change of output signal under the absorption of volatile gas onto sensors, are presented. The proposed sensor has the properties of high sensitivity compare to the conventional SAW gas sensor and chemical selectivity. Thus, it is thought these results are applicable for use in sensor array of an high performance electronic nose system.

Direct optical sensors: principles and selected applications

In the field of bio and chemosensors a large number of detection principles has been published within the last decade. These detection principles are based either on the observation of fluorescence-labelled systems or on direct optical detection in the heterogeneous phase. Direct optical detection can be measured by remission (absorption of reflected radiation, opt(r)odes), by measuring micro-refractivity, or measuring interference. In the last case either Mach-Zehnder interferometers or measurement of changes in the physical thickness of the layer (measuring micro-reflectivity) caused, e.g., by swelling effects in polymers (due to interaction with analytes) or in bioassays (due to affinity reactions) also play an important role. Here, an overview of methods of microrefractometric and microreflectometric principles is given and benefits and drawbacks of the various approaches are demonstrated using samples from the chemo and biosensor field. The quality of sensors does not just depend on transduction principles but on the total sensor system defined by this transduction, the sensitive layer, data acquisition electronics, and evaluation software. The intention of this article is, therefore, to demonstrate the essentials of the interaction of these parts within the system, and the focus is on optical sensing using planar transducers, because fibre optical sensors have been reviewed in this journal only recently. Lack of selectivity of chemosensors can be compensated either by the use of sensor arrays or by evaluating time-resolved measurements of analyte/sensitive layer interaction. In both cases chemometrics enables the quantification of analyte mixtures. These data-processing methods have also been successfully applied to antibody/antigen interactions even using cross-reactive antibodies. Because miniaturisation and parallelisation are essential approaches in recent years, some aspects and current trends, especially for bio-applications, will be discussed. Miniaturisation is especially well covered in the literature.

Spurious free dynamic range for a digitizing array

The paper addresses the problem of improving the spurious free dynamic range (SFDR) for digitization by use of sensor arrays. Nonlinearities in the analog-to-digital conversion process give rise to spurious signals (harmonics and intermodulation products) that limit the overall SFDR of the digitization process. When the signal of interest arises from a sensor, such as an antenna or hydrophone, the paper addresses the question of whether array processing (i.e., use of multiple sensors) can improve the resulting SFDR at the beamformer output. The paper argues that significant improvements can be obtained using linear, or more effectively, optimal (minimum variance distortionless response) beamforming.

The use of sensor arrays for environmental monitoring: interests and limitations.

Continuous, in situ monitoring of air, water and land quality is fundamental to most environmental applications. Low cost and non-invasive chemical sensor arrays provide a suitable technique for in situ monitoring. Their ability and performance under realistic conditions is discussed in this paper. Published studies report promising results despite a number of limitations that are associated with both the technology itself and its application in ever changing ambient conditions. Early investigations include the analysis of single substances as well as odour and wastewater organic load monitoring. Reported applications typically highlight the sensitivity of the currently available sensors to changes in temperature, humidity and flow rate. Two types of approaches are recommended to deal with these effects: either working under fixed experimental conditions or measuring the external parameters to numerically compensate for their change. The main challenge associated with the use of non-specific sensor arrays lies in establishing a relationship between the measured multivariate signals and the standards metrics that are traditionally used for quality assessment of gas mixtures. For instance, odour monitoring requires calibration against olfactometric measurements while investigations of wastewater samples still need to be correlated with organic pollution parameters such as BOD, COD or TOC. On the other hand, results obtained in the field have demonstrated how sensor arrays can be readily used as simple alarm devices or as early warning systems based on a general air/water quality index.