Evaluation of chemometric techniques for the identification and quantification of solvent mixtures using a thin-film metal oxide sensor array

An evaluation was made of suitable chemometric techniques that can be used in both the selection of suitable sensors for a sensor array and the subsequent identification and quantification of analytes using such a device. Data fro a thin-film tin oxide-based gas sensor were obtained for a range of analytes, both pure and in mixtures and analysed using several chemometric techniques, including principal component analysis, cluster analysis and partial least squares. It was shown that the array produced a characteristic response pattern for the analytes, and this was then used for the identification of ethyl acetate, acetone, ethanol and pentane, and the determination of ethanol in various mixtures. The chemometric techniques were not only used to identify and quantify components in the solvent mixture but also indicated which of the array elements were acting independently and the level of interaction which was occurring. The results obtained describe a chemometric and fabrication protocol for sensor array design.     

A single cataluminescence sensor based on spectral array and its use in the identification of vinegars

The discrimination of complex mixtures, especially those with very similar compositions, remains a challenging part of chemical analysis. In this paper, a single cataluminescence (CTL) sensor constructed using MgO nanomaterials in a closed reaction cell (CRC) was used to identify vinegars. It may provide an archetype of this type of highly multicomponent system. By scanning the CTL spectra, which were distributed in 15 wavelengths during the reaction period, the spectral array patterns of the vinegars were obtained. These functioned as their fingerprints. The CTL signals of the array were then normalized and identified through linear discrimination analysis (LDA). Nine types and eight brands of vinegars and an additional series of artificial samples were tested; the new technique was found to distinguish between them very well. This single sensor demonstrated excellent promise for analysis of complex mixtures in real-world applications and may provide a novel method for identifying very similar complex analytes.     

Colorimetric molecularly imprinted polymer sensor array using dye displacement

A colorimetric sensor array composed of seven molecularly imprinted polymers was shown to accurately identify seven different aromatic amines. The response patterns were systematically classified using linear discriminant analysis with 94% classification accuracy. Analyses of the response patterns of the analytes to the imprinted polymer array suggest that the different selectivity patterns, although subtle, appear to arise from the imprinting process. The molecular imprinting process enabled the rapid preparation of the polymers in the array from ethylene glycol dimethacrylate and methacrylic acid (80:20) in the presence of six different template molecules plus a blank nonimprinted polymer. The response of the imprinted polymer array was coupled to a colorimetric response, using a dye displacement strategy. A benzofurazan dye was selected and shown to give an accurate measure of the binding properties of the imprinted polymer array to all seven analytes. The colorimetric response also enabled the inclusion of analytes that are not spectroscopically active and were not among the original analytes that were used as template molecules. This broadens the potential utility of the imprinted polymer sensor array strategy to a wider range of analytes and applications.     

Revealing the properties of oils from their dissolved hydrocarbon compounds in water with an integrated sensor array system

This paper presents a system and method developed to identify a source oil's characteristic properties by testing the oil's dissolved components in water. Through close examination of the oil dissolution process in water, we hypothesise that when oil is in contact with water, the resulting oil-water extract, a complex hydrocarbon mixture, carries the signature property information of the parent oil. If the dominating differences in compositions between such extracts of different oils can be identified, this information could guide the selection of various sensors, capable of capturing such chemical variations. When used as an array, such a sensor system can be used to determine parent oil information from the oil-water extract. To test this hypothesis, 22 oils' water extracts were prepared and selected dominant hydrocarbons analyzed with Gas Chromatography-Mass Spectrometry (GC-MS); the subsequent Principal Component Analysis (PCA) indicates that the major difference between the extract solutions is the relative concentration between the volatile mono-aromatics and fluorescent polyaromatics. An integrated sensor array system that is composed of 3 volatile hydrocarbon sensors and 2 polyaromatic hydrocarbon sensors was built accordingly to capture the major and subtle differences of these extracts. It was tested by exposure to a total of 110 water extract solutions diluted from the 22 extracts. The sensor response data collected from the testing were processed with two multivariate analysis tools to reveal information retained in the response patterns of the arrayed sensors: by conducting PCA, we were able to demonstrate the ability to qualitatively identify and distinguish different oil samples from their sensor array response patterns. When a supervised PCA, Linear Discriminate Analysis (LDA), was applied, even quantitative classification can be achieved: the multivariate model generated from the LDA achieved 89.7% of successful classification of the type of the oil samples. By grouping the samples based on the level of viscosity and density we were able to reveal the correlation between the oil extracts' sensor array responses and their original oils' feature properties. The equipment and method developed in this study have promising potential to be readily applied in field studies and marine surveys for oil exploration or oil spill monitoring.     

Selective recognition and discrimination of water‐soluble azo dyes by a seven‐channel molecularly imprinted polymer sensor array

A seven‐channel molecularly imprinted polymer sensor array was prepared and characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, UV‐Vis spectroscopy, and nitrogen physisorption studies. The results revealed that the imprinted polymers have distinct‐binding affinities from those of structurally similar azo dyes. Analysis of the UV‐Vis spectral response patterns of the seven dye analytes against the imprinted polymer array suggested that the different selectivity patterns of the array were closely connected to the imprinting process. To evaluate the effectiveness of the array format, the binding of a series of analytes was individually measured for each of the seven polymers, made with different templates (including one control polymer synthesized without the use of a template). The response patterns of the array to the selected azo dyes were processed by canonical discriminant analysis. The results showed that the molecularly imprinted array was able to discriminate each analyte with 100% accuracy. Moreover, the azo dyes in two real samples, spiked chrysoidin in smoked bean curd extract and Fanta lime soda (containing tartrazine), were successfully classified by the array.     

Cross‐Reactive Sensor Arrays for the Detection of Peptides in Aqueous Solution by Fluorescence Spectroscopy

A simple but powerful method for the sensing of peptides in aqueous solution has been developed. The transition‐metal complexes [PdCl₂(en)], [{RhCl₂Cp*}₂], and [{RuCl₂(p‐cymene)}₂] were combined with six different fluorescent dyes to build a cross‐reactive sensor array. The fluorescence response of the individual sensor units was based on competitive complexation reactions between the peptide analytes and the fluorescent dyes. The collective response of the sensor array in a time‐resolved fashion was used as an input for multivariate analyses. A sensor array comprised of only six metal–dye combinations was able to differentiate ten different dipeptides in buffered aqueous solution at a concentration of 50 μM . Furthermore, the cross‐reactive sensor could be used to obtain information about the identity and the quantity of the pharmacologically interesting dipeptides carnosine and homocarnosine in a complex biological matrix, such as deproteinized human blood serum. The sensor array was also able to sense longer peptides, which was demonstrated by differentiating mixtures of the nonapeptide bradykinin and the decapeptide kallidin.     

Data analysis for electronic nose systems

Electronic noses (e-noses) employ an array of chemical gas sensors and have been widely used for the analysis of volatile organic compounds. Pattern recognition provides a higher degree of selectivity and reversibility to the systems leading to an extensive range of applications. These range from the food and medical industry to environmental monitoring and process control. Many types of data analysis techniques have been used on the data produced. This review covers aspects of analysis from data normalisation methods to pattern recognition and classification techniques. An overview of data visualisation such as non-linear mapping and multivariate statistical techniques is given. Focus is then on the use of artificial intelligence techniques such as neural networks and fuzzy logic for classification and genetic algorithms for feature (sensor) selection. Application areas are covered with examples of the types of systems and analysis methods currently in use. Future trends in the analysis of sensor array data are discussed.     

Chemical vapor discrimination using a compact and low-power array of piezoresistive microcantilevers

A compact and low-power microcantilever-based sensor array has been developed and used to detect various chemical vapor analytes. In contrast to earlier micro-electro-mechanical systems (MEMS) array sensors, this device uses the static deflection of piezoresistive cantilevers due to the swelling of glassy polyolefin coatings during sorption of chemical vapors. To maximize the sensor response to a variety of chemical analytes, the polymers are selected based on their Hildebrand solubility parameters to span a wide range of chemical properties. We utilize a novel microcontact spotting method to reproducibly coat a single side of each cantilever in the array with the polymers. To demonstrate the utility of the sensor array we have reproducibly detected 11 chemical vapors, representing a breadth of chemical properties, in real time and over a wide range of vapor concentrations. We also report the detection of the chemical warfare agents (CWAs) VX and sulfur mustard (HD), representing the first published report of CWA vapor detection by a polymer-based, cantilever sensor array. Comparisons of the theoretical polymer/vapor partition coefficient to the experimental cantilever deflection responses show that, while general trends can be reasonably predicted, a simple linear relationship does not exist.     

多元线性模型计算基于荧光猝灭原理的膜传感器对分析物的响应参数

根据基于荧光猝灭原理的化学传感膜的结构特征和发光机理,推导并提出量化作用于膜传感器的多种荧光猝灭因素的多元线性模型.结合三杯法,该模型可简便地求出反映不同荧光猝灭机理的特征参数.通过建立的数学模型,测定并计算了芘丁酸膜传感器对应于呋喃妥因等23种药物多种荧光猝灭因素的响应数据和响应参数.结果表明,传感膜对分析物的响应特征往往能得到主要猝灭因素响应模型的近似反映,这为基于荧光猝灭原理的化学传感器定量分析模型的建立提供了可借鉴的思路和方法.     

Nano‐Graphene Oxide Based Multichannel Sensor Arrays towards Sensing of Protein Mixtures

Optical array‐based sensors are attractive candidates for the detection of various bio‐analytes due to their convenient fabrication and measurements. For array‐based sensors, multichannel arrays are more advantageous and used frequently in many electronic sensors. But most reported optically array based sensors are constructed on a single channel array. This difficulty is mainly instigated from the overlap in optical responses. In this report we have used nano‐graphene oxide (nGO) and suitable fluorophores as sensor elements to construct a multichannel sensor array for the detection of protein analytes. By using the optimized multichannel array we are able to detect different proteins and mixtures of proteins with 100 % classification accuracy at sub‐nanomolar concentration. This modified method expedites the sensing analysis as well as minimizes the use of both analyte and sensor elements in array‐based protein sensing. We have also used this system for the single channel array‐based sensing to compare the sensitivity and the efficacy of these two systems for other applications. This work demonstrated an intrinsic trade‐off associated with these two methods which may be necessary to balance for array‐based analyte detections.     

Development of colorimetric sensor array for discrimination of herbal medicine

Today, traditional systems of medicines (such as herbal distillates) become important resources for providing healthcare benefits. The ability to discriminate among closely similar herbal products is critical to ensure their efficacy. This article proposes a pattern-based recognition approach for the rapid discrimination of herbal distillates using a low-cost and sensitive colorimetric sensor array composed of 25 indicators. The color changes of the sensor exposed to the vapor of the herbal distillates can be monitored easily with an ordinary flatbed scanner. The digital representation of the array response was analyzed with hierarchical clustering analysis (HCA) and principal component analysis (PCA). Using new variable selection strategy, 6 indicators among the 25 employed indicators were selected as discriminant elements of the array. So, a complete discrimination (with 100% accuracy) of 46 herbal distillates was achieved. The proposed sensor represented a better resolution when analytes were placed in an oven at 85 °C for 45 min. This colorimetric sensor array demonstrates excellent potential for quality assurance/control applications of herbal distillates.     

Polymer coated sensor array based on quartz crystal microbalance for chemical agent analysis

Quartz crystal microbalance (QCM) gas sensors based on polymeric material were fabricated and their gas response characteristics were examined for four simulant gases of chemical agents, which were dimethyl methyl phosphonate (DMMP), N,N-dimethylacetamide (DMA), 1,5-dichloropentane (DCP) and dichloroethane (DCE). For the selection of appropriate coating materials, both principal component analysis (PCA) and hierarchical cluster methods were applied to a data set collected from 15 QCM sensors for 12 analytes. Four appropriate coating materials were selected after optimizing the correlation between the 15 coating materials and the first four principal component (PC) factors. The four chosen polymers were used as sensitive component for a sensor array, and then PCA is adapted to classify four simulant gases. The results show that the QCM sensor array has high sensitivity and selectivity to four chemical agents.     

Understanding the dynamics of signal transduction for adsorption of gases and vapors on carbon nanotube sensors

Adsorption dynamics and their influence on signal transduction for carbon nanotube-based chemical sensors are explored using continuum site balance equations and a mass action model. These sensors are shown to possess both reversible and irreversible binding sites that can be modeled independently. For the case of irreversible adsorption, it is shown that the characteristic response time scales inversely with analyte concentration. It is inappropriate to report a detection limit for this type of sensor since any nonzero analyte concentration can be detected in theory but at a cost of increasing transduction time with decreasing concentration. The response curve should examine the initial rate of signal change as a function of analyte concentration. Conversely, a reversible sensor has a predefined detection limit, independent of the detector geometry with a characteristic time scaling that becomes constant in the zero analyte concentration limit. A simple analytical test is presented to distinguish between these two mechanisms from the transient response of a nanotube sensor array. Two systems appearing in the literature are shown to have an irreversible component, and regressed surface rate constants for this component are similar across different sensor geometries and analytes.     

Molecularly Imprinted Photonic Polymers as Sensing Elements for the Creation of Cross‐Reactive Sensor Arrays

By combining molecular imprinting and colloidal crystal templating, molecularly imprinted inverse‐opal photonic polymers (MIPPs) acting as sensing elements have been exploited to create sensor arrays for the first time. With this new strategy, abundant sensing elements with differential sensing abilities were easily accessible. Because of the unique hierarchical porous structure integrated in each sensing element, high sensitivity and selectivity, fast response and self‐reporting (label‐free) detection could be simultaneously achieved. All these fascinating features indicate that MIPPs are ideal sensing elements for creating sensor arrays. By integrating the individual sensing elements on a substrate, the formed array chip delivers better portability and high‐throughput capability. As a demonstration, six kinds of contaminants were selected as analytes. The detection and discrimination of these analytes and even their mixtures in a wide range of concentrations, particularly trace amounts of analyte against a high background of other components, could be achieved, indicating the powerful capability of MIPPs‐based sensor array for sensing. These results suggest that the described strategy opens a new route for sensor array creation and should find important applications in a wide range of areas.     

Supramolecular chemistry approach to the design of a high-resolution sensor array for multianion detection in water

Reliable sensing of structurally similar anions in water is a difficult problem, and analytical tests and sensor devices for reliable sensing of multiple anions are very rare. This study describes a method for fabrication of simple colorimetric array-based assays for aqueous anion solutions, including complex analytes encountered in real-life applications. On the fundamental level, this method shows how the discriminatory capacity of sensor arrays utilizing pattern recognition operating in multianalyte environments may be dramatically improved by employing two key features. The synergy between the sensor and hydrogel host resembles the cooperative effects of an apoenzyme and cofactor: the host hydrogel helps extract the target anions from the bulk analyte while stripping the solvate molecules off the anions. In addition, the supramolecular studies of the affinity and selectivity of the potential sensors for target analytes allow for constructing an array predesigned for a particular analyte. To illustrate both aspects, an eight-sensor array utilizing colorimetric sensor materials showing selectivity for fluoride and pyrophosphate while displaying significant cross-reactivity for other anions such as carboxylates, phosphate, or chloride was used to differentiate between 10 anions. The quantitative analyses were also performed to show that the eight-sensor array was found to operate across 4 orders of magnitude concentrations (0.20-360 ppm; 10 microM to 20 mM). The applicability of this approach was demonstrated by analyzing several toothpaste brands. The toothpastes are complex analytes comprising both known and unknown anions in various concentrations. The fluoride-selective yet cross-reactive array is shown to utilize the fluoride content as the main differentiating factor while using the remaining anionic components for further differentiation between toothpaste brands.     

Development of an analytical microsystem for organic gas detection based on surface acoustic wave resonators

Modified Surface Acoustic Wave (SAW) devices can be used as highly sensitive detectors for gases: coated with a selective sorptive layer, they serve as a frequency determining element of an oscillator circuit. To perform a quantitative analysis of organic gas mixtures with polymer coatings as sensitive membranes, it is necessary to use an array of several SAW sensors with sensitivities towards various gaseous components and a subsequent pattern recognition of the sensor responses. An automatic working, self purging and compact analytical microsystem has been developed for organic gas detection. As the central component it contains an array of nine commercially available SAW resonators working at frequency of 433.92 MHz. Eight sensor oscillators, one common reference oscillator for temperature compensation and circuits for frequency mixing are mounted within a compact radial housing (diameter 108 mm). A selection of polymers has been made to detect a broad variety of gaseous organic analytes. Of particular interest have been hydrocarbons, halogenated hydrocarbons and aromatic compounds. Initial experiments with these analytes have been carried out to proof the selection and to optimize the combination of polymer coatings. With the compact sensor configuration a very fast response time in the range of seconds is obtained for qualitative determination of the analytes.Dedicated to Professor Dr. Dr. h.c. mult. J. F. K. Huber on the occasion of his 70th birthday     

Ultrasensitive detection of aliphatic nitro-organics based on “turn-on” fluorescent sensor array

The broad class of explosives includes nitro aromatics as well as challenging aliphatic nitro-organics whose detection is important from counter-terrorism and national security perspectives. Here we report a turn-on fluorescent sensor array based on aggregation-induced emission (AIE) fluorophores as receptors. To achieve a good sensing system with fast response, good sensitivity and low detection limit, three receptors with abundant chemical diversities for target analytes were synthesized. The turn-on response of the individual receptor showed highly variable and cross-reactive analyte-dependent changes in fluorescence. The excellent ability to identify a variety of explosives, especially the challenging aliphatic nitro-organics (2,3-dimethyl-2,3-dinitrobutane (DMNB), 1,3,5-trinitro-1,3,5-triazinane (RDX), cyclotetramethylene tetranitramine (HMX) and entaerythritol tetranitrate (PETN)), was demonstrated in qualitative and quantitative analyses with 100% accuracy. The fluorescence signal amplification in the presence of explosives allows for application of these receptors in a sensor microarray suitable for high-throughput screening. These results suggested that the cross-reactive sensor array based on AIE fluorophores could find a wide range of applications for sensing various analytes or complex mixtures.     

Colorimetric Recognition of Aldehydes and Ketones

A colorimetric sensor array has been designed for the identification of and discrimination among aldehydes and ketones in vapor phase. Due to rapid chemical reactions between the solid‐state sensor elements and gaseous analytes, distinct color difference patterns were produced and digitally imaged for chemometric analysis. The sensor array was developed from classical spot tests using aniline and phenylhydrazine dyes that enable molecular recognition of a wide variety of aliphatic or aromatic aldehydes and ketones, as demonstrated by hierarchical cluster, principal component, and support vector machine analyses. The aldehyde/ketone‐specific sensors were further employed for differentiation among and identification of ten liquor samples (whiskies, brandy, vodka) and ethanol controls, showing its potential applications in the beverage industry.     

An approach to the spectral simulation of infrared hollow waveguide gas sensors

Optical simulations enable to model an entire chemical gas sensing platform based on hollow waveguides (HWGs) operating in the mid-infrared spectral regime using a three-dimensional representation of the sensor components and taking the spectral response to virtual analytes into account. Furthermore, a strategy for including the spectral response of dielectrically coated HWGs is demonstrated. Utilizing experimentally obtained spectroscopic data recorded at well-defined conditions, the complex refractive indices of selected target analytes (i.e., methane, butane, and isobutylene) have been derived based on a refined harmonic oscillator model. In turn, these parameters have enabled to directly assign the dielectric functions of these analytes to virtual objects representing the analyte within the modeled sensor setup. In a next step, spectroscopic sensor response functions have been simulated as absorbance spectra across selected wavelength regimes utilizing spectrally resolved ray-tracing techniques and have been compared to experimental data.