Colorimetric sensor array–smartphone–remote server coupling system for rapid detection of saccharides in beverages

A kind of “colorimetric sensor array–smartphone–remote server” coupling system was constructed for rapid on-site testing of saccharides. First, the binding capacity between saccharides and boric acid compounds (boric acid, phenylboronic acid and 3-nitrophenylboronic acid) was studied. The binding capacity of 3-nitrophenylboronic acid was found to be the highest, followed by phenylboronic acid and boric acid. Then a small-scale colorimetric sensor array (2 × 2) of pH indicator based on affinity interaction between 3-nitrophenylboronic acid and saccharides was developed to detect 19 kinds of saccharides. A camera phone was used to acquire the array images before and after reaction, then the self-developed color discrimination software in smartphone was applied to process pictures in order to obtain the color difference image and data of analytes. The color difference data were analyzed by several methods, including principal component analysis, hierarchical cluster analysis and linear discriminant analysis. The analysis results showed that the sensor array (2 × 2) established in this paper has great discriminative capability for 19 kinds of saccharides, and the classification accuracy is as high as 100%. Nineteen different quantitative models of saccharides that showed high accuracy and precision were established based on partial least-square method. Finally, the smartphone was connected to a remote server on which the qualitative analysis and quantitative analysis models for analytes had been established. The color difference data obtained by the smartphone were uploaded to the remote server for the qualitative analysis and quantitative analysis of saccharides. The effectiveness of the “colorimetric sensor array–smartphone–remote server” coupling system in rapid on-site detection of saccharides was further verified by the spike and recovery experiments. The qualitative analysis results showed that this coupling system could distinguish all of the analytes without a mistake, and the quantitative analysis results showed that the predicted values for saccharides were close to the real values.     

可视交叉传感阵列对蛋白质及其热变性过程的快速识别

以卟啉及其衍生物和特异性染料为敏感化学元件, 基于交叉响应原理构建了识别蛋白质的可视6×6阵列. 该阵列以颜色差谱图显示其与蛋白质作用呈现的特异性光谱反应, 采用聚类分析、 主成分分析和欧氏距离对图谱进行了分析. 结果表明, 该阵列可以鉴别模式蛋白牛血清白蛋白(BSA)、 牛血红蛋白(BHb)和卵清白蛋白(Ova)及其混合物, 且有望实现定量分析. 此外, 阵列的高敏感性使其不仅能识别天然蛋白质和不同变性程度的蛋白质, 还能对其热变性过程进行可视化实时监控. 该阵列产生的特殊颜色变化与蛋白质的空间构型、 微环境pH值的差异及溶解度有关. 因此, 该方法不仅能实现对蛋白质的快速识别, 为蛋白质热变性机理的研究提供新途径, 而且在临床医学和食品安全等的实时快速检测方面有潜在的应用价值.     

A novel detector using a fluorescent sensor array and discrimination of pesticides

A novel, simple, and rapid detector using a fluorescent sensor array for discrimination and quantification of different concentrations (ppb level) of pesticides was proposed in this paper. Employing porphyrin, porphyrin derivatives, and chemically responsive dyes as the sensing elements, the developed sensor array based on a cross-responsive mechanism showed a unique pattern of fluorescence changes upon the reaction that lasted just 10 min. The eigenvalues from raw fluorescence spectra were analyzed via a pattern recognition algorithm, including hierarchical cluster analysis (HCA), principal component analysis (PCA), and back-propagation neural network (BPNN). The results showed that HCA, which were used to assess the feasibility and effectiveness of discrimination of the fluorescent sensor array, revealed a distinct separation between different pesticides. PCA and BPNN were used for automatically predicting the concentration of pesticides, and the recovery was 91.29–109.81 % while the lowest relative standard deviation was up to 3.12 %. It indicates a detector based on the fluorescent sensor array is a rapid and feasible sensing platform for the discrimination and quantitative analysis of pesticides, and also shows the possibilities in the related fields of pesticides identification and detection.     

Traditional Vinegars Identification by Colorimetric Sensor

An expanded colorimetric array detector that was capable of the highly sensitive and highly selective discrimination of vinegars was developed. The system of olfaction visualization and operational approach were discussed. Thirty dyes were selected from natural dyes, chemoresponsive dyes and pH dyes. A 5 × 6 colorimetric sensor array was created by printing the dyes on reverse phase silica gel plates. Four traditional vinegars were measured by the colorimetric sensor array. With cluster analysis, all samples were assembled ‘Zhenjiang Vinegar’, ‘Shanxi Vinegar’, ‘Sichuan Vinegar’, ‘Jiangzhe Vinegar’ when the similarity was 12. This work showed the potential applications of the olfaction visualization technology for visual analyzing and fingerprint identifying the aroma of food.     

Colorimetric sensing of anions in water using ratiometric indicator-displacement assay

The analysis of anions in water presents a difficult challenge due to their low charge-to-radius ratio, and the ability to discriminate among similar anions often remains problematic. The use of a 3 × 6 ratiometric indicator-displacement assay (RIDA) array for the colorimetric detection and identification of ten anions in water is reported. The sensor array consists of different combinations of colorimetric indicators and metal cations. The colorimetric indicators chelate with metal cations, forming the color changes. Upon the addition of anions, anions compete with the indicator ligands according to solubility product constants (K_sp). The indicator–metal chelate compound changes color back dramatically when the competition of anions wins. The color changes of the RIDA array were used as a digital representation of the array response and analyzed with standard statistical methods, including principal component analysis and hierarchical clustering analysis. No confusion or errors in classification by hierarchical clustering analysis were observed in 44 trials. The limit of detection was calculated approximately, and most limits of detections of anions are well below μM level using our RIDA array. The pH effect, temperature influence, interfering anions were also investigated, and the RIDA array shows the feasibility of real sample testing.     

Discrimination of Lung Cancer Related Volatile Organic Compounds with a Colorimetric Sensor Array

A simple and rapid discrimination of four lung cancer related volatile organic compounds (VOCs) was achieved with a novel colorimetric sensor array. Based on the cross-responsive mechanism, the sensor system exhibited high sensitivity to selected lung cancer biomarkers, including p-xylene, styrene, isoprene, and hexanal with concentrations varying from 50 ppb to 500 ppb. By extracting color information, it provided good selectivity and fine discrimination of selected gases via pattern recognition with Fisher linear discriminant (FLD). Additionally, with the employment of the Takagi-Sogeno Fuzzy Neural Network (TSFNN), different concentrations of selected VOCs were discriminated. It also suggested that the colorimetric sensor array proposed could not only distinguish different lung cancer related VOCs but also discriminate specific VOCs of different concentrations with an average rate of classification up to 95%. Our preliminary study demonstrated that the cross-responsive sensor array had infinite potential for further clinical and commercial use for early diagnosis of lung cancer.     

A colorimetric indicator-displacement assay array for selective detection and identification of biological thiols

A simple, inexpensive yet highly selective colorimetric indicator-displacement assay array for the simultaneous detection and identification of three important biothiols at micromolar concentrations under physiological conditions and in real samples has been developed in this work. With use of an array composed of metal indicators and metal ions, clear differentiation among cysteine, homocysteine and glutathione was achieved. On the basis of the colour change of the array, quantification of each analyte was accomplished easily, and different biothiols were identified readily using standard chemometric approaches (hierarchical clustering analysis). Moreover, the colorimetric sensor array was not responsive to changes with 19 other natural amino acids, and it showed excellent reproducibility. Importantly, the sensor array developed was successfully applied to the determination and identification of the three biothiols in a real biological sample.

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.     

Preoxidation for colorimetric sensor array detection of VOCs

A disposable preoxidation technique that dramatically improves the detection and identification of volatile organic compounds (VOCs) by a colorimetric sensor array is reported. Passing a vapor stream through a tube packed with chromic acid on silica immediately before the colorimetric sensor array substantially increases the sensitivity to less-reactive VOCs and improves the limits of detection (LODs) ~300-fold, permitting the detection, identification, and discrimination of 20 commonly found indoor VOC pollutants at both their immediately dangerous to life or health (IDLH) and permissible exposure limit (PEL) concentrations. The LODs of these pollutants were on average 1.4% of their respective PELs.     

Peptide conjugated cellulose nanocrystals with sensitive human neutrophil elastase sensor activity

In chronic wounds, elevated human neutrophil elastase (HNE) is a destructive protease that has been proposed as a biomarker. Numerous wound dressing designs have been introduced in an effort to lower HNE levels. The clinical detection of HNE as a point of care biomarker or an in situ colorimetric adjuvant to chronic wound dressings presents potential advantages in the management of chronic wounds. A colorimetric approach to the detection of HNE using peptide conjugated cotton cellulose nanocrystals (CCN) is reported here. For this purpose a HNE tripeptide substrate, n-Succinyl-Alanine–Alanine-Valine-para-nitroanilide (Suc-Ala–Ala-Val-pNA), was covalently attached to glycine esterified CCN and compared with a similar tetrapeptide analog for colorimetric HNE sensor activity. Visible HNE activity was significantly higher on CCN tripeptide conjugates when compared with similar analogs synthesized on paper. Upon enzymatic release of para-nitroaniline (pNA) from the Glycine-CCN conjugate of succinyl-Ala–Ala-Val-pNA, amplification of the colorimetric response from pNA with reactive dyes enhanced visible absorption of the chromogen. Two color amplifying dyes that react with pNA were compared for their ability to enhance the visual sensor response to HNE activity. The colorimetric detection of HNE with CCN tripeptide conjugates was sensitive at HNE levels previously reported in chronic wound fluid (0.05 U/mL HNE). The HNE sensor and the chromogen amplifying dyes were interfaced with 50 and 10 kD dialysis cellulose membranes (DCM) to model filtration of HNE and chromogen (pNA) from a model wound dressing surface before and after sensor reactivity. The detection sensitivity to HNE activity was assessed with the CCN-tripeptide conjugate interfaced at the DCM surface distal and proximal to a dressing surface. The HNE sensor interfaced proximal to the dressing surface was most efficient with 10 kD membrane filtration of pNA and subsequent reaction with amplifying dyes. When interfaced with the 10 kD cellulose membrane, elastase sensor activity remained sensitive to 0.05 U/mL HNE. The nanocellulose surface properties, performance and design issues of the biosensor approach are discussed.     

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.     

Virtual sensor array as a tool for classifying air pollution

This work examined the acquisition of information about gases using a virtual sensor array and classification. We were particularly interested in the approach in which classes are defined in a qualitative–quantitative manner, that is, by identifying the gas and concentration range. This type of information will be of interest for air pollution assessment purposes. In this field of application, it is often not necessary to provide very precise information. The idea of the virtual sensor array exploits the dependence of a gas sensor’s response on operating conditions. Originally it was developed as a means to improve the selectivity of an electronic nose when energy consumption by this device was a serious limitation. If the response of one sensor is measured in n time points, and each time point is characterised by different controlled exposure conditions, the sensor becomes analogous to an n-dimensional virtual sensor array. Compared with conventional approaches, a virtual sensor array based on a single sensor offers low power consumption, low volume, and low cost, which opens up new markets for wide application of portable and handheld devices. In this article, we show that a virtual sensor array and classification may serve as a reliable source of qualitative–quantitative information about gases. Twenty-six classes (five substances, each at five concentration ranges, and pure air) were recognised with a true positive rate higher than 99.14 ± 0.49% and a true negative rate higher than 99.21 ± 0.52%. As demonstrated, the basis for recognition could be a virtual sensor array associated with a low-power consuming sensor (210–280 mW). The complexity of the applied classifier could be adjusted depending on the choice of sensor operating conditions. For a complex classifier like support vector machine, dynamic exposure was sufficient to obtain high classification performance. A simpler classifier like k-nearest neighbours required more information, that is, information associated with static as well as dynamic exposure.     

基于纳米银的比色阵列传感器的构建及在蛋白质检测中的应用

蛋白质的快速高效检测和鉴定在医学诊断、不同疾病的治疗和蛋白质组学中具有巨大的前景。目前的检测手段大多存在一些问题,如操作繁琐、效率低等,因此开发一个理想的蛋白质检测方法尤为重要。以纳米银(AgNPs)为传感元件的阵列传感器在蛋白质检测方面具有操作便捷、准确率高、可视化等优点。本文合成两种不同颜色和形状的AgNPs:黄色球形和蓝色三角形,以此构建一个简单的比色阵列传感器,用于蛋白质的区分检测。该传感器可以准确地识别和区分不同种类的蛋白质,准确率为100%。在成功识别出不同类型的蛋白质的基础上,进一步评估了该阵列传感器应用于区分正常和变性蛋白质的能力,准确率为96.0%。此外,该阵列传感器对于未知样本的识别也具有高的准确率。     

Colorimetric Artificial Nose for Identification of Breath Volatile Organic Compounds of Patients with Lung Cancer

A novel and highly sensitive colorimetric sensor array was developed for the detection and identification of breath volatile organic compounds（VOCs） of patients with lung cancer.Employing dimeric metalloporphyrins,metallosalphen complexes,and chemically responsive dyes as the sensing elements,the developed sensor array of artificial nose shows a unique pattern of colorific changes upon its exposure to eight less-reactive VOCs and their mixture gas at a concentration of 735 nmol/L within 3 min.Potential of quantitative analysis of VOCs samples was proved.A good linear relationship of 490-3675 nmol/L was obtained for benzene vapor with a detection limit of 49 nmol/L（S/N=3）.Data analysis was carried out by Hierarchical cluster analysis（HCA） and principal component analysis（PCA）.Each category of breath VOCs clusters together in the PCA score plot.No errors in classification by HCA were observed in 45 trials.Additionaly,the colorimetric sensor array showed good reproducibility under the cyclic sensing experiments.These results demonstrate that the developed colorimetric artificial nose system is an excellent sensing platform for the identification and quantitative analysis of breath VOCs of patients with lung cancer.     

Multiple detection for hydrazine based on reduction of the 1,6,7,12-tetrachloroperylene diimide derivative

In this contribution, the 1,6,7,12-tetrachloroperylene diimide derivative (TClPDIs) with first reduction potential of ? 0.0117 V was chosen for detection of hydrazine based on colorimetric probe, fluorescence quenching and chemical sensor. Interaction of TClPDIs with hydrazine in N,N-dimethylformamide lead to a red shift in the maximum absorption and fluorescence quenching as a result of reduction. Consequently, the yellow TClPDIs solution transform to green, the linear range of the determination of hydrazine was 0.317–2.895 nmol (R² = 0.989) for colorimetric detection. Furthermore, the linear range of determination for hydrazine based on fluorescent quenching of TClPDIs was 0.645–3.57 nmol with a correlation coefficient R² = 0.986. Thin film devices of TClPDIs with different thickness (20, 40 and 60 nm) deposited on interdigital electrodes were chosen to study the sensitive detection and quantification of organic amine vapors by monitoring the changes of its current intensity under ambient conditions. This chemical sensor showed different sensitivity towards different organic bases. These results indicated that the TClPDIs is a favorable candidate for the detection of hydrazine using reduction mechanism.     

Enhancement of sensitivity of paper-based sensor array for the identification of heavy-metal ions

Paper-based microfluidic devices have been widely investigated in recent years. Among various detection techniques, colorimetric method plays a very important role in paper-based microfluidic devices. The limitation, however, is also clear: they generally require highly sensitive indicators. In this work, we have developed a novel enrichment-based paper test for the discrimination of heavy-metal ions. Comparing to regular paper-based microfluidic devices, enrichment-based technique showed largely improved sensitivity. Combining with eight pyridylazo compounds and array technologies-based pattern-recognition, we have obtained the discrimination capability of eight different heavy-metal ions at same concentration as low as 50 μM using our enrichment-based pyridylazo compounds array paper. Identification of the heavy-metal ions was readily achieved using a standard chemometric approach. This method can be, of course, used for other analytes as well.     

A differential array of metalated synthetic receptors for the analysis of tripeptide mixtures

A novel library of resin-bound receptors within a cross-reactive differential array for the identification and discrimination of tripeptides and tripeptide mixtures is reported. Pattern recognition using principal component analysis showed complete discrimination of four similar tripeptides and three tripeptide mixtures. The library is comprised of a Cu(II)-centered core with two proximally appended tripeptide arms emanating outward. One tripeptide arm was prepared using combinatorial chemistry to generate the differential nature of the library. Thirty resin-bound receptors were randomly selected from the library and placed within a silicon microchip array that included integrated microfluidics elements, and an indicator-uptake assay was used for colorimetric signaling. The indicator Orange G yielded an accurate measure of the degree of association between receptors and analytes as determined by kinetic analysis of the indicator-uptake assays. Within this paper we detail the method used for differential sensing using a novel receptor library. This work further demonstrates the power and utility of a differential array of synthetic receptors for identification and discrimination of complex bioanalytes.     

A colorimetric sensor array for organics in water

Molecular recognition of organic compounds in aqueous solutions is inherently challenging due to the potential interference from the very high concentration of water. Here we present a simple colorimetric sensor array that probes a wide range of chemical properties. By printing hydrophobic dyes on a hydrophobic membrane, sensor arrays are easily prepared that provide substantial chemical selectivity for the identification and quantification of various organics (both single compounds and complex mixtures) dissolved in water. It is possible to differentiate easily even among closely related organic compounds. Upon immersion in aqueous solutions, digital imaging of the dye array before and after exposure to an analyte provide a color change profile that is a fingerprint for the organic components of the solution. Facile identification of a wide variety of aqueous organic solutions is possible over a concentration range of 0.1 M to 1 muM. Complex mixtures present no inherent difficulty; for example, a series of commercial soft drinks were easily distinguished using the colorimetric sensor array approach.     

Full-range optical pH sensor array based on neural networks

A neural network multivariate calibration is used to predict the pH of a solution in the full-range (0–14) from hue (H) values coming from imaging an optical pH sensor array based on 11 sensing elements with immobilized pH indicators. Different colorimetric acid-base indicators were tested for membrane preparation fulfilling the following conditions: 1) no leaching; 2) change in tonal coordinate by reaction and 3) covering the full pH range with overlapping between their pH responses. The sensor array was imaged after equilibration with a solution using a scanner working in transmission mode. Using software developed by us, the H coordinate of the colour space HSV was calculated from the RGB coordinates of each element.The neural network was trained with the calibration data set using the Levenberg–Marquardt training method. The network structure has 11 input neurons (each one matching the hue of a single element in the sensor array), 1 output (the pH approximation value) and 1 hidden layer with 10 hidden neurons. The network provides an MSE = 0.0098 in the training data, MSE = 0.0183 in the validation data and MSE = 0.0426 in the test data coming from a set of real water samples. The resulting correlation coefficient R obtained in the Pearson correlation test is R = 0.999.     

High selective colorimetric detection of Cd<Superscript>2+</Superscript> ions using cysteamine functionalized gold nanoparticles with cross-linked DL-glyceraldehyde

This paper reports an ingenious colorimetric sensor probe for the detection of Cd²⁺ ions using cysteamine functionalized gold nanoparticles cross-linked with DL-glyceraldehyde (DL-G-CA-Au NPs). Rapid aggregation in DL-G-CA-Au NPs was observed by adding Cd²⁺ ions at PBS buffer pH 7.0, which results in an immediate color change of the solution from red to blue. A red-shift in the wavelength of absorption peak was measured from 520 to 736 nm using UV–visible spectroscopy. The surface functionalization and aggregation of Au NPs were also characterized by recoding FI-IR and DSL data. The colorimetric probe was analyzed in the concentration of Cd²⁺ ions ranging from 0.05 to 500 μM, and a good linearity was observed towards the lower concentration levels with a coefficient of correlation R ² = 0.9862. The limit of detection was found to be 21 nM, which best describes its superior performance over other reported colorimetric probes. Furthermore, the performance of the probe was not influenced by other metal ions, and the stability of DL-G-CA-Au NPs was maintained even after 30 days. The proposed method was successfully applied to various water samples collected from the environment, and an accuracy ≥ 98% was achieved.