基于多指示剂的宽范围离子分析识别技术与应用

采用多指示剂聚合构成的离子分析物识别器,加上人工神经网络数据处理,构成一种新型宽范围离子分析识别技术,能有效扩大对离子的敏感范围,解决光纤化学传感器普遍存在的识别范围小的缺点。对氢离子的分析试验验证了该方法的有效性。     

Multi-Analyte Sensing: From Site-Selective Deposition to Randomly-Ordered Addressable Optical Fiber Sensors

In this report we review the progress in the development of imaging fiber chemical sensors. Emphasis is placed on the chemical sensor component and the fabrication of architectures appropriate for multi-analyte sensing, such as optical fiber sensors. Two main approaches in the fabrication of such sensors will be highlighted: first, sensors made with spatially-resolved sensing sites by site-selective polymerization, second, sensors prepared by random distribution of microsphere sensors on an optical imaging fiber containing thousands of μm-scale wells. Examples of each are given.     

Study on low-cost calibration-free pH sensing with disposable optical sensors

As labor costs become more expensive, less labor-intensive disposable devices have become more ubiquitous. Similarly, the disposable optical pH sensor developed in our lab could provide a convenient yet cost-effective way for pH sensing in processes that require stringent pH control. This optical pH sensor is prepared in uniform individual lots of 100–200 sensors per lot. Calibration is accomplished on a few randomly selected sensors out of each lot. We show that all others in the same lot can then be used directly without requiring individual calibration. In this paper, a calibration model is derived to include all the factors that affect the signal of the disposable sensor. Experimental results show that the derived calibration model fits the experimental data. The readings of 28 randomly selected disposable sensors with 4 sensors from each of the 7 lots show an error less than 0.1 pH units in the useful sensing range of the sensor. The calibration model indicates that if further improvement on precision is desired, more uniform porous material and more advanced coating techniques will be required. When it comes to the effects of the varying coasters, house-made low-cost fluorometers, the variability in the brightness ratio of the blue-to-violet LEDs is the primary reason for the lack of precision. Other factors like LED light intensity distribution, optical properties of the filters and electronics also contribute to the coaster-to-coaster difference, but to a lesser extent. Two different methods for correcting the instrument variations were introduced. After correction, the collective reading errors for all the tested instruments were reduced to less than 0.2 pH units within the sensor's useful sensing range. Based on this result, our lab is currently implementing further improvements in modifying the coasters to equalize the ratios of blue-to-violet LED brightness.     

多荧光光纤传感器及其在混合溶剂检测中的应用

微纳光纤与其他微纳结构的集成可以拓展荧光光纤传感器检测范围和集成度,是光纤传感领域的研究热点。目前,国际上关于荧光光纤传感器这一领域的研究还处于单一检测物荧光响应的阶段,对多检测物的多通道荧光响应仍存在很大挑战。本文结合微纳光纤的光波导性能以及有机荧光材料的光功能特性,制备了能够同时激发和收集多种荧光的微纳光纤,并将之应用于高性能荧光光纤传感器的制备。通过选用不同荧光波长的有机材料与凝胶掺杂,制备了多荧光发射的光纤涂层材料,可控构筑了多组分荧光检测剂掺杂凝胶涂层。利用荧光光谱结合色度图分析,确定检测物与色坐标的关系,实现了多检测物的多通道荧光响应,为实现多荧光光纤传感器的可控构筑提供了有益的借鉴和指导意义。     

层层自组装聚电解质膜光纤传感器的制备和应用

在过去几十年中,光纤的应用已经渗透到多个学科领域。光纤的抗电磁干扰、可远程监控、多重监测、体积小及质量轻等特点,使其在传感器研究领域备受关注。聚电解质层层自组装膜构建的光纤传感器自2000年诞生以来,已快速发展成为传感器领域新的研究热点。该类光纤传感器在微量物质的监测方面具有广泛的应用前景。本文从光纤和光纤传感器优点出发,总结了基于层层自组装多层膜的光纤传感器种类、性能、检测原理以及相应的光纤结构和自组装材料;进而结合作者已做的相关工作,论述了在光纤基底上的聚电解质层层自组装及基于自组装膜的光纤传感器的测试;重点综述了近十年层层自组装膜的光纤pH传感器、湿度传感器、气体传感器、生物传感器及其他类型的光纤传感器的制备与应用,并展望了今后聚电解质层层自组装多层膜光纤传感器的发展。     

Diffusion consistent calibrations for improved chemical imaging using nanoparticle enhanced optical sensors

A basic square root function was successfully used as a diffusion consistent calibration function that considers depletion mechanisms often occurring within optical chemical sensors. This continuous function improved image quality and simplified the calibration process. It may be a universal tool for the typical response function of reversible diffusion controlled sensing reactions. Further, we demonstrate that the gold nanoparticle interaction based ammonium fluorosensor is suitable for non-invasive high-resolution quantitative imaging of complex samples. The plasmon sensitized optical sensors were utilized as a bioanalytical tool for chemical imaging of natural degradation processes occurring in biological tissues. Analytical performance of the nanoparticle enhanced sensors confirmed superior sensitivity, reversibility, durability and overall image quality over non-doped sensing membranes. Although applied in a complex matrix of high potassium (major interferent) and very high sodium (interferent) excellent performance is achieved. The nanoparticle interaction/coextraction based sensing scheme utilized in this study is general and can be used for numerous ions, preferably combined with the diffusion consistent calibrations for superior analytical performance. A table with 44 commercially available ionophores is provided to guide potential users of this sensor configuration.     

光导纤维光谱法——Ⅴ.光导纤维化学传感器

本文介绍了光导纤维化学传感器的基本原理,传光型和传感型化学传感器的各种探头设计和构型,以及它们在无机和有机分析方面的应用。涉及参考文献105篇。     

Optical fiber biosensor coupled to chromatographic separation for screening of dopamine, norepinephrine and epinephrine in human urine and plasma

An optical fiber biosensor has been developed for the determination of catecholamines (dopamine, norepinephrine and epinephrine) based on the recognition capacity of the enzyme laccase. In this study, a glass tube constituted by a fused silica fiber coated with a film of polystyrene/divinylbenzene resin (PS/DVB) was used for catecholamines separation. Firstly, the analyzer was tested for calibration and its analytical performance for catecholamines detection was compared with a classical analytical method, namely high performance liquid chromatography-electrochemical detector (HPLC-ED). The developed analytical device shows a high potential for catecholamines quantification with a detection limit of 2.1, 2.6 and 3.4 pg mL⁻¹ for dopamine, norepinephrine and epinephrine, respectively. The analytical sensitivity, inferred from the slope of the calibration curves established for a range of concentrations between 5 and 125 pg mL⁻¹, was found to be 0.344, 0.252 and 0.140 dB/pg mL⁻¹ for dopamine, norepinephrine and epinephrine, respectively. Furthermore, catecholamines speciation with the PS/DVB fiber was completely achieved in 3 min. The analytical performance of the reported sensor was also evaluated and found adequate for catecholamines determination in human urine and plasma samples.     

基于石墨烯光子晶体光纤的流体传感器

与传统的传感器设备阵列相比,由于结构更为简单,具有广泛检测兼容性的光纤系统逐渐成为分布式监测的有力候选者。然而,受工作机制的限制,大多数光纤传感器仍局限于对折射率等物理参数进行探测,一种用于环境化学监测的全光纤分布式传感系统亟待研发。本工作中,我们向化学气相沉积法生长的石墨烯光子晶体光纤(Gr-PCF)中引入了一种化学传感机制。初步结果表明,石墨烯光子晶体光纤可以选择性地检测浓度为ppb级的二氧化氮气体,并在液体中表现出离子敏感性。石墨烯光子晶体光纤与光纤通信系统的波分、时分复用技术结合后,将为实现分布式光学传感环境问题提供巨大的潜力和机会。     

Evaluation of laser induced breakdown spectroscopy for multielemental determination in soils under sewage sludge application

Laser induced breakdown spectroscopy (LIBS) is an atomic emission spectroscopy technique for simple, direct and clean analysis, with great application potential in environmental sustainability studies. In a single LIBS spectrum it is possible to obtain qualitative information on the sample composition. However, quantitative analysis requires a reliable model for analytical calibration. Multilayer perceptron (MLP), an artificial neural network, is a multivariate technique that is capable of learning to recognize features from examples. Therefore MLP can be used as a calibration model for analytical determinations. Accordingly, the present study proposes to evaluate the traditional linear fit and MLP models for LIBS calibration, in order to attain a quantitative multielemental method for contaminant determination in soil under sewage sludge application. Two sets of samples, both composed of two kinds of soils were used for calibration and validation, respectively. The analyte concentrations in these samples, used as reference, were determined by a reference analytical method using inductively coupled plasma optical emission spectrometry (ICP OES). The LIBS-MLP was compared to a LIBS-linear fit method. The values determined by LIBS-MLP showed lower prediction errors, correlation above 98% with values determined by ICP OES, higher accuracy and precision, lower limits of detection and great application potential in the analysis of different kinds of soils.     

Recent progress in fluorescent and colorimetric sensors for the detection of ions and biomolecules

Optical sensors are widely used in the field of analytical sensing and optical imaging because of their high sensitivity, fast response time, and technical simplicity. This review focuses on recent contributions concerning the ions, neutral molecules and especially tumor micro-environment-related parameters based fluorescent or colorimetric sensors and is organized according to their target classifications.     

Fluorescence optical sensors in analytical chemistry

Recent advances in fluorescence spectroscopy, optical fiber technology, and opto-electronics have led to an exciting new analytical technique called fiber-optical fluorosensing. Optical sensors offer some interesting advantages over other sensor types in that they are not subject to electrical interferences, do not require a reference signal, and can be quite small. Remote sensing over wide distances is another attractive feature of the method. Working principles and typical fluorosensor representatives will be described here in some detail.     

Optical chemical sensors for the detection of explosives and associated substances

The main analytical characteristics of optical chemical sensors for detecting the vapors and microparticles of explosives and associated substances are compared. The limits of detection, sensitivity, sensor setting time (response speed) and recovery time after the action of an analyte, and the selectivity of fluorescence sensors, chemiluminescence sensors, surface-enhanced Raman sensors, surface plasmon resonance sensors, absorption integrated optical waveguide sensors, waveguide interferometric sensors, and ring resonator based sensors. The effectiveness of the use of nanosized structures and bio- and nanostructured specific coatings in optical sensors is analyzed.     

Enzyme-free ethanol sensor based on electrospun nickel nanoparticle-loaded carbon fiber paste electrode

We have developed a novel nickel nanoparticle-loaded carbon fiber paste (NiCFP) electrode for enzyme-free determination of ethanol. An electrospinning technique was used to prepare the NiCF composite with large amounts of spherical nanoparticles firmly embedded in carbon fibers (CF). In application to electroanalysis of ethanol, the NiCFP electrode exhibited high amperometric response and good operational stability. The calibration curve was linear up to 87.5 mM with a detection limit of 0.25 mM, which is superior to that obtained with other transition metal based electrodes. For detection of ethanol present in liquor samples, the values obtained with the NiCFP electrode were in agreement with the ones declared on the label. The attractive analytical performance and simple preparation method make this novel material promising for the development of effective enzyme-free sensors.     

Fiber-optic fluorometer signal enhancement and application to biosensor design

Fiber-optic fluorescence spectroscopy is currently the focus of active research because of the high sensitivity of fluorimetry and capacity for remote analysis with optical fibers. It is shown here that a further increase in sensitivity can be achieved by placing a mirror within a few fiber diameters of the distal end of the optical fiber in a solution of flourophore. A potentially four-fold signal enhancement results which is due to an increase in the excitation intensity as well as the reflection of the collected emitted light. The enhancement is shown to be dependent on the pathlength and concentration of the fluorophore, as well as the numerical aperture and core diameter of the optical fiber. The limit of detection of the fluorometer, which incorporates a mirror, is nanomolar dye concentrations, with the maximum response in path lengths of dye that are in the order of 6 fiber diameters. This principle can be applied to the design of optical sensors for continuously monitoring the concentration of specific biochemicals, and a conceptual design for such a sensor is described. A mathematical model is presented which describes the fluorescence output signal of a fiber-optic flourometer which incorporates a mirror.     

An automatic optosensing device for the simultaneous determination of resveratrol and piceid in wines

Despite the increasing number of usage of molecularly imprinted polymers (MIPs) in optical sensor application, the correlation between the analytical signals and the binding isotherms has yet to be fully understood. This work investigates the relationship between the signals generated from MIPs sensors to its respective binding affinity variables generated using binding isotherm models. Two different systems based on the imprinting of metal ion and organic compound have been selected for the study, which employed reflectance and fluorescence sensing schemes, respectively. Batch binding analysis using the standard binding isotherm models was employed to evaluate the affinity of the binding sites. Evaluation using the discrete bi-Langmuir isotherm model found both the MIPs studied have generally two classes of binding sites that was of low and high affinities, while the continuous Freundlich isotherm model has successfully generated a distribution of affinities within the investigated analytical window. When the MIPs were incorporated as sensing receptors, the changes in the analytical signal due to different analyte concentrations were found to have direct correlation with the binding isotherm variables. Further data analyses based on this observation have generated robust models representing the analytical performance of the optical sensors. The best constructed model describing the sensing trend for each of the sensor has been tested and demonstrated to give accurate prediction of concentration for a series of spiked analytes.     

Optical sensors for determining phenolic compounds with different structures

The literature data published in 1993–2012 on the development and application of optical sensors for the determination of phenolic compounds of various structures are summarized. The design, analytical characteristics, and advantages and disadvantages of the existing optical sensors are reviewed, and some examples of using optical sensors in the analysis of real samples, including those from field experiments, are considered in detail.     

Micro-chemical sensors based on fiber-optic excitation of surface plasmons

In this paper the theoretical base and experimental results of a new class of fiber optical supported surface plasmon resonance spectroscopy (SPRS) transducer is given. Surface plasmons were excited by polychromatic light, and the resonant excitation is detected as an intensity minimum in the measured spectra at certain wavelengths. The excitation takes place at the end zone of a multimode fiber coated with a thin surface plasmon resonance supporting metal layer. As examples for the large application field of this transducer a fiber optical immunosensor for the detection of antibodies against bovine serum albumin and a gas sensor for remote detection of tetrachloroethene was constructed and tested successfully. The sensors were constructed following the theoretical predictions for an optimal performance.     

Automatic decoding of sensor types within randomly ordered,high-density optical sensor arrays

In this paper automatic sensor identification of sensor classes within a high-density randomized array, without a priori knowledge of sensor locations, is demonstrated. Two different fluorescence-based sensor types, with hundreds of replicates each, were randomly distributed into an optical imaging fiber array platform. The sensor element types were vapor-sensitive microspheres with the environmentally-sensitive fluorescent dye Nile Red adsorbed on their surface. Nile Red undergoes spectral changes when exposed to different microenvironmental polarity conditions, e.g. microsphere surface polarity or odor exposure. These reproducible sensor spectral changes, or sensor-response profiles, enable sensors within a randomized array to be grouped into categories by optical decoding methods. Two computational decoding methods (supervised and unsupervised) are introduced; equal classification rates were achieved for both. By comparing sensor responses from a randomized array with those obtained from known (control) arrays, 587 sensors were correctly classified with 99.32% accuracy. Although both methods were equally effective, the unsupervised method, which uses sensor response changes to odor exposure, is a better decoding model for the vapor-sensitive arrays studied, because it relies only on the odor-response profiles. Another decoding technique employed the emission spectra of the sensors and is more applicable to other types of multiplexed fluorescence-based arrays and assays. The sensor-decoding techniques are compared to demonstrate that sensors within high-density optical chemosensor arrays can be positionally-registered, or decoded, with no additional overhead in time or expense other than collecting the sensor-response profiles.