表面增强拉曼光谱在环境分析中的研究进展

表面增强拉曼散射(SERS)效应是一种异常的表面光学效应,其增强因子最大可达到1014～1015.环境污染导致人类生存环境受到严重影响.某些污染物,比如持久性污染物,在环境介质中含量低,毒性大,很少能够直接检测出来.因此必须采用更灵敏的方法和技术.由于SERS效应的高灵敏性,SELLS技术有望成为超灵敏分析环境污染物的一种工具.该文综述了表面增强拉曼光谱在环境污染物检测中的研究进展,并提出SERS传感器将是很重要的发展方向.     

液相自组装在表面增强拉曼散射生物传感器中的研究进展

研究发现在不混溶两相界面自组装的纳米粒子可以用于构建液相表面增强拉曼散射（SERS）基底,与传统的固相SERS生物传感器相比,基于此技术发展起来的液相SERS生物传感器具有界面无损、组装快速、自愈合、可以进行原位检测等优势。由此衍生出了一系列在液相自组装SERS活性材料构建生物传感器的方法,该文重点讨论了将液相自组装SERS技术用于对一类重要的疾病标志物microRNAs(miRNAs)的检测中,以扩展基于液相自组装界面作为SERS基底的生物传感器更广阔的应用。     

用表面增强拉曼光谱检测蛋白质膜污染

膜技术如微滤、超滤、纳滤、反渗透等正得到越来越广泛的应用,然而,膜在运行过程中出现的膜污染严重制约了该技术的发展,不仅引起膜通量和分离性能下降,而且污染后膜的清洗和更换也人大提高了运行成本。发展一种能够实现膜污染的早期诊断、过程跟踪以及不同物质膜污染能力鉴别的检测手段对深入了解膜污染过程,控制和减缓膜污染的发生至关重要。     

多层纳米银／壳聚糖膜用于芘的表面增强拉曼测定

多环芳烃类物质的高疏水性质使得其在金属表面吸附能力差,从而拉曼增强信号弱。该文针对此问题,制备了以壳聚糖为骨架,纳米银颗粒为热点的多层纳米银／壳聚糖复合膜表面拉曼增强基底,成功用于芘的表面增强拉曼检测。由于壳聚糖本身的富集作用,目标分子被吸附、富集于银纳米颗粒形成拉曼热点,可检测0．01μmol／L的芘。     

一种新型包埋染料的核壳纳米颗粒表面增强共振拉曼探针的研制及其在免疫分析中的应用

应用于生物分析的纳米探针主要包括:等离子体共振颗粒探针,量子点、荧光探针和拉曼探针等等.拉曼探针跟其它纳米颗粒探针相比,其重要的优点是它能提供丰富的分子结构信息,从而很大程度上避免了光谱重叠,有可能研制出各种不同的拉曼探针.特别值得注意的是,基于表面增强与共振增强相结合的纳米拉曼探针,能超灵敏地、高特异性地检测生物分子.该文采用了一种新型的合成方法,成功地制备了以纳米金为核,二氧化硅为外壳,且其中包埋有染料的金/二氧化硅核壳纳米颗粒,并把它作为一种表面增强共振拉曼(SERRS)探针用于免疫分析.     

基于纳米金颗粒放大的电化学传感器用于三聚氰胺的检测

三聚氰胺与胸腺嘧啶（T）之间能够通过三个氢键结合,以富T的DNA探针为识别元件,结合DNA修饰的纳米金颗粒放大技术,以电活性物质钌胺作为信号分子,发展了一种高灵敏检测三聚氰胺的电化学传感器,该传感器具有良好的特异性和灵敏度,检测下限低至0．5nmol／L。     

基于Fe3O4@SiO2-MIPs富集/表面增强拉曼光谱检测孔雀石绿的研究

以乙烯基修饰的二氧化硅包覆磁性纳米材料为载体,孔雀石绿(MG)为模板分子,采用表面印迹技术制备了具有核壳结构的磁性分子印迹聚合物Fe3O4@Si O2-MIPs(MG)。运用透射电镜(TEM)、傅里叶变换红外光谱仪(FT-IR)、X射线衍射仪(XRD)等技术对聚合物进行结构表征,并开展吸附性能研究。实验结果表明,所制备的Fe3O4@Si O2-MIPs(MG)对MG具有优异的分子识别能力和良好的选择性吸附性能,实现了对养殖水和虾肉中MG的高效富集,采用纳米银表面增强拉曼光谱定量,检测限分别达到0.5 ng/m L和6 ng/g,具有广阔的应用推广前景。     

生物传感器检测牛奶病原微生物的研究进展

牛奶中病原微生物的含量是衡量牛奶质量的重要指标之一,生物传感器在牛奶病原微生物检测方面有较好的优势.介绍了生物传感器的组成和原理,并详细综述了近几年电化学生物传感器和质量敏感型生物传感器在牛奶中病原微生物的定量检测中的研究现状,探讨了未来的发展趋势.     

WO3 nanocrystals: Synthesis and application in highly sensitive detection of acetone

WO₃ nanocrystals have been prepared by a sol-gel route and characterized by X-ray diffractometry, scanning electron microscopy, and transmission electron microscopy. The experimental results show that WO₃ nanocrystals have a high crystallographic quality and a good dispersivity. The particles’ sizes are in the range of 25-100 nm. The fabricated WO₃ nanocrystal-based sensors have an excellent sensitivity and selectivity to acetone, and display a rapid response and recovery characteristics. The developed sensors exhibit a detection limit down to 0.05 ppm at 300 °C, rendering a promising application in noninvasive diagnosis of diabetes. The response mechanism of the WO₃ nanocrystal sensor to low concentration of acetone has been discussed based on the depletion layer model.     

Surface plasmon resonance (SPR) sensors for the rapid, sensitive detection of the cellular response to osmotic stress

Cells regulate their volume in response to changes in osmolarity of both, their extracellular and intracellular environments. As stability of the cell volume is a compelling exigency for cellular integrity, techniques for a sensitive, time-resolved volume measurement of adherently grown mammalian cells attract considerable interest, especially in the field of cell physiology and biology. In this study we apply a surface plasmon resonance (SPR) based biosensor for the comparative analysis of the volume responses of two renal epithelial cell types to non-isotonic challenges. The on-line, label-free and non-invasive biosensor format shows distinct similarities and differences in the reaction kinetics of the two cell types. Furthermore regulatory volume responses to the osmotic stimuli as well as their inhibition by Gd³⁺ ions can be observed with a high time-resolution. Limit-of-detection measurements indicate the high sensitivity of the sensor capable of detecting cellular volume responses of adherently grown mammalian cells to osmotic stimuli well below a bioanalytical relevant value of 5 mOsm/kg.     

A labchip for highly selective and sensitive electrochemiluminescence detection of Hg2+ ions in aqueous solution employing integrated amorphous thin film diodes

An electrochemiluminescence (ECL) based detection of Hg²⁺ ions using a novel monolithically integrated labchip technology has been developed. The combination of a chemical sensor molecule, the azacrown ether appended trisphenanthroline ruthenium(II) complex 1, and an amorphous silicon based pin-diode detects an exceptionally low concentration of 66 nM according to a device current of 1.85 pA, respectively. To support a high sensitivity, fluid volumes of 1.2 or 1.8 nL in the designed measuring cells are investigated by an amorphous silicon based pin-diode at a constant flow rate of 1 μL min⁻¹. The working electrode area can be specified for both cells to 0.06 or 0.09 mm² according to a photosensitive detector area of 400 or 500 μm in diameter. Corresponding to the distance between the monolithic integrated polymer based microcapillary and the sensing pin-diode layers of ∼150 μm the detector solid angle was calculated to 73.3°. The fabrication methodology and the experimental details are presented. Furthermore, performance metrics including diode characteristics, detection limit, transient current behavior, dynamic range, and linearity are reported. Additionally, the chemical structure, the ECL response towards different metal ions, and the relationship between ECL intensity of 1 and the concentration of Hg²⁺ ions are shown.     

Development of a software tool for rapid,reproducible, and stakeholder-friendly dynamic coupling of system dynamics and physically-based models

System Dynamics (SD) modeling is well adapted to developing participatory environmental models. However, SD models are ill-suited for complex physical (e.g., groundwater) processes, and existing methods to couple them with physically-based models tend to be complex and inflexible. We here present Tinamit, a novel tool to couple SD and physically-based models in a rapid, reproducible, and stakeholder-friendly manner. Tinamit requires only a few lines of Python code to couple and simulate models (or, with its interface, no coding at all), which is expected to make model coupling more accessible to stakeholders and allow them to continue developing coupled models after the end of a funded project. We use Tinamit to couple a SD-based farmer economics model from Pakistan with a soil salinity model (SAHYSMOD) and analyze the trade-offs of various policies, of which canal lining with subsidies seemed promising. Such results cannot be readily obtained from either model alone.     

水体氨氮原位快速检测智能传感器的研制

介绍了氨氮传感器的检测原理,给出了智能氨氮传感器的结构设计和电路设计方法,重点讲述了氨气敏和铵离子传感器的标定算法以及多传感器数据融合算法,并对其性能进行了测试和分析。该智能氨氮传感器是集成了氨气敏、铵离子和pH温度探头的复合传感器,可以用于实现水体氨氮含量的原位快速检测。     

A FETI-like domain decomposition method for coupling finite elements and boundary elements in large-size problems of acoustic scattering

Numerical simulations of acoustic scattering in the frequency domain based on hybrid methods coupling finite elements and boundary elements are the most suited for dealing with problems involving wave propagation in inhomogeneous media. Furthermore, it is necessary to resort to high performance computing to effectively solve the large size problems. However, the direct coupling yields a linear system with a matrix which is partly dense and partly sparse and thus not adapted to high performance computing. To avoid this difficulty, we present a new iterative method constructed from a non overlapping domain decomposition technique.     

A simple retrieval method for land surface temperature and fraction of water surface determination from satellite microwave brightness temperatures in sub-arctic areas

A strong linear relationship is found between Special Sensor Microwave/Imager (SSM/I) microwave (19 and 37 GHz) surface emissivities at horizontal and vertical polarizations over snow- and ice-free land surfaces. This allows retrieving the land surface emissivity and temperature from satellite microwave brightness temperatures after atmospheric corrections. Over the Canadian sub-arctic continental area, we show that the main factor modifying the emissivity is the fraction of water surface (FWS) within a pixel. Accordingly, a map of the fraction of water surface across the Canadian landmass is derived, given a correspondence within 6% as compared to the 1 km² Canadian National Topographic Database of water-covered areas. The microwave-derived surface temperatures are compared to synchronous in situ air and ground surface temperatures and also with independent satellite IR measurements over areas without snow or ice. Root mean square differences range between 2° and 3.5°, with mean bias error of the order of 1-3°. Better results are always obtained with the 37 GHz channel rather than with the 19 GHz channel. Over dense vegetation, the microwave-derived surface temperature is closer to the air temperature (at surface level) than to the ground temperature. The proposed simple retrieval algorithm, not sensitive to cloud cover, appears very useful for monitoring summer interannual or seasonal trends of the fraction of surface water, as well as the daily land surface temperature variation, which are very important parameters in environmental change analysis.     

Empirical comparisons of feed-forward connectionist and conventional regression models for prediction of first lactation 305-day milk yield in Karan Fries dairy cows

In this paper, two connectionist models are proposed based on different learning paradigms, viz., back propagation neural networks (BPNN) and radial basis function neural networks (RBFNN) to predict the first lactation 305-day milk yield (FLMY305) in Karan Fries (KF) dairy cattle. Also, a conventional multiple linear regression (MLR) model is developed for the prediction. In this study, all the models have been developed using a scientifically determined optimum dataset of representative breeding traits of the cattle. The prediction performances of the connectionist models are compared with that of the conventional model. This study shows that the RBFNN model performs relatively better than the MLR model. However, the BPNN model performs more or less in the close vicinity of the conventional MLR model. Hence, it is inferred that the connectionist models have potential as an alternative to the conventional models for predicting FLMY305 in KF cattle.     

A rapid and selective method for monitoring the growth of coliforms in milk using the combination of amperometric sensor and reducing of methylene blue

A novel method for monitoring the growth of coliforms in milk was developed based on measuring the current change in an amperometric sensor. The sensor consists of a circuit with a homemade potentiostat and a pair of electrodes. The electrode was immersed in milk samples containing methylene blue with various concentrations of bacterial inoculums. The microbial metabolism led to the reduction of methylene blue resulting in a change of current. The time required to identify readily detectable change (detection time, DT) provided an approximate measurement of the amount of microorganisms in the initial inoculums. The sensor system used in this study has the selectivity towards coliform bacteria such as Escherichia coli and Enterobacter aerogenes. The calibration curve of DT against concentration of coliform showed a linear correlation coefficient (R² = 0.9192) over the range of 10²–10⁸ CFU/mL. The sensor was able to detect the coliform bacteria at initial concentrations of 10⁵ CFU/mL within 6 h, making it suitable for use in real-time monitoring of bacterial growth. This system has potential application in the detection of coliform concentration in milk at dairy farms when a proper selective media is designed.