Electrochemical sensor for hydroperoxides determination based on Prussian blue film modified electrode

An electrochemical sensor for hydroperoxides determination was investigated. The sensor was based on the electrocatalytic reduction of hydroperoxides on Prussian blue (PB)-modified glassy carbon electrode. The modified electrode possesses a high electrocatalytic effect towards all studied peroxides with the highest effect obtained with H₂O₂ followed by tert-butyl hydroperoxide (TBH), cumene hydroperoxide (CH) and linoleic acid hydroperoxide (LAH). In addition, the modified electrode showed a good stability and a fast response time (<20 s). The lower detection limits of H₂O₂, TBH, CH and LAH were found to be 10⁻⁷ mol L⁻¹, 2 × 10⁻⁷ mol L⁻¹, 3.5 × 10⁻⁷ mol L⁻¹ and 4 × 10⁻⁷ mol L⁻¹, respectively. The electrochemical sensor was then applied for amperometric determination of peroxide value (PV) in edible oil at an applied potential of 50 mV (vs. Ag/AgCl (1 M KCl)). A good linearity has been found in the range 0.02–1.0 mequiv. O₂/kg, with a detection limit (S/N = 3) of 0.001 mequiv. O₂/kg. The precision of the method (R.S.D., n = 9) for within and between-days is better than 1.9% and 2.7%, respectively at 0.1 mequiv. O₂/kg. The method was successfully applied to the determination of PV in real edible oil samples with an excellent agreement with results obtained with the official standard procedure. The proposed method is accurate, simple, cheap and could be used to control edible oil rancidity with a high sample throughputs (more than 120 samples/h).     

Redox coenzyme functionalization of electrochemically grown Prussian blue films

Thin solid films of the molecular semiconductor rubidium Prussian blue, RbFe₂(CN)₆, are electrochemically deposited on quartz-crystal microbalance electrodes. The films are found to surface-coordinate tightly both the oxidized and reduced forms of the redox coenzyme nicotinamide adanine dinucleotide (NAD⁺), presumably via the diphosphate linkage. Gravimetric and electrode potential measurements provide evidence that the surface-bound NAD⁺ can act as an electron-transfer mediator from solution to the Prussian blue. The electron transfer appears to result from an inner-sphere mechanism between NADH and Fe₂(CN)₆⁻; unbound NADH in solution does not reduce the Prussian blue films. Conversion of surface-bound NAD⁺ to NADH can be enacted enzymatically, with subsequent electron transfer regenerating NAD⁺. The semiconductive properties of the film transport surface electrons to the bulk, enabling near-quantitative reduction, with the bound coenzyme acting catalytically as an electron-transfer mediator. The potential application of these coenzyme-functionalized molecular semiconductor films to the area of biosensing is explored.     

Amperometric glucose microbiosensor based on a Prussian Blue modified carbon fiber electrode for physiological applications

Results of experiments in vitro and in vivo, using an amperometric glucose microbiosensor based on a Prussian Blue (PB) modified carbon fiber electrode with very low dimensions (∼10 μm diameter), are presented. The electrocatalytic properties of the PB film enable detection of an enzymatic by-product (H₂O₂) at a very low applied potential: 0.0 V against SCE. The main steps during glucose microbiosensor construction were examined by cyclic voltammetry and electrochemical impedance spectroscopy. Excellent selectivity of the glucose microbiosensors against a large number of physiological interference compounds is demonstrated. Finally, microbiosensor responses during intraperitoneal injection, local infusion and local electrical stimulation showed sufficient sensitivity and stability to monitor multi-phasic and reversible changes in brain ECF glucose levels during physiological experiments, illustrating the excellent properties and utility of this biosensor design in the neurosciences.     

多壁碳纳米管半乳糖生物传感器研究

以普鲁士蓝(PB)膜玻碳电极为基质,用多壁碳纳米管固定半乳糖氧化酶(GAO),构造了半乳糖电流型传感器,研究了半乳糖氧化酶在此传感器中的催化反应机理,对多壁碳纳米管半乳糖传感器的检测条件进行了优化。确认其对半乳糖具有灵敏的生物响应性,表现出良好的线性和分辨力。此传感器对半乳糖摩尔浓度0.5×10-4~1.5×10-2mol/L呈线性响应,检出限为1.0×10-4mol/L,响应时间为10 s,30 d后,响应电流依然保持80%。     

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.     

Voltammetric behavior of multi-walled carbon nanotubes modified electrode-hexacyanoferrate(II) electrocatalyst system as a sensor for determination of captopril

The study of electrochemical behavior and determination of captopril, as an angiontensin-converting enzyme inhibitor, is reported on multi-walled carbon nanotube (MCNT) modified glassy carbon electrode (GCE) and hexacyanoferrate(II) (HCF) electrocatalyst. The cyclic voltammetric results indicate that MCNTs and HCF system can remarkably enhance electrocatalytic activity toward the oxidation of captopril in acidic solutions. It is leading to a considerable improvement of the anodic peak current for captopril, and allows the development of a highly sensitive voltammetric sensor for detection of captopril in pharmaceutical and clinical samples. The investigation of captopril oxidation on the iron oxide nanoparticles modified carbon paste electrode does not show any electrocatalytic effect on the oxidation of captopril, suggesting that iron oxide impurities in the MCNTs are not the active sites in captopril sensing. Under optimized conditions on MCNTs-HCF system, the proposed method with respect to other reported electrochemical methods shows wider dynamic range (0.5–600 μM) with suitable selectivity, practical detection limit of 0.2 μM and good precision (R.S.D. <3%).     

A method of sensor fault detection and identification

A method of Bayesian belief network (BBN)-based sensor fault detection and identification is presented. It is applicable to processes operating in transient or at steady-state. A single-sensor BBN model with adaptable nodes is used to handle cases in which process is in transient. The single-sensor BBN model is used as a building block to develop a multi-stage BBN model for all sensors in the process under consideration. In the context of BBN, conditional probability data represents correlation between process measurable variables. For a multi-stage BBN model, the conditional probability data should be available at each time instant during transient periods. This requires generating and processing a massive data bank that reduces computational efficiency. This paper presents a method that reduces the size of the required conditional probability data to one set. The method improves the computational efficiency without sacrificing detection and identification effectiveness. It is applicable to model- and data-driven techniques of generating conditional probability data. Therefore, there is no limitation on the source of process information. Through real-time operation and simulation of two processes, the application and performance of the proposed BBN method are shown. Detection and identification of different sensor fault types (bias, drift and noise) are presented. For one process, a first-principles model is used to generate the conditional probability data, while for the other, real-time process data (measurements) are used.     

新型光电流传感器(OCT)

基于高压电力系统的高精度和高绝缘要求,传统的电流传感器体积大、份量重、造价及维护费用高。因此,一种安全性能好、精度高、易维护、灵活轻便的新型传感器的研究开发势在必行。光纤电流传感器(OCT)与传统的电流互感器相比具有安全性好、制造成本低、运行精度高、产品尺寸小、重量轻和维护成本低等优点,非常容易与光通讯系统联网,被人们称为电力系统新一代的CT。本文研究了基于法拉第效应的光纤电流传感器及其原理。     

A knowledge-based system for sensor selection

This paper presents a Knowledge-based system (KBS) developed to allow users, who may not be knowledgeable about sensors, to select sensors suitable for their specific needs. The KBS runs on a micro-computer. The selection criteria are user specified and are based on the desired measurement parameters. The system output includes all of the operational and dimensional parameters of the recommended sensor, price, and vendor information.     

无线传感器网络选择性传递攻击的检测和防御机制

针对无线传感器网络的选择性转发攻击,以提高恶意节点检测率和系统防御性为目标,提出了一种基于最优转发策略的随机路由算法和可信邻居节点监听的检测和防御方法。该方法通过引入距离、信任度等参数构建转发路径,同时,在路由发现和选择过程中,采用节点监听机制对恶意节点进行检测和防御处理。在Matlab环境下对该机制进行了仿真实验,并与其他方法进行了性能对比分析。实验结果表明：该方法能够在消耗相对较少能量情形下有效检测出选择性传递攻击,保持较高事件报文成功率,并且对恶意节点能做到有效的防御和处理。     

A sensitive and selective sensor for dopamine determination based on a molecularly imprinted electropolymer of o-aminophenol

A simple and reliable method was proposed for preparing a selective dopamine (DA) sensor based on a molecularly imprinted electropolymer of o-aminophenol. The sensor is selective for the determination of DA in the presence of high concentrations of ascorbic acid (AA), with a maximum molar ratio of 1/1000. The molecular imprinted (MIP) sensor was tested by cyclic voltammetry (CV) as well as differential pulse voltammetry (DPV) to verify the changes in oxidative currents of ferricyanide. In optimized conditions, DA at concentrations of 2 × 10⁻⁸ to 0.25 × 10⁻⁶ mol/L could be determined with a detection limit of 1.98 × 10⁻⁹ mol/L (S/N = 3). The MIP sensor showed high selectivity, sensitivity, and reproducibility. Determination of DA in simulated samples of dopamine hydrochloride showed good recovery.     

A novel fault-tolerant sensor system for sensor drift compensation

The conventional fault-tolerant sensor systems would fail when outputs from incorporated sensors are either noisy or drifting. This paper presents a novel real-time fault compensation method, which uses state estimation and compensation techniques, that the sensor system can perform robust measurements even when outputs from every incorporated sensor are noisy and drifting. In a simulation example, the proposed design can detect and correct the sensor errors (dc bias and drift) in real time. For the dc bias, the minimum detectable offset value is 0.1, which is the same as the standard deviation of the sensor noise. The compensated sensor output is biased at values smaller than 0.02. For the sensor drifts, the proposed method can compensate drifts for the change rate of drifts up to four times faster than that of the signal to be measured. The highest change rate of drifts, that can be compensated by this method, is determined by the standard deviation of the sensor noise.     

Low cost chemical sensor device for supersensitive pentaerythritol tetranitrate (PETN) explosives detection based on titanium dioxide nanotubes

Within the last decade there has been a great increase in the need of trace and ultra-trace explosive detection. In this report, we demonstrate a new and versatile type of chemical explosive sensors based on metal oxide nanotubes easily made, even with the need of a low budget. We describe the step-by-step procedure to fabricate a sensing chip device, beginning with the synthesis of the starting materials to the point of supersensitive measurements of PETN explosive. As a result, the whole process actually is one of the most cost-effective methods to produce explosive sensing devices reported until now. The achieved chemical sensor device will be able to detect PETN explosive down to ∼112 ppt.     

A data collection protocol for real-time sensor applications

The nature of many sensor applications as well as continuously changing sensor data often imposes real-time requirements on wireless sensor network protocols. Due to numerous design constraints, such as limited bandwidth, memory and energy of sensor platforms, and packet collisions that can potentially lead to an unbounded number of retransmissions, timeliness techniques designed for real-time systems and real-time databases cannot be applied directly to wireless sensor networks. Our objective is to design a protocol for sensor applications that require periodic collection of raw data reports from the entire network in a timely manner. We formulate the problem as a graph coloring problem. We then present TIGRA (Timely Sensor Data Collection using Distributed Graph Coloring) — a distributed heuristic for graph coloring that takes into account application semantics and special characteristics of sensor networks. TIGRA ensures that no interference occurs and spatial channel reuse is maximized by assigning a specific time slot for each node. Although the end-to-end delay incurred by sensor data collection largely depends on a specific topology, platform, and application, TIGRA provides a transmission schedule that guarantees a deterministic delay on sensor data collection.     

A dominance-based stepwise approach for sensor placement optimization

A Wireless Sensor Network (WSN) usually consists of numerous wireless devices deployed in a region of interest, each of which is capable of collecting and processing environmental information and communicating with neighboring devices. The problem of sensor placement becomes non trivial when we consider environmental factors such as terrain elevations. In this paper, we differentiate a stepwise optimization approach from a generic optimization approach, and show that the former is better suited for sensor placement optimization. Following a stepwise optimization approach, we propose a Crowd-Out Dominance Search (CODS), which makes use of terrain information and intersensor relationship information to facilitate the optimization. Finally, we investigate the effect of terrain irregularity on optimization algorithm performances, and show that the proposed method demonstrates better resistance to terrain complexity than other optimization methods.     

一种无线传感器网络冗余节点状态调度方法

覆盖质量与能量均衡是制约无线传感器网络规模与生存时间的重要因素.针对大规模无线传感器网络中,如何满足一定覆盖率条件的同时,延长网络生存时间这一问题,在LDAS基础上引入基于容忍覆盖区域的感知模型,提出了一种冗余节点的状态调度方法.该方法加入基于剩余能量的冗余判别因素,并通过预休眠节点选举机制,避免了相邻节点同时休眠或工作的情况发生,提高了覆盖效率.仿真实验证明了本方法的有效性,该方法在覆盖质量和能量均衡方面都有较好的表现.     

Poly(brilliant cresyl blue) electrogenerated on single-walled carbon nanotubes modified electrode and its application in mediated biosensing system

Single-walled carbon nanotubes (SWCNTs) functionalized with carboxylic acid groups were cast to glassy carbon electrode (GCE) to construct a three-dimensional nano-micro structured scaffold. Brilliant cresyl blue (BCB) was electropolymerized on the above-mentioned SWCNTs/GCE using continuous cycling between −0.7 and 0.9 V vs. SCE. PolyBCB yielded on SWCNTs/GCE exhibited the enhanced electrochemical redox behavior compared with that electrogenerated on bare GCE. The apparent surface coverage of PolyBCB obtained by SWCNTs/GCE was at least 10 times higher than that obtained by bare GCE, namely 4.8 × 10⁻⁹ and 3.6 × 10⁻¹⁰ mol cm⁻². The cyclic voltammograms recorded by PolyBCB/SWCNTs/GCE exhibited well-defined two peaks located at −0.25 V and −0.06 V, respectively, with a surface-controlled mechanism. In addition, morphologies of PolyBCB electrogenerated on GCE and SWCNTS/GCE were characterized by atomic force microscopy. Finally, this proposed PolyBCB/SWCNTs/GCE was used in the construction of the second-generation biosensors to hydrogen peroxide and glucose, with the enhanced analytical performance.     

A survey on sensor localization

Localization is one of the fundamental problems in wireless sensor networks (WSNs), since locations of the sensor nodes are critical to both network operations and most application level tasks. Although the GPS based localization schemes can be used to determine node locations within a few meters, the cost of GPS devices and non-availability of GPS signals in confined environments prevent their use in large scale sensor networks. There exists an extensive body of research that aims at obtaining locations as well as spatial relations of nodes in WSNs without requiring specialized hardware and/or employing only a limited number of anchors that are aware of their own locations. In this paper, we present a comprehensive survey on sensor localization in WSNs covering motivations, problem formulations, solution approaches and performance summary. Future research issues will also be discussed.     

A permanent magnetic perturbation testing sensor

A new PMP (permanent magnetic perturbation) testing sensor for NDT (nondestructive testing) was proposed for the first time based on the analysis of magnetic perturbation mechanism and PMP principle. Afterwards, the proposed PMP sensor was developed and its relevant structural parameter for design was analyzed by experiments. The comparisons among PMP, MFL (magnetic flux leakage) and ECT (eddy-current testing) sensor were carried out, which suggest that PMP is a new method. Finally, some practical engineering application cases of PMP sensor were presented, which further indicate that the proposed PMP sensor is of great practical value and the potential of wide industrial applications as a supplement of conventional NDT methods.     

A flexible layered control policy for resource allocation in a sensor grid

The paper proposes a flexible layered control policy for sensor resource allocation in a sensor grid. In order to allocate sensor resources in the system to maximize the sensor grid utility, different controllers are deployed at three levels: a job-level controller, an application group controller, and a sensor grid system controller. At the lowest levels, job-level controllers perform fast, frequent, local adaptation for optimizing a single sensor grid application at a time, while, at the highest levels, sensor grid system controllers perform less frequent control actions to optimize all applications. Sensor grid system control considers all sensor grid applications in response to large system changes at coarse time granularity. Sensor grid system control exploits the interlayer coupling of the resource layer and the application layer to achieve a system-wide optimization based on the sensor grid users’ preferences. Job-level control adapts a single application to small changes at fine granularity. The layered control system uses a set of utility functions to evaluate the performance of sensor grid applications and groups. The control system chooses control actions that would result in a higher level of utility. In the simulation, a performance evaluation of the algorithm is carried out.