Pt nanoparticles: Heat treatment-based preparation and Ru(bpy)(3)(2+)-mediated formation of aggregates that can form stable films on bare solid electrode surfaces for solid-state electrochemiluminescence detection

A simple thermal process for the preparation of small Pt nanoparticles is presented, carried out by heating a H-2-PtCl6/3- thiophenemalonic acid aqueous solution. The following treatment of such colloidal Pt solution with Ru( bpy)(3)(2+) causes the assembly of Pt nanoparticles into aggregates. Most importantly, directly placing such aggregates on bare solid electrode surfaces can produce very stable films exhibiting excellent electrochemiluminescence behaviors.

Capillary electrophoresis with amperometric detection of curcumin in Chinese herbal medicine pretreated by solid-phase extraction

In the present study, curcumin from Chinese herbal medicine turmeric was determined by capillary electrophoresis with amperometric detection (CE-AD) pretreated by a self-designed, simple, inexpensive solid-phase extraction (SPE) cartridge based on the material of tributyl phosphate resin. An average concentration factor of 9 with the recovery of >80% was achieved when applied to the analysis of curcumin in extracts of turmeric. Under the optimized CE-AD conditions: a running buffer composed of 15 mM phosphate buffer at a pH 9.7, separation voltage at 16 W, injection for 6 s at 9 W and detection at 1.20 V, CE-AD with SPE exhibited low detection limit as 3 - 10(-8) mol/l (SIN = 3), high efficiency of 1.0(.)10(5) N, linear range of 7(.)10(-4) -3(.)10(-6) mol/l (r = 0.9986) for curcumin extracted from light petroleum. The method developed resulted in enhancement of the detection sensitivity and reduction of interference from sample matrix in complicated samples and exhibited the potential application for routine analysis, especially in food, because a relatively complete process of sample treatment and analysis was described.

Amperometric tyrosinase biosensor based on a sol-gel-derived titanium oxide-copolymer composite matrix for detection of phenolic compounds

A new type of tyrosinase biosensor was developed for the detection of phenolic compounds, based on the immobilization of tyrosinase in a sol-gel-derived composite matrix that is composed of titanium oxide sol and a grafting copolymer of poly(vinyl alcohol) with 4-vinylpyridine. Tyrosinase entrapped in the composite matrix can retain its activity to a large extent owing to the good biocompatibility of the matrix. The parameters of the fabrication process and the variables of the experimental conditions for the enzyme electrode were optimized. The resulting sensor exhibited a fast response (20 s), high sensitivity (145.5 muA mmol(-1) 1) and good storage stability. A detection limit of 0.5 muM catechol was obtained at a signal-to-noise ratio of 3.

Capacitive detection of glucose using molecularly imprinted polymers

A novel glucose biosensor based on capacitive detection has been developed using molecularly imprinted polymers. The sensitive layer was prepared by electropolymerization of o-phenylenediamine on a gold electrode in the presence of the template (glucose). Cyclic voltammetry and capacitive measurements monitored the process of electropolymerization. Surface uncovered areas were plugged with 1-dodecanethiol to make the layer dense, and the insulating properties of the layer were studied in the presence of redox couples. The template molecules and the nonbound thiol were removed from the modified electrode surface by washing with distilled water. A capacitance decrease could be obtained after injection of glucose. The electrode constructed similarly but with ascorbic acid or fructose only showed a small response compared with glucose. The stability and reproducibility of the biosensor were also investigated. (C) 2001 Elsevier Science B.V. All rights reserved.

Electrocatalytic oxidation and flow amperometric detection of hydrazine at an electropolymerized 4-vinylpyridine/palladium film electrode

A poly(4-vinyl)pyridine (PVP)/Pd film electrode was constructed for the electrocatalytic detection of hydrazine. The preparation of the PVP/GC electrode was performed by electropolymerization of the monomer 4-vinylpyridine onto the surface of a glassy carbon electrode. Subsequently, palladium is electrodeposited onto the polymer modified electrode surface. The ion-exchange function of PVP polymer is helpful to this process in view of the tetrachlorapalladate anion. Compared with the Pd/GC electrode, the modified electrode displays a better mechanical stability in a flowing stream. The PVP/Pd film electrode exhibits higher sensitivity when detecting hydrazine with a detection limit of 0.026 ng (S/N=3).

DETERMINATION OF CYSTEINE AND REDUCED GLUTATHIONE IN HUMAN PLASMA BY LIQUID-CHROMATOGRAPHY WITH PULSED AMPEROMETRIC ELECTROCHEMICAL DETECTION USING A PLATINUM-PARTICLES MODIFIED GLASSY-CARBON ELECTRODE

An assay procedure utilizing pulsed amperometric detection at a platinum-particles modified electrode has been developed for the determination of cysteine and glutathione in blood samples following preliminary separation by reversed-phase liquid chromatography. A chemically modified electrode (CME) constructed by unique electroreduction from a platinum-salt solution to produce dispersed Pt particles on a glassy carbon surface was demonstrated to catalyze the electo-oxidation of sulfhydryl-containing compounds: DL-cysteine (CYS), reduced glutathione (GSH). When used as the sensing electrode in flow-system pulsed-amperometric detection (PAD), electrode fouling could be avoided using a waveform in which the cathodic reactivation process occurred at a potential of - 1.0 V vs. Ag/AgCl to achieve a cathodic desorption of atomic sulfur. A superior detection limit for these free thiols was obtained at a Pt particle-based GC electrode compared with other methods; this novel dispersed Pt particles CME exhibited high electrocatalytic stability and activity when it was employed as an electrochemical detector in FIA and HPLC for the determination of those organo-sulfur compounds.

ELECTROCHEMICAL DETECTION OF COBALT IN HAIR FOLLOWING ON-COLUMN DERIVATIZATION WITH 1-(2-PYRIDYLAZO)-2-NAPHTHOL-6-SULFONIC ACID AND REVERSED-PHASE LIQUID-CHROMATOGRAPHY

A method for the specific determination of cobalt based on reversed-phase liquid chromatography with amperometric detection via on-column complex formation has been developed. A water-soluble chelating agent, 1-(2-pyridylazo)-2-naphthol-6-sulphonic acid (PAN-6S), is added to the mobile phase and aqueous cobalt solutions are injected directly into the column to form in situ the cobalt-PAN-6S chelate, which is then separated from other metal PAN-6S chelates and subjected to reductive amperometric detection at a moderate potential of -0.3 V. Because the procedure eliminates the interference of oxygen and depresses the electrochemical reduction of the mobile phase-containing ligand PAN-6S, by virtue of the quasi:reversible electrode process of the cobalt-PAN-6S complex, a low detection limit of 0.06 ng can be readily obtained. Interference effects were examined for sixteen common metal species, and at a 5- to 8000-fold excess by mass no obvious interference was observed. The feasibility of the method as an approach to the specific analysis of cobalt in a hair sample has been demonstrated.

Rapid and quantitative detection of the microbial spoilage of meat by Fourier Transform Infrared Spectroscopy and machine learning

Ellis, D. I., Broadhurst, D., Kell, D. B., Rowland, J. J., Goodacre, R. (2002). Rapid and quantitative detection of the microbial spoilage of meat by Fourier Transform Infrared Spectroscopy and machine learning. ? Applied and Environmental Microbiology, 68, (6), 2822-2828 Sponsorship: BBSRC

Is a Detector Only Good for Detection?

A common design of an object recognition system has two steps, a detection step followed by a foreground within-class classification step. For example, consider face detection by a boosted cascade of detectors followed by face ID recognition via one-vs-all (OVA) classifiers. Another example is human detection followed by pose recognition. Although the detection step can be quite fast, the foreground within-class classification process can be slow and becomes a bottleneck. In this work, we formulate a filter-and-refine scheme, where the binary outputs of the weak classifiers in a boosted detector are used to identify a small number of candidate foreground state hypotheses quickly via Hamming distance or weighted Hamming distance. The approach is evaluated in three applications: face recognition on the FRGC V2 data set, hand shape detection and parameter estimation on a hand data set and vehicle detection and view angle estimation on a multi-view vehicle data set. On all data sets, our approach has comparable accuracy and is at least five times faster than the brute force approach.

Development of germanium/silicon integration for near infrared detection

Silicon (Si) is the base material for electronic technologies and is emerging as a very attractive platform for photonic integrated circuits (PICs). PICs allow optical systems to be made more compact with higher performance than discrete optical components. Applications for PICs are in the area of fibre-optic communication, biomedical devices, photovoltaics and imaging. Germanium (Ge), due to its suitable bandgap for telecommunications and its compatibility with Si technology is preferred over III-V compounds as an integrated on-chip detector at near infrared wavelengths. There are two main approaches for Ge/Si integration: through epitaxial growth and through direct wafer bonding. The lattice mismatch of ~4.2% between Ge and Si is the main problem of the former technique which leads to a high density of dislocations while the bond strength and conductivity of the interface are the main challenges of the latter. Both result in trap states which are expected to play a critical role. Understanding the physics of the interface is a key contribution of this thesis. This thesis investigates Ge/Si diodes using these two methods. The effects of interface traps on the static and dynamic performance of Ge/Si avalanche photodetectors have been modelled for the first time. The thesis outlines the original process development and characterization of mesa diodes which were fabricated by transferring a ~700 nm thick layer of p-type Ge onto n-type Si using direct wafer bonding and layer exfoliation. The effects of low temperature annealing on the device performance and on the conductivity of the interface have been investigated. It is shown that the diode ideality factor and the series resistance of the device are reduced after annealing. The carrier transport mechanism is shown to be dominated by generation–recombination before annealing and by direct tunnelling in forward bias and band-to-band tunnelling in reverse bias after annealing. The thesis presents a novel technique to realise photodetectors where one of the substrates is thinned by chemical mechanical polishing (CMP) after bonding the Si-Ge wafers. Based on this technique, Ge/Si detectors with remarkably high responsivities, in excess of 3.5 A/W at 1.55 μm at −2 V, under surface normal illumination have been measured. By performing electrical and optical measurements at various temperatures, the carrier transport through the hetero-interface is analysed by monitoring the Ge band bending from which a detailed band structure of the Ge/Si interface is proposed for the first time. The above unity responsivity of the detectors was explained by light induced potential barrier lowering at the interface. To our knowledge this is the first report of light-gated responsivity for vertically illuminated Ge/Si photodiodes. The wafer bonding approach followed by layer exfoliation or by CMP is a low temperature wafer scale process. In principle, the technique could be extended to other materials such as Ge on GaAs, or Ge on SOI. The unique results reported here are compatible with surface normal illumination and are capable of being integrated with CMOS electronics and readout units in the form of 2D arrays of detectors. One potential future application is a low-cost Si process-compatible near infrared camera.

Application of signal detection methods to fisheries management

The abundance of many commercially important fish stocks are declining and this has led to widespread concern on the performance of traditional approach in fisheries management. Quantitative models are used for obtaining estimates of population abundance and the management advice is based on annual harvest levels (TAC), where only a certain amount of catch is allowed from specific fish stocks. However, these models are data intensive and less useful when stocks have limited historical information. This study examined whether empirical stock indicators can be used to manage fisheries. The relationship between indicators and the underlying stock abundance is not direct and hence can be affected by disturbances that may account for both transient and persistent effects. Methods from Statistical Process Control (SPC) theory such as the Cumulative Sum (CUSUM) control charts are useful in classifying these effects and hence they can be used to trigger management response only when a significant impact occurs to the stock biomass. This thesis explores how empirical indicators along with CUSUM can be used for monitoring, assessment and management of fish stocks. I begin my thesis by exploring various age based catch indicators, to identify those which are potentially useful in tracking the state of fish stocks. The sensitivity and response of these indicators towards changes in Spawning Stock Biomass (SSB) showed that indicators based on age groups that are fully selected to the fishing gear or Large Fish Indicators (LFIs) are most useful and robust across the range of scenarios considered. The Decision-Interval (DI-CUSUM) and Self-Starting (SS-CUSUM) forms are the two types of control charts used in this study. In contrast to the DI-CUSUM, the SS-CUSUM can be initiated without specifying a target reference point (‘control mean’) to detect out-of-control (significant impact) situations. The sensitivity and specificity of SS-CUSUM showed that the performances are robust when LFIs are used. Once an out-of-control situation is detected, the next step is to determine how much shift has occurred in the underlying stock biomass. If an estimate of this shift is available, they can be used to update TAC by incorporation into Harvest Control Rules (HCRs). Various methods from Engineering Process Control (EPC) theory were tested to determine which method can measure the shift size in stock biomass with the highest accuracy. Results showed that methods based on Grubb’s harmonic rule gave reliable shift size estimates. The accuracy of these estimates can be improved by monitoring a combined indicator metric of stock-recruitment and LFI because this may account for impacts independent of fishing. The procedure of integrating both SPC and EPC is known as Statistical Process Adjustment (SPA). A HCR based on SPA was designed for DI-CUSUM and the scheme was successful in bringing out-of-control fish stocks back to its in-control state. The HCR was also tested using SS-CUSUM in the context of data poor fish stocks. Results showed that the scheme will be useful for sustaining the initial in-control state of the fish stock until more observations become available for quantitative assessments.

The use of fault detection and diagnostics to reduce air handling unit energy consumption

The contribution of buildings towards total worldwide energy consumption in developed countries is between 20% and 40%. Heating Ventilation and Air Conditioning (HVAC), and more specifically Air Handling Units (AHUs) energy consumption accounts on average for 40% of a typical medical device manufacturing or pharmaceutical facility’s energy consumption. Studies have indicated that 20 – 30% energy savings are achievable by recommissioning HVAC systems, and more specifically AHU operations, to rectify faulty operation. Automated Fault Detection and Diagnosis (AFDD) is a process concerned with potentially partially or fully automating the commissioning process through the detection of faults. An expert system is a knowledge-based system, which employs Artificial Intelligence (AI) methods to replicate the knowledge of a human subject matter expert, in a particular field, such as engineering, medicine, finance and marketing, to name a few. This thesis details the research and development work undertaken in the development and testing of a new AFDD expert system for AHUs which can be installed in minimal set up time on a large cross section of AHU types in a building management system vendor neutral manner. Both simulated and extensive field testing was undertaken against a widely available and industry known expert set of rules known as the Air Handling Unit Performance Assessment Rules (APAR) (and a later more developed version known as APAR_extended) in order to prove its effectiveness. Specifically, in tests against a dataset of 52 simulated faults, this new AFDD expert system identified all 52 derived issues whereas the APAR ruleset identified just 10. In tests using actual field data from 5 operating AHUs in 4 manufacturing facilities, the newly developed AFDD expert system for AHUs was shown to identify four individual fault case categories that the APAR method did not, as well as showing improvements made in the area of fault diagnosis.

Highly sensitive surface enhanced Raman scattering (SERS) detection platforms formed by large area self-assembled Au nanorod arrays

This thesis explores a new method to fabricate SERS detection platforms formed by large area self-assembled Au nanorod arrays. For the fabrication of these new SERS platforms a new droplet deposition method for the self-assembly of Au nanorods was developed. The method, based in the controlled evaporation of organic suspensions of Au nanorods, was used for the fabrication of horizontal and vertical arrays of Au nanorods over large areas (100μm2). The fabricated nanorods arrays showed a high degree of order measured by SEM and optical microscopy over mm2 areas, but unfortunately they detached from the support when immersed in any analyte solutions. In order to improve adhesion of arrays to the support and clean off residual organic matter, we introduced an additional stamping process. The stamping process allows the immobilization of the arrays on different flexible and rigid substrates, whose feasibility as SERS platforms were tested satisfactory with the model molecule 4ABT. Following the feasibility study, the substrates were used for the detection of the food contaminant Crystal Violet and the drug analogue Benzocaine as examples of recognition of health menaces in real field applications.

Assessing segmentation processes by click detection: online measure of statistical learning, or simple interference?

Statistical learning can be used to extract the words from continuous speech. Gómez, Bion, and Mehler (Language and Cognitive Processes, 26, 212–223, 2011) proposed an online measure of statistical learning: They superimposed auditory clicks on a continuous artificial speech stream made up of a random succession of trisyllabic nonwords. Participants were instructed to detect these clicks, which could be located either within or between words. The results showed that, over the length of exposure, reaction times (RTs) increased more for within-word than for between-word clicks. This result has been accounted for by means of statistical learning of the between-word boundaries. However, even though statistical learning occurs without an intention to learn, it nevertheless requires attentional resources. Therefore, this process could be affected by a concurrent task such as click detection. In the present study, we evaluated the extent to which the click detection task indeed reflects successful statistical learning. Our results suggest that the emergence of RT differences between within- and between-word click detection is neither systematic nor related to the successful segmentation of the artificial language. Therefore, instead of being an online measure of learning, the click detection task seems to interfere with the extraction of statistical regularities.

Mutual information performance of differential MPSK detection over time-varying channels

This paper provides mutual information performance analysis of multiple-symbol differential WSK (M-phase shift keying) over time-correlated, time-varying flat-fading communication channels. A state space approach is used to model time correlation of time varying channel phase. This approach captures the dynamics of time correlated, time-varying channels and enables exploitation of the forward-backward algorithm for mutual information performance analysis. It is shown that the differential decoding implicitly uses a sequence of innovations of the channel process time correlation and this sequence is essentially uncorrelated. It enables utilization of multiple-symbol differential detection, as a form of block-by-block maximum likelihood sequence detection for capacity achieving mutual information performance. It is shown that multiple-symbol differential ML detection of BPSK and QPSK practically achieves the channel information capacity with observation times only on the order of a few symbol intervals