•Parameters essential for stationary Pseudo reference electrodes were discussed.•Voltage stability, current noise, voltage noise and impedance were investigated.•Relationship between surface area and ...level of electrochemical noise was examined.•Solid-state Ag/AgCl electrodes exhibited optimized stability, noise and impedance.•Ag/AgCl electrode was tested against standard methods and results were validated.
Electrochemical noise measurement (ENM) is well-established as a standard test procedure for laboratory use to assist in assessing organic coatings. However, its non-destructive nature makes it particularly appealing for field use i.e. the monitoring of actual structures. A fundamental requirement for collecting valid electrochemical noise data in any situation is the use of a stable reference electrode that produces as little noise as possible. This is particularly important for organically coated substrates, where the currents being measured are very small due to attenuation of the signal by the high-impedance coating. Standard electrodes, e.g. the saturated calomel electrode, are not suitable for field measurements. In the present study, a method of assessing candidate electrodes and their noise characteristics is proposed leading to a suggestion for a suitable pseudo-reference electrode (PRE). An important conclusion is that when used as a PRE, the area of the electrode influences the noise characteristics. In general, the smaller the electrode the lower the current noise. But this has to be balanced against small electrodes having higher impedance, the latter being undesirable, so an optimization is needed.
•Fault detection and isolation of a dual spool gas turbine engine is investigated by using dynamic neural networks.•Banks of dynamic neural nets and time-delay neural nets are developed for solving ...the fault detection problem.•Results show certain engine variables have better detection capabilities as compared to others.•Fault detection performance was shown to be improved by monitoring several engine variables simultaneously.•Fault isolation uses multilayer perceptions as pattern classifier of residual signals that are generated from the fault detection phase.
The main goal of this paper is to design and develop a fault detection and isolation (FDI) scheme for aircraft gas turbine engines by using neural networks. Towards this end, first for the fault detection task two types of dynamic neural networks are used and compared to learn the engine dynamics. Specially, the dynamic neural model (DNM) and the time delay neural network (TDNN) are utilized. For both architectures a bank of neural networks is trained separately to capture the dynamic relationships among the engine measurable variables. The results show that certain engine parameters have better detection capabilities as compared to the others. Finally, the fault isolation task is accomplished by using a multilayer perception (MLP) network functioning as a pattern classifier applied to the residual signals that are generated by the two dynamic neural networks used for the purpose of the fault detection task. The simulation results do indeed substantiate and verify that our proposed FDI scheme represents a promising tool for aircraft engine diagnostics and health monitoring.
In this paper, a neural network-based fault detection and isolation (FDI) scheme is presented to detect and isolate faults in a highly nonlinear dynamics of an aircraft jet engine. Towards this end, ...dynamic neural networks (DNN) are first developed to learn the input–output map of the jet engine. The DNN is constructed based on a multi-layer perceptron network which uses an IIR (infinite impulse response) filter to generate dynamics between the input and output of a neuron, and consequently of the entire neural network. The trained dynamic neural network is then utilized to detect and isolate component faults that may occur in a dual spool turbo fan engine. The fault detection and isolation schemes consist of multiple DNNs or parallel bank of filters, corresponding to various operating modes of the healthy and faulty engine conditions. Using the residuals that are generated by measuring the difference of each network output and the measured engine output various criteria are established for accomplishing the fault diagnosis task, that is addressing the problem of fault detection and isolation of the system components. A number of simulation studies are carried out to demonstrate and illustrate the advantages, capabilities, and performance of our proposed fault diagnosis scheme.
The development of the single substrate technique presents a realistic possibility of utilising electrochemical noise measurement for on-site evaluations of corrosion behaviour. A theoretical model ...was developed to further understand the effects of reference electrodes on the acquired data to increase confidence in the technique. The model demonstrates that the reference electrodes can have a significant impact on the measurements, resulting in erroneous values if the reference electrodes are not selected carefully. Furthermore, the derived equations elucidate how to limit/remove such influence, facilitating accurate application of the single substrate technique on bare metal and coated substrates both in laboratories and in the field.
Outstanding protection of Cu by high‐quality boron nitride nanofilm (BNNF) 1–2 atomic layers thick in salt water is observed, while defective BNNF accelerates the reaction of Cu toward water. The ...chemical stability, insulating nature, and impermeability of ions through the BN hexagons render BNNF a great choice for atomic‐scale protection.
Simultaneous detection of multiple biomarkers, such as extracellular signaling molecules, is a critical aspect in disease profiling and diagnostics. Precise positioning of antibodies on surfaces, ...especially at the micro- and nanoscale, is important for the improvement of assays, biosensors, and diagnostics on the molecular level, and therefore, the pursuit of device miniaturization for parallel, fast, low-volume assays is a continuing challenge. Here, we describe a multiplexed cytokine immunoassay utilizing electron beam lithography and a trehalose glycopolymer as a resist for the direct writing of antibodies on silicon substrates, allowing for micro- and nanoscale precision of protein immobilization. Specifically, anti-interleukin 6 (IL-6) and antitumor necrosis factor alpha (TNFα) antibodies were directly patterned. Retention of the specific binding properties of the patterned antibodies was shown by the capture of secreted cytokines from stimulated RAW 264.7 macrophages. A sandwich immunoassay was employed using gold nanoparticles and enhancement with silver for the detection and visualization of bound cytokines to the patterns by localized surface plasmon resonance detected with dark-field microscopy. Multiplexing with both IL-6 and TNFα on a single chip was also successfully demonstrated with high specificity and in relevant cell culture conditions and at different times after cell stimulation. The direct fabrication of capture antibody patterns for cytokine detection described here could be useful for biosensing applications.
To investigate the role of the deep-learning (DL) method in the generation of dual-energy computed tomography (DECT) images from single-energy images for precise diagnosis of kidney stone type.
DECT ...of 23 patients was acquired, and the stone types were investigated based on the DECT software suggestions. The data were divided into two paired groups:120 kVp input and 80 kVp target and 120 kVp input and 135 kVp targets, p2p-UNet-GAN was exploited to generate the different energy images based on the common CT protocols.
The images generated of the generative adversarial network (GAN) network were evaluated based on the SSIM, PSNR, and MSE metrics, and the values were estimated as 0.85-0.95, 28-32, and 0.85-0.89 respectively. The attenuation ratio of test patient images were estimated and compared with real patient reports. The network achieved high accuracy in stone region localisation and resulted in accurate stone type predictions.
This study presents a useful method based on the DL technique to reduce patient radiation dose and facilitate the prediction of urinary stone types using single-energy CT imaging.
Enzymes are essential biocatalysts and very attractive as therapeutics. However, their functionality is strictly related to their stability, which is significantly affected by the environmental ...changes occurring during their usage or long-term storage. Therefore, maintaining the activity of enzymes is essential when they are exposed to high temperature during usage or when they are stored for extended periods of time. Here, we stabilize and protect enzymes by coencapsulating them with trehalose into polymersomes. The anhydrobiotic disaccharide preserved up to about 81% of the enzyme's original activity when laccase/trehalose-loaded nanoreactors were kept desiccated for 2 months at room temperature and 75% of its activity when heated at 50 °C for 3 weeks. Moreover, the applicability of laccase/trehalose-loaded nanoreactors as catalysts for bleaching of the textile dyes orange G, toluidine blue O, and indigo was proven. Our results demonstrate the advantages of coencapsulating trehalose within polymersomes to stabilize enzymes in dehydrated state for extended periods of time, preserving their activity even when heated to elevated temperature.
Due to their desirable elastic modulus and density that are similar to natural bone, non-toxic element containing magnesium alloys are regarded as promising bio-degradable materials. A biodegradable ...HA-particle-reinforced magnesium-matrix composite Mg–3Zn–0.2Ca-1HA (wt%) was fabricated for biomedical application by a combination of high shear solidification (HSS) and hot extrusion technology. The microstructure, mechanical properties, corrosion resistance and cell biocompatibility of the composite were subsequently investigated. In comparison with the matrix alloy, the as-cast Mg-3Zn-0.2Ca-1HA composite obtained by HSS technology exhibited a uniform and fine grained structure, further refined after a hot extrusion ratio of 36:1. The yield strength (0.2%YS), ultimate tensile strength and elongation of the extruded composite were 322 MPa, 341 MPa and 7.6%, respectively. The corrosion rate of the as-extruded Mg-3Zn-0.2Ca-1HA composite was measured to be 1.52 mm/y. Electrochemical and immersion tests showed that the corrosion resistance of the composite is slightly improved comparing to that of the matrix alloy.
Adsorption of a biofouling layer on the surface of biosensors decreases the electrochemical activity and hence shortens the service life of biosensors, particularly implantable and wearable ...biosensors. Real-time quantification of the loss of activity is important for in situ assessment of performance while presenting an opportunity to compensate for the loss of activity and recalibrate the sensor to extend the service life. Here, we introduce an electrochemical noise measurement technique as a tool for the quantification of the formation of a biofouling layer on the surface of gold. The technique uniquely affords thermodynamic and kinetic information without applying an external bias (potential and/or current), hence allowing the system to be appraised in its innate state. The technique relies on the analysis of non-faradaic current and potential fluctuations that are intrinsically generated by the interaction of charged species at the electrode surface, i.e., gold. An analytical model is extended to explain the significance of parameters drawn from statistical analysis of the noise signal. This concept is then examined in buffered media in the presence of albumin, a common protein in the blood and a known source of a fouling layer in biological systems. Results indicate that the statistical analysis of the noise signal can quantify the loss of electrochemical activity, which is also corroborated by impedance spectroscopy as a complementary technique.
PDF
