Narrow Results

The corrosion performance of plasma sprayed alumina–40wt.% titania (A40T) coated high-density graphite was investigated in molten LiCl–KCl eutectic salt at $600^{\circ }$C for periods of 500, 1000, and 2000h under argon atmosphere. The microstructural and compositional investigations of corrosion-tested A40T coatings by scanning electron microscopy and energy dispersive X-ray spectroscopy showed that the samples exhibited better corrosion resistance up to 500h. The poor corrosion behavior and failure of A40T coating from graphite substrate in the long-term (1000 and 2000h) immersion was discussed in detail based on the microstructure and composition analysis. The phases existing in the as-sprayed coating ($\beta$-Al₂TiO₅, $\gamma$-Al₂O₃, R-TiO₂, and $\alpha$-Al₂O₃) remained in the detached coating after 1000h exposure to the molten salt. The reaction between molten salt and A40T coating was not evident from XRD analysis. A40T coatings with chromium carbide–nichrome (Cr₃C₂–NiCr) bond coat showed complete spallation of the top coating and oxidation of the bond coat as evident from the X-ray diffraction analysis. Detachment of the A40T coating occurred due to the penetration of the molten salt into the coating through the voids and pores present on the surface, which weakened the adhesion strength between the substrate and the A40T coating or top coat-bond coat interfaces.

Regarding biocompatibility, toxicity, degradation, and interaction with body cells, the materials as well as fabrication process used for biomedical implants are crucial aspects. Implant materials are chosen in accordance with these criteria. The most recent medical implants are made of materials, i.e. stainless steel, Co–Cr and titanium alloys. Although these conventional implant materials generate hazardous ions and have a stress shield effect in many medical implant situations, the implants must be removed from the body within a certain period of time. In order to avoid the need for implant removal, researchers advise using magnesium metal matrix composite (Mg-MMC) as an implant material. Magnesium composites are subjected to a variety of engineering processes to enhance their mechanical and biocompatibility properties, including the addition of reinforcement, treating the surface, and changing the synthesis processes. The solid-state “friction stir process” is discussed for the fabrication of magnesium metal matrix composites. The influence of various reinforcing materials’, process parameters and reinforcing strategies are summarized in this review study with respect to the microstructure, mechanical characteristics, and corrosion behavior of biodegradable magnesium matrix composites. This study provides an importance of magnesium-based composites for biomedical implants and the degradation behavior reduces the secondary activities to remove implants.

Recently, metal-supported solid oxide fuel cells (MS–SOFCs) have been in the spotlight again for their design, thanks to their inexpensive materials, robustness, resistance to thermal cycling, and benefits of manufacturability. Hydrogen energy electrochemical devices, like MS–SOFCs, have a lot of potential. They are very ideal substitutes for solid oxide fuel cells (SOFCs) that utilize electrolytes or ceramic electrodes as their carrier basis, because of their greater durability, mechanical stability, heat cycle resistance, and rapid startup time. Even though MS–SOFCs have several advantages over conventional ceramic-based SOFCs, researchers are still struggling to perfect them due to issues such as selecting the appropriate metal-based material for the electrodes (anode, electrode) and comprehending how they deteriorate. This limitation might be evaded by optimizing the pore former filling and the diameter of the metallic supports (130–250$\mu$m). Optimization methods, such as particle swarm optimization, as well as penetration cycle numbers (1–15), as well as the impacts of fire temperatures (400–900^∘C), were investigated to aid in optimizing the catalyst infiltration procedure. The enhanced cell outperformed its original performance by a factor of three, reaching an ideal energy density of 0.9W cm${}^{-2}$ at 700^∘C when powered by hydrogen. The improved cells had a 2% degradation rate per 100h at 550^∘C, a 4.5% degradation rate at 600^∘C, and a 5.5% degradation rate at 700^∘C. We used electrochemical impedance spectroscopy and scanning electron microscopy to look at the catalyst’s mass shipping, coarsening, and chromium poisoning.

The contamination of aquatic systems by tetracycline hydrochloride (TC) has emerged as an urgent environmental concern necessitating immediate intervention. Herein, a mechanochemical approach was utilized to synthesize a FeOOH@AC nanocomposite through the co-grinding of goethite (FeOOH), hydroxylamine hydrochloride (NH₂OH⋅HCl), and activated carbon (AC). The FeOOH@AC nanocomposite acted as a catalyst for the activation of sodium persulfate (PS), producing strong oxidizing radicals for the removal of TC from water. The results demonstrated that the physicochemical properties and crystal structure of FeOOH were altered via ball-milling treatment. The activation of PS-generated sulfate radicals (SO${}_4^{\cdot -})$ and hydroxyl radicals (${}^{\cdot }$OH) synergistically degraded TC. Additionally, the degradation rate of TC in a 50mg/L solution reached 91.26% after the addition of FeOOH@AC and PS. This work offers a theoretical and technical foundation for the mechanochemical ball milling preparation of FeOOH@AC, facilitating PS activation for the degradation of TC in water.

As a newly emerging catalysis, tribocatalysis is receiving more and more attention with regard to the criteria to fabricate or choose materials as catalysts for it. In this study, two different commercial silicon (Si) powders, Si30 and Si300, were adopted as catalysts in tribocatalytic degradation of organic dyes. Only round nanoparticles from 30 to 100nm were observed in Si30, while some highly large and irregular particles, as large as 1000nm × 500nm and with a roughly flat major surface, could be observed in Si300. Stimulated through magnetic stirring using Teflon magnetic rotary disks, as much as 95% of 20 mg/L rhodamine B (RhB) solution and 97% of 20 mg/L methyl orange (MO) solution were degraded by Si300 after 3h and 50min, respectively; while only 73% of RhB and 83% of MO were degraded by Si30 after 5h and 4h, respectively. EPR spectra showed that more superoxide and hydroxyl radicals were generated by Si300 under magnetic stirring. It is proposed that in those large particles in Si300, their large flat major surfaces dramatically enhance their absorption of mechanical energy through friction and there are much less lattice defects to hinder electrons and holes from diffusing to the surface, which both results in the contrasting tribocatalytic degradations of organic dyes between Si300 and Si30. These findings reveal a huge difference in tribocatalytic performance among different materials of the same composition.

The investigation of the degradation of two commercially available dyes (Remazol Turquoise Blue and Everzol Turquoise Blue) by the lignin-degrading fungus Phanerochaete chrysosporium and comparison with that of a phthalocyanine whose structure is known (Heligon Blue) are presented. Atomic absorption showed a large release of copper from the biomass at day 7. Polarography served to speciate the copper present in the supernatant. Day 5 sees the complete disappearance of the main dye peak with the release of free copper into the supernatant. Day 7 sees a large increase in the free copper signal with two other electroactive species also present in the supernatant, all of which are seen to decrease at day 8. Visible spectroscopy shows that the main decolourization takes place between day 4 and day 6, with complete decolourization occurring at day 7. HPLC analysis again confirms the above results, with possible degradation products detected at 254 nm occurring at 3.621 and 4.170 min at day 7 which may well correlate with those found in polarographic analysis at –1050 and –1150 mV. Day 7 also sees a large increase in a peak at 2.744 min.

In order to understand the effect of natural environmental factors on the carbon fiber/epoxy composites, the degradation of carbon fiber/epoxy composite was studied. The specimens were exposed in a Xe lamp chamber and suffered to ultraviolet light radiation, temperature and/or humidity conditions. The results show that the radiation, temperature and/or humidity could cause extensive corrosion to the surface and interior of the carbon/epoxy composite and attack the interface between matrix and carbon fiber, resulting in an obvious reduction of the transverse tensile strength and interlaminar shear strength. On the contrary, the longitudinal transverse shear strength was not affected much by the radiation, temperature and/or humidity. The results indicate that the radiation, temperature and/or humidity can result in the corrosion of the carbon/epoxy composite and consequently affect the mechanical properties of the carbon/epoxy composite partially.

A thin film transistor (TFT) characteristics measuring and bias stress applying system using an alternating current (AC) pulse sequence similar to a real driving pulse was developed to study the properties of hydrogenated amorphous-silicon (a-Si:H) TFTs under real operating conditions. Using this system, the application of a gate bias stress and the measurement of source-to-drain current were performed successfully. Degradation of the TFT transfer curve depended on the ratio of on time to off time for a fixed on time; a longer off time made the shift of threshold voltage V_TH smaller. In addition, degradation of transfer curves depended on the frequency of the driving pulse; a higher frequency pulse produced a larger degradation. These results could originate from the dependence of the direction of V_TH shift on the polarity of the gate bias, and the differences of injection barrier height and the mobility of the electron and hole. Using the AC driving pulse and the transient measurement system proposed in this study may be useful in understanding the response of TFTs under real operating conditions.

The difficulty of recycling and low photocatalytic efficiency in the visible light significantly limit the use of nano-TiO₂ in water pollution control. In this work, Bucky papers (BPs), which play a vital role for adsorption of pollutants and transfer of electrons, are introduced as substrates to fabricate and anchor TiO₂ nanorods by a facile hydrothermal method. The photocatalytic properties of the TiO₂ and BP composites (TiO₂@BP) are studied by photodegrading methylene blue in water solutions. It is found that TiO₂@BP possesses four times photocatalytic efficiency for methylene blue of TiO₂@Si under ultraviolet light irradiation and 10 times under visible light irradiation. This is considered to be attributed to the synergic effect of TiO₂@BP system and surface defects of TiO₂ nanorods. The TiO₂@BP also shows a stable photocatalytic property even after five cyclic photocatalytic degradation. This study indicates that TiO₂@BP is a promising candidate for photocatalytic applications, which provides a reference for further research on synthesis of reusable photocatalysts with higher efficiency.

Porous materials are promising candidates for the removal of organic pollutants from different water bodies. Among porous materials, cryogels are more attractive candidates due to their macro-porosity and rapid adsorption. This work evaluated the fabrication and adsorption capability of macro-porous Gum Arabic-based Cryogel. The fabricated Gum Arabic cryogel was modified and protonated to the protonated modified Gum Arabic Cryogel to compare its adsorption capacities for three different dyes. The successful fabrication of cryogel was confirmed by Fourier Transform Infrared spectroscopy, Differential Scanning Calorimetry, Thermal gravimetric analysis and Scanning Electron Microscopy. The protonated modified Gum Arabic Cryogel showed enhanced adsorption capability towards subjected dyes by following second-order rate kinetics. These cryogels can be employed as an efficient adsorbent to remove toxic contaminants from wastewater effluents.

Briefly, we reviewed the latest progress in energy conversion efficiency and degradation rate of the quantum dot (QD) solar cells. QDs are zero dimension nanoparticles with tunable size and accordingly tunable band gap. The maximum performance of the most advanced QD solar cells was reported to be around 10%. Nevertheless, majority of research groups do not investigate the stability of such devices. QDs are cheaper replacements for silicon or other thin film materials with a great potential to significantly increase the photon conversion efficiency via two ways: (i) creating multiple excitons by absorbing a single hot photon, and (ii) formation of intermediate bands (IBs) in the band gap of the background semiconductor that enables the absorption of low energy photons (two-step absorption of sub-band gap photons). Apart from low conversion efficiency, QD solar cells also suffer from instability under real operation and stress conditions. Strain, dislocations and variation in size of the dots (under pressure of the other layers) are the main degradation resources. While some new materials (i.e. perovskites) showed an acceptable high performance, the QD devices are still inefficient with an almost medium rate of 4% (2010) to 10% (2015).

The layered Bi₃O₄Br nanoplates were synthesized through a simple calcination process, which can simultaneously harvest visible light and ultrasonic vibration to realize the effective piezo-photocatalysis. The piezo-photocatalysis over the Bi₃O₄Br leads to a great enhancement in catalytic efficiency with respect to the pure photocatalysis or piezocatalysis. The apparent rate constant of piezo-photocatalysis for the degradation of MO achieves to be 0.008 min${}^{-1}$, which is 5.20 and 1.51 times as high as the individual piezocatalysis and photocatalysis, respectively. This enhancement would be attributed to the built-in piezoelectric field induced by ultrasonic vibration facilitating the separation of charge carriers in photoexcited Bi₃O₄Br.

In this paper, we propose an improved version of the neighbor embedding super-resolution (SR) algorithm proposed by Chang et al. [Super-resolution through neighbor embedding, in Proc. 2004 IEEE Computer Society Conf. Computer Vision and Pattern Recognition(CVPR), Vol. 1 (2004), pp. 275–282]. The neighbor embedding SR algorithm requires intensive computational time when finding the K nearest neighbors for the input patch in a huge set of training samples. We tackle this problem by clustering the training sample into a number of clusters, with which we first find for the input patch the nearest cluster center, and then find the K nearest neighbors in the corresponding cluster. In contrast to Chang’s method, which uses Euclidean distance to find the K nearest neighbors of a low-resolution patch, we define a similarity function and use that to find the K most similar neighbors of a low-resolution patch. We then use local linear embedding (LLE) [S. T. Roweis and L. K. Saul, Nonlinear dimensionality reduction by locally linear embedding, Science290(5500) (2000) 2323–2326] to find optimal coefficients, with which the linear combination of the K most similar neighbors best approaches the input patch. These coefficients are then used to form a linear combination of the K high-frequency patches corresponding to the K respective low-resolution patches (or the K most similar neighbors). The resulting high-frequency patch is then added to the enlarged (or up-sampled) version of the input patch. Experimental results show that the proposed clustering scheme efficiently reduces computational time without significantly affecting the performance.

In this paper, we propose a new circuit level hardening techniques that can decrease the sensitivity of Static Random Access Memory (SRAM) cells to radiation induced Single Event Upsets (SEUs). Five different types of 32 nm double gate (DG)-FinFET-based SRAM cells are analyzed. Proposed SRAM cell outperforms over the unhardened SRAM when exposed to radiation. This is primarily due to the modification of the source potential used to reduce the effect of SEU without affecting normal operation. Static Noise Margin (SNM), Read Noise Margin (RNM), Write Noise Margin (WNM) and Power Delay Product (PDP) are the performance metrics computed for each type of SRAM cell. Effect of back gate voltage and back gate oxide thickness variation on device characteristic show detrimental effects on radiation hardened capabilities of a device. Benchmarking is done against DICE latch and it is found that as compared to DICE latch proposed DG-FinFET SRAM has low transistor count, less area, low recovery time and fault tolerance to internal as well as external nodes.

This paper presents a non-sampling based method for the simultaneous evaluation of quality and performance reliability of engineering systems with multiple time-variant responses due to multiple degrading components. This work provides a platform for robust design of degrading systems. The system performance degradations are related to component degradations using mechanistic models. The system soft failure is defined as the non-conformance of any response with respect to critical levels and such relations are easily modeled as time dependent limit-state functions. Then, for discrete time it is shown that an incremental failure set that emerges from a safe region can be written using only a pair of successive system instantaneous failure sets. The cumulative distribution function of soft failure is built by summing the incremental failure probabilities. A practical implementation of the proposed method can be manifest by first-order reliability methods (FORM) and second-order bounds. The proposed method can be used to assess initial quality and performance reliability of systems with combinations of designated means and tolerances. Examples of electro mechanical systems show the details of the formulation and the potential of the approach. Error sources and their magnitudes are discussed.

Many offshore oil and gas installations in the North Sea are approaching the end of their designed lifetimes. Technological improvements and higher oil prices have developed favorable conditions for more oil recovery from these existing installations. However, in most cases, an extended oil production period does not justify investment in new installations. Therefore cost-effective maintenance of the existing platform infrastructure is becoming very important.

In this paper, an inspection frequency optimization model has been developed which can be used effectively by the inspection and maintenance personnel in the industry to estimate the number of inspections/optimum preventive maintenance time required for a degrading component at any age or interval in its lifecycle at a minimum total maintenance cost. The model can help in planning inspections and maintenance intervals for different components of the platform infrastructure. The model has been validated by a case study performed on flowlines installed on the top side of an offshore oil and gas platform in the North Sea. Reliability analysis has been carried out to arrive at the best inspection frequency for the flowline segments under study.

Conventionally, reliability prediction of electronic components is carried out using standard handbooks such as MIL STD 217 plus, Telcordia, etc. But these methods fail to provide a realistic estimate of reliability for upcoming technologies. Currently, electronic reliability prediction is moving towards applying the Physics of Failure approach which considers information on process, technology, fabrication techniques, materials used, etc. Industries employ different technologies like CMOS, BJT and BICMOS for various applications. The possibility of chance of failure at interdependencies of materials, processes, and characteristics under operating conditions is the major concern which affects the performance of the devices. They are characterized by several failure mechanisms at various stages such as wafer level, interconnection, etc. For this, the dominant failure mechanisms and stress parameters needs to be identified.

Optocouplers are used in input protection of several instrumentation systems providing safety under over-stress conditions. Hence, there is a need to study the reliability and safety aspects of optocouplers. Design of experiments is an efficient and prominent methodology for finding the reliability of the item, as the experiment provides a proof for the hypothesis under consideration. One of the important techniques involved is Taguchi method which is employed for finding the prominent failure mechanisms in semiconductor devices. By physics of failure approach, the factors that are affecting the performance on both environmental and electrical parameters with stress levels for optocouplers are identified. By constructing a 2-stage Taguchi array with these parameters where output parameters decides the effect of top two dominant failure mechanisms and their extent of chance of failure can be predicted. This analysis helps us in making the appropriate modifications considering both the failure mechanisms for the reliability growth of these devices. This paper highlights the application of design of experiments for finding the dominant failure mechanisms towards using physics of failure approach in electronic reliability prediction of optocouplers for application of instrumentation.

Some life tests result in few or no failures. In such cases, we can, and should, consider using degradation measurements to assess reliability. In real world, product degradation is a stochastic process. Since such degradation is often seen as a monotonous process, literature widely uses Gamma Process to describe and quantify degradation. However, in these publications, scale parameter is considered constant over time and results under this assumption may have big deviation from the actual measurements under nonlinear condition. The purpose of this paper is to improve Gamma Process method to fit a broader class of degradation models. Firstly, we use MLE to estimate the parameters under the timely constant-scale-parameter assumption and analyze why the model does not fit data well. Then we propose an improved model to improve the method and use Monte Carlo simulation to verify the validity of the improved method.

Condition-based maintenance (CBM) optimization involves considering inherent uncertainties and external uncertainties. Since computational complexity increases exponentially with the number of degradation uncertainties and stages, scenario reduction aims to select small set of typical scenarios which can maintain the probability distributions of outputs of possible scenarios. A novel scenario reduction method, 3D-outputs-clustering scenario reduction (3DOCS), is presented by considering the impacts of uncertainty parameters on the output performance for CBM optimization which have been overlooked. Since the output performance for CBM is much more essential than the inputs, the proposed scenario reduction method reduces degradation scenarios by $K$-means clustering of the multiple outputs of degradations scenarios for CBM. It minimizes the probabilistic distribution distances of outputs between original and selected scenarios. Case studies show that 3DOCS has advantages as a smaller distance of output performance of selected scenarios compared to that of initial scenarios.

The application of reliability-based design optimization (RBDO) to degrading systems is challenging because of the continual interplay between calculating time-variant reliability (to ensure reliability policies are met) and moving the design point to optimize various objectives, such as cost, weight, size and so forth. The time needed for Monte Carlo Simulation (MCS) is lengthy when reliability calculations are required for each iteration of the design point. The common methods used to date to improve efficiency have some shortcomings: First, most approaches approximate probability via a method that invokes the most-likely failure point (MLFP), and second, tolerances are almost always excluded from the list of design parameters (hence only so-called parameter design is performed), and, without tolerances, true monetary costs cannot be determined, especially in manufactured systems. Herein, the efficiency of RBDO for degrading systems is greatly improved by essentially uncoupling the time-variant reliability problem from the optimization problem. First, a meta-model is built to relate time-variant reliability to the design space. Design of experiment techniques helps to select a few judicious training sets. Second, the meta-model is accessed to quickly evaluate objectives and reliability constraints in the optimization process. The set-theory approach (with MCS) is invoked to find the system reliability accurately and efficiently for multiple competing performance measures. For a case study, the seminal roller clutch with degradation due to wear is examined. The meta-model method, using both moving least-squares and kriging (using DACE in Matlab), is compared to the traditional approach whereby reliability is determined by MCS at each optimization iteration. The case study shows that both means and tolerances are found that correctly minimize a monetary cost objective and yet ensure that reliability policies are met. The meta-model approach is simple, accurate and very fast, suggesting an attractive means for RBDO of time-variant systems.