Electronic Instabilities Leading to Electroformation of Binary Metal Oxide‐based Resistive Switches

Oxide‐based resistive switching devices are a leading contender for the next generation memories. Before use, each device has to go through a conditioning process called electroformation which has been suggested to be initiated by the accumulation of oxygen vacancies. Here, experimental evidence is presented which shows that both Ta₂O_5‐x‐ and TiO_2‐x‐based crossbar devices, exhibit characteristic electronic instability leading to a reversible constriction of the current flow to a narrow filament prior to permanent change. Thus, it is asserted, electroformation is initiated through purely electronic and reversible events, to be followed later by structural changes in the material, like oxygen vacancy redistribution. Furthermore, the electronic instability responsible for electroformation also gives rise to negative differential resistance (NDR) and that this characteristics appears to involve two distinct mechanisms: a thermal one in which Joule heating causes resistance to decrease as current increases and a second electronic mechanism that appears not to require Joule heating for NDR. Using a combination of thermometry and thermal modeling, a self‐consistent temperature and filament radius as a function of power are found for the 5 μm cross‐bar devices. In the thermal NDR regime, the filament appears to be ～500 nm in diameter and has a peak temperature of ～300 °C, while in the adiabatic regime, the estimated filament diameter is much smaller (<50 nm) and the maximum temperature inside it exceeds 800 °C.     

Phenomenological modeling of anisotropy induced by evolution of the dislocation structure on the macroscopic and microscopic scale

This work focuses on the modeling of the evolution of anisotropy induced by the development of the dislocation microstructure. A model formulated at the engineering scale in the context of classical metal plasticity and a model formulated in the context of crystal plasticity are presented. Images obtained by transmission-electron microscopy (TEM) show the influence of the strain path on the evolution of anisotropy for the case of two common materials used in sheet metal forming, DC06 and AA6016-T4. Both models are capable of accounting for the transient behavior observed after changes in loading path for fcc and bcc metals. The evolution of the internal variables of the models is correlated with the evolution of the dislocation structure observed by TEM investigations.     

Application of neural networks for the prediction of hourly mean surface temperatures in Saudi Arabia

This paper utilizes artificial neural networks for the prediction of hourly mean values of ambient temperature 24 h in advance. Full year hourly values of ambient temperature are used to train a neural network model for a coastal location — Jeddah, Saudi Arabia. This neural network is trained off-line using back propagation and a batch learning scheme. The trained neural network is successfully tested on temperatures for years other than the one used for training. It requires only one temperature value as input to predict the temperature for the following day for the same hour. The predicted hourly temperature values are compared with the corresponding measured values. The mean percent deviation between the predicted and measured values is found to be 3.16, 4.17 and 2.83 for three different years. These results testify that the neural network can be a valuable tool for hourly temperature prediction in particular and other meteorological predictions in general.     

A complementary metal–oxide semiconductor digitally programmable current conveyor

A second‐generation current conveyor with digitally programmable current gains is presented. A current division network with zero standby power consumption is utilized in two different ways to provide both gain and attenuation of the second‐generation current conveyor's current transfer characteristics. The proposed topology overcomes several drawbacks of the previous solutions through affording a more power and area efficient solution while exhibiting relatively wider tuning range and bandwidth. A variable‐gain amplifier and a two‐integrator‐loop filter biquad providing low‐pass and band‐pass responses are given as application examples. A modified two‐integrator‐loop topology is developed to offer independent control of the pole frequency and quality factor without disturbing the passband gain. Simulation results obtained from a standard 0.18 µm complementary metal–oxide semiconductor process are given. Copyright © 2011 John Wiley & Sons, Ltd.     

A green route for biodiesel production from waste cooking oil over base heterogeneous catalyst

The present work describes the synthesis of porous BaSnO₃ by eco‐friendly sol‐gel method using albumin as a bio‐template agent, and its application as a solid base catalyst in biodiesel production from waste cooking oil. The physico‐chemical, textural, and morphological properties of the catalyst were evaluated by X‐ray diffraction (XRD), Brunauer‐Emmett‐Teller (BET), field emission scanning electron microscopy (FESEM), and temperature programmed desorption (TPD)–CO₂ techniques. The synthesized catalyst showed considerable stability, efficient catalytic activity, and negligible metal leaching. The satisfactory performance of the catalyst could be ascribed to the presence of basic sites of different strength on the surface of the catalyst. The catalyst produced maximum biodiesel yield of 96% at optimum reaction conditions of 90°C reaction temperature, methanol to oil molar ratio of 10:1, catalyst dosage of 6 wt%, and reaction time of 2 hours. Moreover, the catalyst showed substantial reusability up to five reaction cycles without any considerable decrease in transesterification activity.     

Adaptive memetic method of multi-objective genetic evolutionary algorithm for backpropagation neural network

Neural Computing and Applications - In recent years, multi-objective evolutionary optimization algorithms have shown success in different areas of research. Due to their efficiency and power, many...     

Dynamic analysis of spinning triangle geometry part 1: validation of methodology

The physical shape or geometry of the spinning triangle directly affects the quality of ring spun yarns. This study developed a technique to measure the geometrical parameters of the spinning triangle during ring spinning using a combination of a clear rubber roller and digital image processing. The clear roller exposed the spinning triangle zone during the yarn spinning process in a non-invasive manner, and yarn properties were not affected. A digital camera recorded images of the spinning triangle. An image processing algorithm was then developed to process the images to measure the dynamic geometry of the spinning triangle. The method was able to effectively measure the width, height and skew of the spinning triangle along with changes in these parameters over time. This technique will be applied in a follow-up study to investigate the effects of the shape of the spinning triangle on yarn quality.     

Enzymatic Characterisation of Novamyl®, a Thermostable α-Amylase

The thermostable -amylase Novamyl^® is used in the baking industry as an antistaling agent due to its ability to reduce retrogradation of amylopectin. We have studied its enzymatic properties at pH 5.0. We make two main conclusions: (1) Novamyl^® shows sequence homology to cycloglycosyl transferases (CGTases); like these enzymes, Novamyl^® cleaves cyclodextrins, forms transglycosylation products and is subject to product inhibition by maltose. Novamyl^® has 5 subsites in the active site and is also subject to substrate inhibition. (2) Novamyl^® is clearly different from exoglucanases like β-amylase and glucoamylase. It is able to hydrolyse a pentasaccharide with bulky substituents at both ends (INdp5) and is inhibited by the α-amylase inhibitor Trestatin A. Although Novamyl^® appears unable to hydrolyse α-1,6-linkages, it is able to degrade amylopectin to a greater extent than β-amylase as well as β-limit dextrins. Novamyl^® degrades amylose in such a manner that initially the molecular weight is drastically reduced while β-amylase does not show any detectable effect on the molecular weight of this substrate. Products of the degradation of amylopectin and amylose by Novamyl^® are maltose and oligosaccharides, whereas β-amylase and glucoamylase produce only maltose and glucose, respectively. This was shown in baking experiments as well. The new data presented here clearly show that unlike exoamylases, Novamyl^® does not require a non-reducing end and attacks amylose, Indp5 and cyclodextrins in an endo-like manner. Based on these results Novamyl^® should be reclassified.     

Evaluation of fish meat noodles: physical property,dough rheology,chemistry and water distribution properties

The present study reports the rheological, textural, structural and water distribution properties of fish meat noodles. The results showed that storage and loss modulus were increased when 20% fish meat was added while decreased with the addition of >20% fish meat, whereas loss rate behaved vice versa. The moisture and fat content increased significantly (P < 0.05) while water absorption index was decreased upon the increment of fish meat compared to control. Lightness of dough and hardness of noodles decreased significantly (P < 0.05) while redness and yellowness were increased. Similarly, less swelled starch granules and dominancy of protein network over starch granules were observed in microstructure. The amount of free water was increased while bound water was decreased when >20% fish meat was added during low-field nuclear magnetic resonance. The findings suggest the feasibility of adding 15–20% fish meat for the proper structure and chemistry of noodles.