Solid-state synthesis and effect of temperature on optical properties of Cu-ZnO, Cu-CdO and CuO nanoparticles

Controlling novel morphologies and developing effective doping strategies are two important tasks for advancing ZnO and CdO based nanomaterials. Modulation of band energies through size control offers new ways to control photoresponse and photoconversion efficiencies of the solar cell. The P-type semiconductors of copper oxide and zinc oxide are an important functional material used for photovoltaic cells. CuO is attractive as a selective solar absorber since it has high solar absorbance and a low thermal emittance. This work describes the synthesis and characterization of semiconducting nanoparticles (ZnO, CuO, CdO, Cu-ZnO, Cu-CdO) via one-step, solid-state reaction in the presence of polyethylene glycol 400.Solid-state mechanochemical processing—which is not only a physical size reduction process in conventional grinding but also a chemical reaction that is mechanically activated at the nanoscale during grinding. The present method is a simple and efficient method for the preparation of nanoparticles with high yield at low cost. The structural and chemical composition of the nanoparticles were analyzed by X-ray diffraction, field emission scanning electron microscopy and energy-dispersive spectrometer (FESEM/EDAX). Optical properties and band gap were studied by UV-vis absorption spectra. XRD data has been concluded that the Cu doping induced the lattice constants to change to some extent. These results have showed that the band gap energy decreases with increase in annealing temperature, which can be attributed to the improvement in crystallinity of the samples. The band gap of the Cu-ZnO and Cu-CdO crystals can be tuned in the range of 3.34-3.28 eV and 2.80-2.21 eV respectively, by the use of dopants.     

Pattern identification in dynamical systems via symbolic time series analysis

This paper presents symbolic time series analysis (STSA) of multi-dimensional measurement data for pattern identification in dynamical systems. The proposed methodology is built upon concepts derived from Information Theory and Automata Theory. The objective is not merely to classify the time series patterns but also to identify the variations therein. To achieve this goal, a symbol alphabet is constructed from raw data through partitioning of the data space. The maximum entropy method of partitioning is extended to multi-dimensional space. The resulting symbol sequences, generated from time series data, are used to model the dynamical information as finite state automata and the patterns are represented by the stationary state probability distributions. A novel procedure for determining the structure of the finite state automata, based on entropy rate, is introduced. The diversity among the observed patterns is quantified by a suitable measure. The efficacy of the STSA technique for pattern identification is demonstrated via laboratory experimentation on nonlinear systems.     

Parameterized complexity of the induced subgraph problem in directed graphs

In this Letter, we consider the parameterized complexity of the following problem: Given a hereditary property P on digraphs, an input digraph D and a positive integer k, does D have an induced subdigraph on k vertices with property P? We completely characterize hereditary properties for which this induced subgraph problem is W[1]-complete for two classes of directed graphs: general directed graphs and oriented graphs. We also characterize those properties for which the induced subgraph problem is W[1]-complete for general directed graphs but fixed parameter tractable for oriented graphs. These results are among the very few parameterized complexity results on directed graphs.     

Drying and color characteristics of coriander foliage using convective thin-layer and microwave drying

Heat sensitive properties (aromatic, medicinal, color) provide herbs and spices with their high market value. In order to prevent extreme loss of heat sensitive properties when drying herbs, they are normally dried at low temperatures for longer periods of time to preserve these sensory properties. High energy consumption often results from drying herbs over a long period. Coriander (Coriandrum sativum L., Umbelliferae) was dehydrated in two different drying units (thin layer convection and microwave dryers) in order to compare the drying and final product quality (color) characteristics. Microwave drying of the coriander foliage was faster than convective drying. The entire drying process took place in the falling rate period for both microwave and convective dried samples. The drying rate for the microwave dried samples ranged from 42.3 to 48.2% db/min and that of the convective dried samples ranged from 7.1 to 12.5% db/min. The fresh sample color had the lowest L value at 26.83 with higher L values for all dried samples. The results show that convective thin layer dried coriander samples exhibited a significantly greater color change than microwave dried coriander samples. The color change index values for the microwave dried samples ranged from 2.67 to 3.27 and that of the convective dried samples varied from 4.59 to 6.58.     

Ferroelectric Materials for Microwave Tunable Applications

A review of the properties of ferroelectric materials that are relevant to microwave tunable devices is presented: we discuss the theory of dielectric response of tunable bulk materials and thin films; the experimental results from the literature and from own work are reviewed; the correspondence between the theoretical results and the measured properties of tunable materials is critically analyzed; nominally pure, real (defected), and composite bulk materials and thin films are addressed. In addition, techniques for characterization of tunable ferroelectrics and applications of these materials are briefly presented.     

Effects of User Request Patterns on a Multimedia Delivery System

Because of their size, service times, and drain on server resources, multimedia objects require specialized replication systems in order to meet demand and ensure content availability. We present a novel method for creating replication systems where the replicated objects' sizes and/or per-object service times are large. Such replication systems are well-suited to delivering multimedia objects on the Internet. Assuming that user request patterns to the system are known, we show how to create replication systems that distribute read load to servers in proportion to their contribution to system capacity and experimentally show the positive load distribution properties of such systems. However, when user request patterns differ from what the system was designed for, system performance will be affected. Therefore, we also report on results that reveal (i) how server loads are affected and (ii) the impact two system design parameters (indicators of a system's load distribution qualities) have on server load when request patterns differ from that for which a system was designed.     

Role of sample size in the nucleation kinetics of phase transformations in steel alloys

Certain commercial steel alloys exhibit a two-step phase transformation process during solidification when substantial undercooling of the liquid allows access to the metastable phase. This two-step transformation leads to a desirable microstructure under certain conditions. Electrostatic Levitation (ESL) and Electromagnetic Levitation (EML) are two methods of containerless processing used to study how nucleation and growth kinetics influence the transformation delay between phases. Because the two facilities show substantially different delay results, the test environment differences have been analyzed to determine the root cause of this deviation. In particular, the difference in sample size between ESL and EML is examined and modeling shows that this difference is not the controlling factor in determining transformation delay behavior.     

An optimal model for representing the kinetics of growth and product formation by Lactobacillus rhamnosus on multiple substrates

A comprehensive model was developed to simulate Lactobacillus rhamnosus growth on a medium containing multiple limiting carbon sources. The strategy of optimizing specific growth rate to predict growth on multiple substrates was demonstrated. The model predictions were based on parameters obtained from L. rhamnosus growth on individual substrates. The model was able to simulate the growth, substrate consumption, product formation and specific growth rate profiles of L. rhamnosus accurately. The model prediction that co-metabolism of glucose and pyruvate enhances growth rate of and flavor production by the bacterium was experimentally verified.     

Reliability of fine-pitch through-vias in glass interposers and packages for high-bandwidth computing and communications

Glass is an ideal substrate material to enable 2.5D and 3D packaging of ICs at low cost and high performance. However, it is a brittle material and is prone to failures during fabrication and operation. Large coefficient of thermal expansion (CTE) mismatch between copper and glass leads to thermomechanical stresses that can lead to glass cracking and delamination from glass interfaces. This paper focuses on modeling and reliability characterization of copper-plated through-package-vias (TPV) in glass packages. Thermomechanical simulations were carried out to obtain design guidelines for reliable TPVs in glass. Test-vehicles with different glass thicknesses and copper TPV fabrication conditions were fabricated for thermal cycling tests, resistance monitoring and failure analysis. The reliability characterization results showed good thermomechanical reliability of TPVs in ultra-thin glass panels.     

Bacteria-Responsive Self-Assembly of Antimicrobial Peptide Nanonets for Trap-and-Kill of Antibiotic-Resistant Strains

Bacterial trapping using nanonets is a ubiquitous immune defense mechanism against infectious microbes. These nanonets can entrap microbial cells, effectively arresting their dissemination and rendering them more vulnerable to locally secreted microbicides. Inspired by this evolutionarily conserved anti-infective strategy, a series of 15 to 16 residue-long synthetic β-hairpin peptides is herein constructed with the ability to self-assemble into nanonets in response to the presence of bacteria, enabling spatiotemporal control over microbial killing. Using amyloid-specific K114 assay and confocal microscopy, the membrane components lipoteichoic acid and lipopolysaccharide are shown to play a major role in determining the amyloid-nucleating capacity as triggered by Gram-positive and Gram-negative bacteria respectively. These nanonets displayed both trapping and killing functionalities, hence offering a direct improvement from the trap-only biomimetics in literature. By substituting a single turn residue of the non-amyloidogenic BTT1 peptide, the nanonet-forming BTT1-3A analog is produced with comparable antimicrobial potency. With the same sequence manipulation approach, BTT2-4A analog modified from BTT2 peptide showed improved antimicrobial potency against colistin-resistant clinical isolates. The peptide nanonets also demonstrated robust stability against proteolytic degradation, and promising in vivo efficacy and biosafety profile. Overall, these bacteria-responsive peptide nanonets are promising clinical anti-infective alternatives for circumventing antibiotic resistance.