Transparente leitfähige Nitride

Transparent conductive nitrides – New perspectives in device design More than 20 years after the pioneer of the GaN LED Nobel laureate Shuji Nakamura published that germanium is an inferior dopand for GaN when compared to silicon we showed that the opposite is true in regard of achievable n-type doping concentration. With Ge-doped GaN now device performance can be improved and new device structures realized. As transparent highly conductive nitride (TCN) new application fields emerge for GaN, in particular the replacement of ITO. Besides many potential applications Ge-doped GaN layers also show interesting physics as a new quasiparticle, the Collexon.     

Modeling river water quality parameters using modified adaptive neuro fuzzy inference system

Water quality is always one of the most important factors in human health. Artificial intelligence models are respected methods for modeling water quality. The evolutionary algorithm(EA) is a new technique for improving the performance of artificial intelligence models such as the adaptive neuro fuzzy inference system(ANFIS) and artificial neural networks(ANN). Attempts have been made to make the models more suitable and accurate with the replacement of other training methods that do not suffer from some shortcomings, including a tendency to being trapped in local optima or voluminous computations. This study investigated the applicability of ANFIS with particle swarm optimization(PSO)and ant colony optimization for continuous domains(ACO_R) in estimating water quality parameters at three stations along the Zayandehrood River, in Iran. The ANFIS-PSO and ANFIS-ACO_R methods were also compared with the classic ANFIS method, which uses least squares and gradient descent as training algorithms. The estimated water quality parameters in this study were electrical conductivity(EC), total dissolved solids(TDS), the sodium adsorption ratio(SAR), carbonate hardness(CH), and total hardness(TH). Correlation analysis was performed using SPSS software to determine the optimal inputs to the models. The analysis showed that ANFIS-PSO was the better model compared with ANFIS-ACO_R. It is noteworthy that EA models can improve ANFIS' performance at all three stations for different water quality parameters.     

Structure–function relationship of fermented skate skin gelatin-derived bioactive peptides: a peptidomics approach

Food Science and Biotechnology - In this study, we investigated the multi-functionality of bioactive peptides derived from fermented skate (Raja kenojei) skin gelatin hydrolysates. The extracted...     

Experimental Investigations of Machinability in the Turning of Compacted Graphite Iron using Minimum Quantity Lubrication

Unique mechanical properties of the compacted graphite iron (CGI) attracted attention of manufacturers and suppliers mainly in automotive industry in last decades. However due to the low machinability of the CGI material, more efficient machining strategies need to be implemented. Improvement in the cost-effective and environmentally sensitive processing of compacted graphite iron (CGI) is one of the major concerns of the manufacturing world because of the allure of CGI's mechanical properties. This study assesses the efficiency of minimum quantity lubrication (MQL) in CGI turning when compared to the dry-cutting condition. The turning tests were conducted across a wide range of cutting parameters: three different cutting speeds (100, 200, 300 m/min) and three different feed rates (0.1, 0.2, 0.3 mm/rev), all at a constant depth of cut (1 mm). The MQL efficiency is evaluated through cutting force and surface roughness measurements, optical and SEM analyses of chip formation and tool-wear analysis. The results showed that MQL usage provided a reduction in the resultant cutting forces by 2–5%, a reduction in surface roughness by 25%. The SEM analysis also revealed much clearer and smoother cutting edges on tool surfaces used in the MQL tests.     

Influence of processing on stability,microstructure and thermoelectric properties of Ca3Co4 − xO9 + δ

Due to high figure of merit, Ca₃Co_4 ? xO_9 + δ (CCO) has potential as p-type material for high-temperature thermoelectrics. Here, the influence of processing including solid state sintering, spark plasma sintering and post-calcination on stability, microstructure and thermoelectric properties is reported. By a new post-calcination approach, single-phase materials were obtained from precursors to final dense ceramics in one step. The highest zT of 0.11 was recorded at 800 °C for CCO with 98 and 72% relative densities. In situ high-temperature X-ray diffraction in air and oxygen revealed a higher stability of CCO in oxygen (～970 °C) than in air (～930 °C), with formation of Ca₃Co₂O₆ which also showed high stability in oxygen, even at 1125 °C. Since achievement of phase pure high density CCO by post-calcination method in air is challenging, the phase stability of CCO in oxygen is important for understanding and further improvement of the method.     

Partial oxidation of methane in hollow‐fiber membrane reactors based on alkaline‐earth metal‐free CO2‐tolerant oxide

The U‐shaped alkaline‐earth metal‐free CO₂‐stable oxide hollow‐fiber membranes based on (Pr_0.9La_0.1)₂(Ni_0.74Cu_0.21Ga_0.05)O_4+δ (PLNCG) are prepared by a phase‐inversion spinning process and applied successfully in the partial oxidation of methane (POM) to syngas. The effects of temperature, CH₄ concentration and flow rate of the feed air on CH₄ conversion, CO selectivity, H₂/CO ratio, and oxygen permeation flux through the PLNCG hollow‐fiber membrane are investigated in detail. The oxygen permeation flux arrives at approximately 10.5 mL/min cm² and the CO selectivity is higher than 99.5% with a CH₄ conversion of 97.0% and a H₂/CO ratio of 1.8 during 140 h steady operation. The spent hollow‐fiber membrane still maintains a dense microstructure and the Ruddlesden‐Popper K₂NiF₄‐type structure, which indicates that the U‐shaped alkaline‐earth metal‐free CO₂‐tolerant PLNCG hollow‐fiber membrane reactor can be steadily operated for POM to syngas with good performance. © 2014 American Institute of Chemical Engineers AIChE J, 60: 3587–3595, 2014     

Photo-vulcanization using thiol-ene chemistry: Film formation,morphology and network characteristics of UV crosslinked rubber latices

The photo-vulcanization with versatile thiol-ene chemistry represents an innovative approach to crosslink diene-rubber materials both in latex and in solid film state. In this work, the structure of elastomer-based thiol-ene networks and the morphology after film formation are studied in detail using electron microscopic techniques, atomic force microscopy and multiple-quantum solid-state NMR spectroscopy. Additionally, film formation properties and corresponding macroscopic properties of photo-vulcanized natural rubber (NR) latex and its synthetic counterpart, isoprene rubber (IR) latex, are determined in dependence on the curing procedure (pre- and post-vulcanization). The results reveal that thiol-ene cured elastomers comprise homogenously distributed crosslinks with a low amount of short chain defects. Whilst photochemically pre-cured NR latex particles provide coherent films, the film formation and mechanical properties of IR are strongly governed by the crosslink density of the latex particles. In film state, photo-vulcanization promotes narrow crosslink distributions and excellent tensile properties of both NR and IR.     

A Petri net based design engine for manufacturing systems

Support for the efficient design and operation of complex manufacturing systems requires an integrated modelling, analysis, and control methodology as well as its implementation in a software tool. In this paper the Petri net based design engine TimeNET is presented for this task. Petri nets are able to capture the characteristic features of manufacturing systems in a concise form. A subclass of coloured Petri nets is used, which has been developed especially for the application area of manufacturing. Structure and work plans are modelled separately. Stochastic as well as deterministic and more general distributions are adopted for the firing times of transitions. Fundamental questions about system properties can be answered using qualitative analysis. For an efficient performance and dependability prediction, different evaluation techniques are proposed: direct numerical analysis, approximate analysis, and simulation. Finally, the model can be used to evaluate different control strategies and to control the manufacturing system directly. There is no need to change the modelling methodology, thus avoiding additional effort, for example for model conversion. In the paper this necessary steps are described using an application example.     

Covalent Linkage and Macrocylization Preserve and Enhance Synergistic Interactions in Catalytic Amyloids

The self-assembly of short peptides into catalytic amyloid-like nanomaterials has proven to be a powerful tool in both understanding the evolution of early proteins and identifying new catalysts for practically useful chemical reactions. Here we demonstrate that both parallel and antiparallel arrangements of β-sheets can accommodate metal ions in catalytically productive coordination environments. Moreover, synergistic relationships, identified in catalytic amyloid mixtures, can be captured in macrocyclic and sheet-loop-sheet species, that offer faster rates of assembly and provide more complex asymmetric arrangements of functional groups, thus paving the way for future designs of amyloid-like catalytic proteins. Our findings show how initial catalytic activity in amyloid assemblies can be propagated and improved in more-complex molecules, providing another link in a complex evolutionary chain between short, potentially abiotically produced peptides and modern-day enzymes.