Changes in vibrational entropy during the early stages of chemical unmixing in fcc Cu–6% Fe

A nanocrystalline face-centered cubic (fcc) solid solution of 6% Fe in Cu was prepared by high-energy ball milling, and annealed at temperatures from 200 to 360 °C to induce chemical unmixing. The chemical state of the material was characterized by three-dimensional atom probe microscopy, Mössbauer spectrometry and X-ray powder diffractometry. The unmixing was heterogeneous, with iron atoms forming iron-rich zones that thicken with further annealing. The phonon partial density of states (pDOS) of ⁵⁷Fe was measured by nuclear resonant inelastic X-ray scattering, showing the pDOS of the as-prepared material to be that of an fcc crystal. The features of this pDOS became broader in the early stages of unmixing, but only small changes in average phonon frequencies occurred until the body-centered cubic (bcc) phase began to form. The vibrational entropy calculated from the pDOS underwent little change during the early stage of annealing, but decreased rapidly when the bcc phase formed in the material.     

In vitro bioaccessibility of coenzyme Q10 in enriched yoghurts

In this study, the aim was to determine the bioaccessibilities of coenzyme Q10 (CoQ10) in yoghurt samples produced using enriched skim milk with different coenzyme Q10 preparations. First, emulsified coenzyme Q10, γ‐cyclodextrin/coenzyme Q10 complex and nanoparticle coenzyme Q10 were prepared with the reference coenzyme Q10 standard. These coenzyme Q10 preparations were added into the milk to produce coenzyme Q10 enriched yoghurt samples. Nanoparticle coenzyme Q10 was obtained as in spherical shape with 176.00 ± 50.62 nm diameter. Coenzyme Q10 bioaccessibility was found as 50.59 ± 1.88% in control yoghurt. The yoghurt enriched nanoparticle coenzyme Q10 had the highest coenzyme Q10 bioaccessibility (73.81 ± 1.61%) among the produced yoghurts (P < 0.01). Coenzyme Q10 bioaccessibilities were also found as 63.75 ± 0.91% and 46.83 ± 1.27% in yoghurts enriched with emulsified coenzyme Q10, and γ‐cyclodextrin/coenzyme Q10 complex, respectively.     

Uncertainties in the prediction of flow in a long reach of the Sacramento River

The accurate prediction of the flow field in a long reach of a complex waterway is prerequisite to the evaluation to acceptable engineering accuracy of strategies for the restoration, resource management and hazard assessment. In this study, we consider some aspects of the numerical prediction of flow in a long reach of the Sacramento River in California with view to gaining a better understanding the sources and the extent of the uncertainties that are present in the predictions. The predictions were obtained using a finite‐volume method to solve the time‐averaged forms of the equations governing the conservation of mass and momentum. Body‐fitted coordinates were used to define the complex river bathymetry. Both depth‐averaged and fully three‐dimensional (3D) computations were performed. The results were compared with data obtained from a large‐scale physical model of the same reach. The outcome of the comparisons served to provide the basis for the assessment of the sensitivity of the solutions to assumptions made regarding the conditions at inlet to the solution domain, the choice of turbulence model used to close the time‐averaged equations and, for the depth‐averaged calculations, the choice of method used for prescribing the bed friction. The influence of other parameters such as the density of the computational grid, the method used to define the channel bathymetry, and the unsteadiness of the mean flow that results from vortex shedding from a bridge pier and abutments were also assessed. The results obtained form a useful addition to the growing literature on the computational modelling of flows in natural waterways.     

Analysis,design, and optimization of structures with integral compliant mechanisms for mid‐frequency response

A multi‐scale paradigm is proposed that utilizes periodic, small‐scale, integral compliant mechanisms within larger‐scale structures for the attenuation of vibro‐acoustic response. Amplification principles serve as the basis for the design of these mechanisms in achieving reduced energy transmission. The spectral finite element method is exploited for a force–velocity and energy flow analysis of the resultant truss‐like structures. A genetic algorithm is employed to optimize structure size for greatest effectiveness in the frequency range of interest. This study demonstrates that a significant decrease in structural vibration is achievable and suggests promising applications including the design of acoustic isolation panels for broadband vehicle noise reduction. Copyright © 2007 John Wiley & Sons, Ltd.     

Enterprise knowledge management model: a knowledge tower

One of the most important aspects of knowledge management (KM) is to create a system that is capable of providing mechanisms and methodologies allowing the right knowledge to be at the right place and at the right person as well as at the right time within an enterprise. There have been several models developed for this purpose. The main objectives of these models are to organize the knowledge activities to increase competitive advantage and turn the market share into a continuous and permanent superiority through utilizing the intellectual capital of the enterprise for better products and services. When existing models are carefully analyzed, it can be clearly seen that every model addresses different aspects of KM. While some of these models have been intensifying on the use of technology and production of knowledge, the others rather focus on the utilization of knowledge itself. Although these models point out the importance of managerial participation, they are mainly designed to be facilitated at operational levels. It is now obviously seen that there is a need for a new model that will deal with KM at strategic, tactic, and operational levels in an integrated manner. In this study, an enterprise knowledge management model (EKMM) is developed to facilitate this. The model is also called the “Knowledge Tower” due to its dynamics and tower-like infrastructure. EKMM does not only deal with utilizing the knowledge but also create KM strategies, knowledge culture as well as respective leveraging activities. It provides an extensive assessment capability to make sure that the KM practices are carried out as effectively as possible. This surely helps identifying the lack of implementations and areas requiring improvements.     

Synthesis and characterization of Schiff base derivative with pyrrole ring and electrochromic applications of its oligomer

In this study, Schiff base monomer, 2-[(1H-pyrrol-2-yl-methylene)amino]phenol (2-PMAP) was obtained by condensation reaction of 2-aminophenol with pyrrole-2-carbaldehyde. This monomer was oxidized in an aqueous alkaline medium by NaOCl to obtain the corresponding oligomer (O-2-PMAP). The resulting compounds were characterized by ¹H- and ¹³C-NMR, FT-IR, UV–vis, TG-DTA and size exclusion chromatography (SEC) techniques. Metal complexes compounds of O-2-PMAP were prepared with various metal salts, such as Cu (AcO)₂·H₂O, Zn (AcO)₂·2H₂O, Cd (AcO)₂·2H₂O, Pb (AcO)₂·3H₂O and Co (AcO)₂·4H₂O. In addition to this, electrochemical copolymerization of O-2-PMAP with thiophene (Th), 3,4-ethylenedioxythiophene (EDOT) and pyrrole (Py) were performed onto indium/tin oxide (ITO)-coated glass plate. The spectral changes of the co-polymeric films were recorded in the range of the different potentials. The film stabilities of its EDOT and Py copolymers were determined. Consequently, it was realized that the copolymer films kept their stability for a long time.     

An effective synthesis route for improving the catalytic activity of carbon-supported Co–B catalyst for hydrogen generation through hydrolysis of NaBH4

A novel method for synthesis of carbon-supported cobalt boride catalyst was developed for hydrogen generation from catalytic hydrolysis of NaBH₄ solution. The activated carbon and carbon black supported catalysts prepared by “reduction–precipitation” method were found to be much more active than those prepared by conventional “impregnation–reduction” method inspite of the same Co content. A maximum hydrogen generation was achieved using carbon black supported Co–B, which lowers the activation energy to 56.7 kJ mol⁻¹. The effects of NaOH concentration (1–15 wt.%), NaBH₄ concentration (5–20 wt.%) and reaction temperature (25–40 °C) on the performance of the most active catalyst (Co–B/C_B) were investigated in detail. The results indicated that this catalyst can be used in a hydrogen generator for mobile applications such as PEMFC systems due to its high catalytic activity and simple preparation method.     

Fuzzy logic and statistical-based modelling of the Marshall Stability of asphalt concrete under varying temperatures and exposure times

In this study, the Marshall Stability (MS) of asphalt concrete under varying temperature and exposure times was modelled by using fuzzy logic and statistical method. This is an experimental study conducted using statistics and fuzzy logic methods. In order to investigate the Marshall Stability of asphalt concrete based on exposure time and environment temperature, exposure times of 1.5, 3, 4.5 and 6 h and temperatures of 30, 40 and 50 °C were selected. The MS of the asphalt concrete at 17 °C (in laboratory environment temperature) was used as reference. The results showed that the MS of the asphalt core samples decreased 40.16% at 30 °C after 1.5 h and 62.39% after 6 h. At 40 °C the decrease was 74.31% after 1.5 h, and 78.10% after 6 h. At 50 °C the stability of the asphalt decreased 83.22% after 1.5 h, 88.66% after 6 h. The relationships between experimental results, fuzzy logic model and statistical results exhibited good correlation. The correlation coefficient was R = 0.99 for fuzzy logic model and R² = 0.9 for statistical method. Based on the results of the study, it could be said that both the fuzzy logic method and statistical methods could be used for modelling of the stability of asphalt concrete under varying temperature and exposure time.     

Adaptive neuro-fuzzy inference approach for prediction the stiffness modulus on asphalt concrete

In this study, stiffness modulus parameters of asphalt concrete were determined experimentally for different temperature and exposure times. The stiffness modules were calculated according to Nijboer stiffness module. Basic physical properties and the quantity of bitumen of asphalt core samples were designated for determining the stiffness modules. The samples were exposed to 17 °C (reference temperature), 30, 40 and 50 °C temperatures for 1.5, 3, 4.5 and 6 h respectively and then Marhall Stability tests were done for each samples. By using the test results a prediction model with Sugeno type based on the adaptive neuron-fuzzy inference system (ANFIS) was alternatively developed to predict the stiffness modules of asphalt core samples. As a result, it was seen that the developed prediction model could be used as a prediction model for unperformed situations which are not suitable for experiments.