Global optimum of microstructure parameters in the CMWP line-profile-analysis method by combining Marquardt-Levenberg and Monte-Carlo procedures

Line profile analysis of X-ray and neutron diffraction patterns is a powerful tool for determining the microstructure of crystalline materials. The Convolutional-Multiple-Whole-Profile (CMWP) procedure is based on physical profile functions for dislocations, domain size, stacking faults and twin boundaries. Order dependence, strain anisotropy, hkl dependent broadening of planar defects and peak shape are used to separate the effect of different lattice defect types. The Marquardt-Levenberg (ML) numerical optimization procedure has been used successfully to determine crystal defect types and densities. However, in more complex cases like hexagonal materials or multiple phases the ML procedure alone reveals uncertainties. In a new approach the ML and a Monte-Carlo statistical method are combined in an alternative manner. The new CMWP procedure eliminates uncertainties and provides globally optimized parameters of the microstructure.     

Mechanical,forming and biological properties of Ti-Fe-Zr-Y alloys prepared by 3D printing

Biomedical Ti-Fe-Zr-Y alloys were prepared by 3D printing on pure titanium substrate. The influences of Zr on mechanical, forming, and biological properties of the alloys were investigated in detail. The results showed that with increasing the Zr addition, the surface roughness, friction coefficient and worn volume decrease at first and then increase, the lowest values obtained at 5.86 at.% Zr addition. The ultimate compression stress and specific strength gradually decrease. The studied alloys have no cytotoxicity. They can promote the early adhesion and proliferation of cells. The eutectic alloy with 5.86 at.% Zr addition has the best ability of apatite deposition, it exhibits a better comprehensive performance among the studied alloys, which is superior to the Ti_70.5Fe_29.5 and Ti-6Al-4 V alloys.     

Preparation and properties of a new porous ceramic material used in clean energy field

At high temperature, the oxide redox reactions of ceria can split H₂O and CO₂ to produce H₂ and CO, so porous ceria with high temperature resistance and high specific surface area has an important foreground in clean energy applications. In this work, a reticulated porous ceria ceramic material with interconnected porous structure was prepared by the impregnation technique using organic polyurethane sponges as template. The influences of pretreated sponge, dipping time length, pore size and sintering temperature on the porosity and strength of the porous ceria ceramics were systematically studied. With the increasing sintering temperature, the glass phase occurred and led to an increase in strength, but an decrease in porosity. Eventually, we analyzed the relationships between porosity and strength of these porous materials, aiming to provide theoretical and practical references for its application in clean-energy field.     

Influence of cerium content on the corrosion behavior of Al-Co-Ce amorphous alloys in 0.6 M NaCl solution

The effect of cerium content on the corrosion behavior of Al-Co-Ce amorphous alloys in 0.6 M NaCl solution was investigated by cyclic polarization, Mott-Schottky and X-ray photoelectron spectroscopy techniques. Results indicated that the open circuit potential of Al-Co-Ce amorphous alloys displayed a decreased tendency with the increase in Ce content, and the amorphous alloy with 4 at.% Ce presented both the lowest passive current density and donor density indicating the best corrosion resistance, while adding excess Ce led to the reduced corrosion resistance of Al-Co-Ce alloys. Furthermore, it was found that a low Ce content is beneficial to the formation of a more protective passive film on Al-Co-Ce amorphous alloys, and the corrosion inhibition reactions of Al-Co-Ce alloys in 0.6 M NaCl solution were changed with the increase in Ce content and the detailed reasons were discussed.     

Understanding the galvanic corrosion of the Q-phase/Al couple using SVET and SIET

The galvanic corrosion of the Q-phase/Al couple in 0.1 M NaCl solutions has been studied using the scanning vibrating electrode technique (SVET), the scanning ion-selective electrode technique (SIET) and energy dispersive X-ray spectroscopy (EDX). The galvanic corrosion of the Q-phase/Al couple was found to be dependent on pH and immersion time. Current density maps obtained by SVET shows that the anodic oxidation processes emerge from Al in a localized manner in pH 2 and 6 solutions but is initiated in a uniform manner in pH 13 solution, whereas, the cathodic processes are more homogeneously distributed over the Q-phase at pH 2, 6 and 13. It is seen that the Q-phase remains cathodic in the Q-phase/Al couple in acidic, neutral and alkaline solutions indicating that the galvanic polarity of the Q-phase is independent of pH. The effect of the galvanic corrosion was largest at pH 2 and 13 compared to pH 6. The pH map obtained by SIET indicates that the galvanic activity of the Q-phase/Al couple proceeds via heavy alkalization of the Q-phase surface with the generation of appreciable amounts of OH⁻ ions. The enrichment of Cu indicated by EDX is responsible for the observed cathodic activity of the Q-phase in the Q-phase/Al couple.     

Development of an adaptive fuzzy logic-based inverse dynamic model for laser cladding process

The precision, performance, and robustness of model-based controllers depend, to a large extent, on the accuracy of the inverse dynamic model which is incorporated in the design of the controller. Due to complex nature of the laser cladding process and presence of time-varying uncertainties, derivation of an accurate mathematical inverse dynamic model of the process is very difficult, and involves many unknown parameters. The inverse dynamic model of the complex nonlinear laser cladding process, which is difficult to be described mathematically, can be described by a fuzzy logic-based inverse dynamic model constructed form input–output data. In this paper, the development of an adaptive fuzzy inverse dynamic model of the laser cladding process, using a systematic fuzzy modelling approach is presented. In a closed-loop laser cladding process, the scanning speed of the substrate is required to produce a clad with desired geometry and quality. In this paper, a fuzzy inverse dynamic model that describes the scanning speed as a function of the cladding parameters in particular the clad height is developed. The developed fuzzy model is validated by comparing the model output with experimental data. The results are very promising and show that fuzzy models can accurately describe the process dynamics.     

Impact of ZnO gate interfacial layer on piezoelectric response of AlGaN/GaN C-HEMT based ring gate capacitor

We report on a piezoelectric response investigation of AlGaN/GaN circular high electron mobility transistor (C-HEMT) based ring gate capacitor as a new stress sensor device to be potentially applied for dynamic high-pressure sensing. A ring gate capacitor of C-HEMT with an additional ZnO gate interfacial layer was used to measure the changes in the piezoelectric charge induced directly by the variation of piezoelectric polarization of both gate piezoelectric layers (AlGaN, ZnO) for harmonic loading at different excitation frequences. Our experimental results show that about 10 nm thick piezoelectric ZnO layer grown on ring gate/AlGaN interface of C-HEMT can yield almost a 60% increase in the piezoelectric detection sensitivity of the device due to its higher piezoelectric coefficient. A three-dimensional CoventorWare simulation is carried out to confirm the increase in the measured piezoelectric response of ZnO based ring gate capacitor of C-HEMT.     

An expert system for automated recognition of patients with obstructive sleep apnea using electrocardiogram recordings

Obstructive sleep apnea (OSA) is a highly prevalent sleep disorder. The traditional diagnosis methods of the disorder are cumbersome and expensive. The ability to automatically identify OSA from electrocardiogram (ECG) recordings is important for clinical diagnosis and treatment. In this study, we proposed an expert system based on discrete wavelet transform (DWT), fast-Fourier transform (FFT) and least squares support vector machine (LS-SVM) for the automatic recognition of patients with OSA from nocturnal ECG recordings. Thirty ECG recordings collected from normal subjects and subjects with sleep apnea, each of approximately 8 h in duration, were used throughout the study. The proposed OSA recognition system comprises three stages. In the first stage, an algorithm based on DWT was used to analyze ECG recordings for the detection of heart rate variability (HRV) and ECG-derived respiration (EDR) changes. In the second stage, an FFT based power spectral density (PSD) method was used for feature extraction from HRV and EDR changes. Then, a hill-climbing feature selection algorithm was used to identify the best features that improve classification performance. In the third stage, the obtained features were used as input patterns of the LS-SVM classifier. Using the cross-validation method, the accuracy of the developed system was found to be 100% for using a subset of selected combination of HRV and EDR features. The results confirmed that the proposed expert system has potential for recognition of patients with suspected OSA by using ECG recordings.     

Micromachining of passive planar micromixer on poly (methyl methacrylate) substrate with excimer laser ablation

Excimer laser ablation technique was introduced into this work to fabricate a passive planar micromixer on the PMMA substrate. T-junction shaped and width-changed S-shaped microchannels were both designed in this micromixer to enhance mixing effect. The mixing experiment of distilled water and Rhodamine B with injection flow rate of 500 and 1,500 μm/s validates the mixing effectivity of this micromixer, and indicates the feasibility of excimer laser ablation in the microfabrication of μ-TAS device.     

A blind watermarking method using maximum wavelet coefficient quantization

This paper proposes a blind watermarking algorithm based on maximum wavelet coefficient quantization for copyright protection. The wavelet coefficients are grouped into different block size and blocks are randomly selected from different subbands. We add different energies to the maximum wavelet coefficient under the constraint that the maximum wavelet coefficient is always maximum in a block. The watermark is embedded the local maximum coefficient which can effectively resist attacks. Also, using the block-based watermarking, we can extract the watermark without using the original image or watermark. Experimental results show that the proposed method is quite robust under either non-geometry or geometry attacks.