Pressure effects on the thermodynamic and mechanical properties of zinc-blende ZnTe compound

In this paper, the moment method in statistical mechanics has been employed to study the pressure effects on thermodynamic and mechanical properties of zinc-blende zinc telluride using many-body potential. We have derived the analytical expressions of the pressure-dependent lattice parameter, volume compression as well as mean-square displacement of zinc-blende type compound. Numerical calculations performed for ZnTe compound up to 12 GPa are found to be in good and reasonable agreement with available experimental data as well as with previous theoretical studies. These results have been used to evaluate the bulk modulus and its first pressure derivative of ZnTe. The present moment method has taken into account the quantum zero-point vibrations at low temperature and the higher-order anharmonic terms in the atomic displacements. This research shows the advantage of moment method on extensively studying thermo-mechanical properties of materials under high pressures.     

Downward self‐polarization of lead‐free (K0.5Na0.5)(Mn0.005Nb0.995)O3 ferroelectric thin films on Nb:SrTiO3 substrate

Spontaneously appearing macroscopic polarization (self‐polarization) in ferroelectrics without an electrode or an external electric field would enable the freedom to design many ferroelectric heterostructures and devices. The (K_0.5Na_0.5)(Mn_0.005Nb_0.995)O₃ (KNMN) thin film was grown on Nb:SrTiO₃ single‐crystal substrate and the resultant self‐polarization behavior due to strain relaxation was investigated. The lattice mismatch and difference in TEC between the KNMN thin film and the Nb:SrTiO₃ substrate creates a compressive strain. The compressive strain gradient may be the main cause for the observed downward self‐polarization. The downward self‐polarization of the KNMN thin film can be explained by the strong inhomogeneous compressive strain caused by strain relaxation. (© 2016 WILEY‐VCH Verlag GmbH &Co. KGaA, Weinheim)     

Experimental and Numerical Simulations of Spray Impingement and Combustion Characteristics in Gasoline Direct Injection Engines under Variable Driving Conditions

Gasoline direct injection (GDI) increases engine power output and reduces emissions. In GDI engines, increasing injection pressure improves atomization, which increases thermal efficiency at the cost of wall wetting. When wall wetting occurs, both soot emissions and fuel consumption increase. Wall wetting in GDI engines under cold driving conditions has rarely been considered. In this study, experimental data characterizing droplet splashing/spreading phenomena were collected to inform numerical simulations of combustion characteristics and wall wetting subject to variable driving conditions and excess air ratio, λ. Fully 3D and unsteady numerical simulations were carried out to predict flow-field, combustion, and spray-impingement characteristics. To simulate a GDI engine, a spray-impingement model was developed using both experimental data and previous modeling efforts. The excess air ratio and driving-condition temperature were the variable parameters considered in this study. When decreasing λ from 1.0 to 0.7 by increasing the fuel-injection rate (fuel rich), the cylinder pressure increases to 61 % of the pressure when λ=1.0. Because of increasing the fuel-injection rate, the increased momentum in the fuel spray increases both wall wetting and soot generation. At low driving-condition temperatures, the cylinder pressure was up to 63 % less than that under warm conditions, but with increased soot generation. Simulations revealed a correlation between wall wetting and the soot emissions. Soot generation was most sensitive to changes in wall wetting.     

Adaptive Mixed GMsFEM for Flows in Heterogeneous Media

In this paper, we present two adaptive methods for the basis enrichment of the mixed Generalized Multiscale Finite Element Method (GMsFEM) for solving the flow problem in heterogeneous media. We develop an a-posteriori error indicator which depends on the norm of a local residual operator. Based on this indicator, we construct an offline adaptive method to increase the number of basis functions locally in coarse regions with large local residuals. We also develop an online adaptive method which iteratively enriches the function space by adding new functions computed based on the residual of the previous solution and special minimum energy snapshots. We show theoretically and numerically the convergence of the two methods. The online method is, in general, better than the offline method as the online method is able to capture distant effects (at a cost of online computations), and both methods have faster convergence than a uniform enrichment. Analysis shows that the online method should start with a certain number of initial basis functions in order to have the best performance. The numerical results confirm this and show further that with correct selection of initial basis functions, the convergence of the online method can be independent of the contrast of the medium. We consider cases with both very high and very low conducting inclusions and channels in our numerical experiments.     

Crucial role of HMGA1 in the self-renewal and drug resistance of ovarian cancer stem cells

Cancer stem cells are a subpopulation of cancer cells characterized by self-renewal ability, tumorigenesis and drug resistance. The aim of this study was to investigate the role of HMGA1, a chromatin remodeling factor abundantly expressed in many different cancers, in the regulation of cancer stem cells in ovarian cancer. Spheroid-forming cancer stem cells were isolated from A2780, SKOV3 and PA1 ovarian cancer cells by three-dimensional spheroid culture. Elevated expression of HMGA1 was observed in spheroid cells along with increased expression of stemness-related genes, such as SOX2, KLF4, ALDH, ABCB1 and ABCG2. Furthermore, spheroid A2780 cells, compared with adherent cells, showed higher resistance to chemotherapeutic agents such as paclitaxel and doxorubicin. HMGA1 knockdown in spheroid cells reduced the proliferative advantage and spheroid-forming efficiency of the cells and the expression of stemness-related genes. HMGA1 overexpression in adherent A2780 cells increased cancer stem cell properties, including proliferation, spheroid-forming efficiency and the expression of stemness-related genes. In addition, HMGA1 regulated ABCG2 promoter activity through HMGA1-binding sites. Knockdown of HMGA1 in spheroid cells reduced resistance to chemotherapeutic agents, whereas the overexpression of HMGA1 in adherent ovarian cancer cells increased resistance to chemotherapeutic agents in vitro. Furthermore, HMGA1-overexpressing A2780 cells showed a significant survival advantage after chemotherapeutic agent treatment in a xenograft tumorigenicity assay. Together, our results provide novel insights regarding the critical role of HMGA1 in the regulation of the cancer stem cell characteristics of ovarian cancer cells, thus suggesting that HMGA1 may be an important target in the development of therapeutics for ovarian cancer patients.     

A simple and cost-effective molecular diagnostic system and DNA probes synthesized by light emitting diode photolithography

This work introduces a novel chip to be used in the future as a simple and cost-effective method for creating DNA arrays using light emission diode (LED) photolithography. The DNA chip platform contains 24 independent reaction sites, which allows for the testing of a corresponding amount of patients’ samples in hospital. An array of commercial UV LEDs and lens systems was combined with a microfluidic flow system to provide patterning of 24 individual reaction sites, each with 64 independent probes. Using the LED array instead of conventional laser exposure systems or micro-mirror systems significantly reduces the cost of equipment. The microfluidic system together with microfluidic flow cells drastically reduces the amount of used reagents, which is important due to the high cost of commercial reagents. The DNA synthesis efficiency was verified by fluorescence labeling and conventional hybridization.     

Novel fabrication route for carbon-free and dense CuInSe2 (CIS) thin films via a non-vacuum process for solar cell application

Carbon-free CuInSe₂ (CIS) thin film with a dense microstructure has been prepared using a novel non-vacuum based fabrication route. Cu_xS_y and In₂Se₃ binary nanoparticles, approximately 10 nm in size, were synthesized by a low temperature colloidal process. The precursor film was deposited using the coating ink formulated with the binary nanoparticles and pyridine, and then annealed in the rapid thermal annealing (RTA) chamber at 540 °C for 15 min under selenium (Se) atmosphere. Scanning electron micrographs, X-ray diffraction patterns and Raman spectra showed a phase pure carbon-free and dense CIS thin film was prepared in this method. A solar cell device fabricated using this CIS thin film showed the following photovoltaic characteristics: V_OC = 350 mV, J_SC = 24.72 mA cm⁻², FF = 38.73% and η = 3.36% under standard AM 1.5 condition.     

Design of vibration isolators by exploiting the beneficial effects of stiffness and damping nonlinearities

The present study is concerned with the design of a new type of single degree of freedom (sdof) nonlinear vibration isolation system that can deal with harmonic excitations and take advantage of both spring and damping nonlinearities. For typical design requirements expressed in terms of a transmissibility envelope, the proposed design makes use of a recently developed method called the output frequency response function (OFRF) approach, which provides a direct relationship between the system output frequency response and parameters that define the system nonlinearity. Taking all output harmonics into account, a detailed step-by-step procedure is developed to systematically determine the nonlinear parameters from a small set of simulation or experimental data. Simulation studies are conducted to verify the results and demonstrate that the design can effectively achieve all the three requirements for a vibration isolation system of a low resonant peak, low high frequency transmissibility, and a large isolation range.     

Window-modulated compounding Nakagami imaging for ultrasound tissue characterization

Ultrasound Nakagami parametric imaging is a useful tool for tissue characterization. Previous literature has suggested using a square with side lengths corresponding to 3 times the transducer pulse length as the minimum window for constructing the Nakagami image. This criterion does not produce sufficiently smooth images for the Nakagami image to characterize homogeneous tissues. To improve image smoothness, we proposed window-modulated compounding (WMC) Nakagami imaging based on summing and averaging the Nakagami images formed using sliding windows with varying window side lengths from 1 to N times the transducer pulse length in 1 pulse length step. Simulations (the number densities of scatterers: 2–16 scatterers/mm²) and experiments on fully developed speckle phantoms (the scatterer diameters: 20–106 μm) were conducted to suggest an appropriate number of frames N and to evaluate the image smoothness and resolution by analyzing the full width at half maximum (FWHM) of the parameter distribution and the widths of the image autocorrelation function (ACF), respectively. In vivo ultrasound measurements on rat livers without and with cirrhosis were performed to validate the practical performance of the WMC Nakagami image in tissue characterization. The simulation results showed that using a range of N from 7 to 10 as the number of frames for image compounding reduces the estimation error to less than 5%. Based on this criterion, the Nakagami parameter obtained from the WMC Nakagami image increased from 0.45 to 0.95 after increasing the number densities of scatterers from 2 to 16 scatterers/mm². The FWHM of the parameter distribution (bins = 40) was 13.5 ± 1.4 for the Nakagami image and 9.1 ± 1.43 for the WMC Nakagami image, respectively (p-value < .05). The widths of the ACF for the Nakagami and WMC Nakagami images were 454 ± 5.36 and 458 ± 4.33, respectively (p-value > .05). In the phantom experiments, we also found that the FWHM of the parameter distribution for the WMC Nakagami image was smaller than that of the conventional Nakagami image (p-value < .05), and there was no significant difference of the ACF width between the Nakagami and WMC Nakagami images (p-value > .05). In the animal experiments, the Nakagami parameters obtained from the WMC Nakagami image for normal and cirrhotic rat livers were 0.62 ± 0.08 and 0.92 ± 0.07, respectively (p-value < .05). The results demonstrated that the WMC technique significantly improved the image smoothness of Nakagami imaging without resolution degradation, giving Nakagami model-based imaging the ability to visualize scatterer properties with enhanced image quality.     

Generalized total variation-based MRI Rician denoising model with spatially adaptive regularization parameters

Magnetic resonance imaging (MRI) is an outstanding medical imaging modality but the quality often suffers from noise pollution during image acquisition and transmission. The purpose of this study is to enhance image quality using feature-preserving denoising method. In current literature, most existing MRI denoising methods did not simultaneously take the global image prior and local image features into account. The denoising method proposed in this paper is implemented based on an assumption of spatially varying Rician noise map. A two-step wavelet-domain estimation method is developed to extract the noise map. Following a Bayesian modeling approach, a generalized total variation-based MRI denoising model is proposed based on global hyper-Laplacian prior and Rician noise assumption. The proposed model has the properties of backward diffusion in local normal directions and forward diffusion in local tangent directions. To further improve the denoising performance, a local variance estimator-based method is introduced to calculate the spatially adaptive regularization parameters related to local image features and spatially varying noise map. The main benefit of the proposed method is that it takes full advantage of the global MR image prior and local image features. Numerous experiments have been conducted on both synthetic and real MR data sets to compare our proposed model with some state-of-the-art denoising methods. The experimental results have demonstrated the superior performance of our proposed model in terms of quantitative and qualitative image quality evaluations.