Temporal investigation of acoustic wave pressure spectrum of high repetition rate TEA-CO2 lasers by using a three-dimensional mathematical model

The production of acoustic wave is one of the most important factors on the action of High Repetition Rate TEA-CO₂ lasers. In this paper a three-dimensional mathematical modeling has been considered for investigation of temporal and spatial variations of acoustic waves in the laser cavity and its effect on the output of HRR lasers. By calculation of equations obtained from this model and plotting the pressure spectrum in different states, the effect of electrodes dimensions, cavity dimensions, gas flow velocity and repetition rate of laser in different times have been acquired. At last, optimum conditions for performance of laser action and having a good output have been arrived.     

Synthesis,thermal analysis,and linear and nonlinear optical characterization of substituted polyphosphonates derived from 1,12‐dodecanediol

The syntheses of a series of substituted polyphosphonates of the type [OP(X)(Ar)O(CH₂)₁₂]_n (X = O, S, Se; Ar = phenyl, 2,2′‐bithienyl‐5‐yl) are reported. The s for the polyphosphonates range from 1.1 to 4.6 × 10⁴ Da and are significantly higher than those previously reported for polyphosphonates synthesized via polycondensation reactions. Thermal characterization indicates that all of the polymers are in the rubbery state at room temperature and have thermal stabilities as high as 290 °C. The linear absorption spectra, emission spectra, and emission quantum yields of the 2,2′‐bithenyl‐5‐yl substituted polyphosphonates show distinct trends with respect to the chalcogen attached to the phosphorus. Solutions of these polymers show emission at wavelengths ranging from 380 to 400 nm and, depending on the choice of X, the quantum yields are considerably larger than that of 2,2′‐bithiophene. Nonlinear optical measurements of the polyphosphonates with 2,2′‐bithenyl‐5‐yl substituents show that nonlinear absorbance increases with increasing molecular weight of X. © 2016 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2016 , 54, 3663–3674     

Size and shape-dependent melting mechanism of Pd nanoparticles

Molecular dynamics simulation was employed to understand the thermodynamic behavior of cuboctahedron (cub) and icosahedron (ico) nanoparticles with 2–20 number of full shells. The original embedded atom method (EAM) was compared to the more recent highly optimized version as inter-atomic potential. The thermal stability of clusters were probed using potential energy and specific heat capacity as well as structure analysis by radial distribution function (G(r)) and common neighbor analysis (CNA), simultaneously, to make a comprehensive picture of the solid-state and melting transitions. The result shows ico is the only stable shape of small clusters (Pd₅₅–Pd₃₀₉ using original EAM and Pd₅₅ using optimized version) those are melting uniformly due to their small diameter. An exception is cub Pd₃₀₉ modeled via optimized EAM that transforms to ico at elevated temperatures. A similar cub to ico transition was predicted by original EAM for Pd₉₂₃–Pd₂₀₇₅ clusters, while for the larger clusters both cub and ico are stable up to the melting point. As detected by \(G(r)\) and CNA, moderate and large cub clusters were showing surface melting by nucleation of the liquid phase at (100) planes and growth of liquid phase at the surface before inward growth. While diagonal (one corner to another) melting was dominating over ico clusters owing to their partitioned structure, which retarded the growth of the liquid phase. The large ico clusters, using optimized EAM, presented a combination of surface and diagonal melting due to the simultaneous diagonal melting started from different corners. Finally, the melting temperature as well as latent heat of fusion were calculated and compared with the available models and previous studies, which showed, unlike the present result, the models failed to predict size-dependent motif cross-over.     

Study the effect of striping in two-step anodizing process on pore arrangement of nano-porous alumina

Two-step anodic oxidation of aluminum is generally employed to produce the ordered porous anodized alumina (PAA). Dissolving away (striping) the oxide film after the first anodizing step plays a key role in the final arrangement of nano-pores. In this work, different striping durations between 1 and 6 h were applied to the sample that was initially anodized at a constant voltage of 40 V at 17 °C for 15 h. The striping duration of 3 h was realized as the optimum time for achieving the best ordering degree for the pores. Scanning electron microscopy (SEM) was used during and at the end of the process to examine the cross section and finishing surface of the specimens. Linear-angular fast Fourier transform (LA-FFT), an in-house technique based on MATLAB software, was employed to assess the ordering degree of the anodized samples.     

Importance of RNA secondary structure information for yeast donor and acceptor splice site predictions by neural networks

Previously, Patterson et al. showed that mRNA structure information aids splice site prediction in human genes [Patterson, D.J., Yasuhara, K., Ruzzo, W.L., 2002. Pre-mRNA secondary structure prediction aids splice site prediction. Pac. Symp. Biocomput. 7, 223-234]. Here, we have attempted to predict splice sites in selected genes of Saccharomyces cerevisiae using the information obtained from the secondary structures of corresponding mRNAs. From Ares database, 154 genes were selected and their structures were predicted by Mfold. We selected a 20-nucleotide window around each site, each containing 4 nucleotides in the exon region. Based on whether the nucleotide is in a stem or not, the conventional four-letter nucleotide alphabet was translated into an eight-letter alphabet. Two different three-layer-based perceptron neural networks were devised to predict the 5' and 3' splice sites. In case of 5' site determination, a network with 3 neurons at the hidden layer was chosen, while in case of 3' site 20 neurons acted more efficiently. Both neural nets were trained applying Levenberg-Marquardt backpropagation method, using half of the available genes as training inputs and the other half for testing and cross-validations. Sequences with GUs and AGs non-sites were used as negative controls. The correlation coefficients in the predictions of 5' and 3' splice sites using eight-letter alphabet were 98.0% and 69.6%, respectively, while these values were 89.3% and 57.1% when four-letter alphabet is applied. Our results suggest that considering the secondary structure of mRNA molecules positively affects both donor and acceptor site predictions by increasing the capacity of neural networks in learning the patterns.