Evolution of Face-Centered Cubic Ti Alloys Transformation by X-ray Diffraction Profile Analysis in Mechanical Alloying

Four titanium alloys (Ti-Ta, Ti-Ta-Sn, Ti-Ta-Mn, and Ti-Nb-Sn) were synthesized by mechanical alloying (MA) in a planetary mill in different times between 2 h and 100 h. The microstructure characterization was made by X-ray diffraction (XRD), in which the Rietveld method was applied to analyze the diffraction patterns. The study demonstrated that after short milling times between 2 h and 30 h, the fraction of hexagonal close-packed (hcp) phase decreases; at the same time, the formation of body-centered cubic (bcc) and face-centered cubic (fcc) Ti phases are promoted. Additionally, after 30 h of MA, the full transformation of hcp-Ti was observed, and the bcc-Ti to fcc-Ti phase transformation took place until 50 h. The results suggest that the addition of Ta and Sn promotes the fcc-Ti phase formation, obtaining 100% of this phase at 50 h onwards, whereas Nb and Mn show the opposite effect.

Determining the Preferred Orientation of Silver-Plating via X-ray Diffraction Profile

Determining the preferred orientation of plating film is of practical importance. In this work, the Rietveld method and quantitative texture analysis (RM+QTA) are used to analyze the preferred orientation of plating silver film with XRD profile, whose <311> axial texture can be completely described by a set of exponential harmonics index, extracted from a single XRD profile, C41,1(0.609), C61,1(0.278), C81,1(−0.970). The constructed pole figures with the index of the exponential harmonic are following those measured by the multi-axis diffractometer. The method using exponential harmonic index can be extended to characterize the plating by electroplating in a quantitative harmonic description. In addition, a new dimension involving crystallite shape and size is considered in characterizing the preferred orientation.

Dominating the Structural, Microstructural and Magnetic Features of Li+ Substituted Strontium Hexaferrite (Sr1-xLi2xFe12O19)

Lithium ion substituted hexagonal strontium ferrite (Sr1-xLi2xFe12O19, where x= 0.1, 0.2, and 0.3) powders have been felicitously fabricated using tartrate precursor scheme. The impact of the Li+ content, as well as the annealing temperature on the phase evolution, microstructure and magnetic performance, was commanded by X-ray diffraction profile (XRD), scanning electron microscopy (SEM), and vibrating sample magnetometer (VSM). Single phase hexagonal ferrite was consummated at a Li+ ratio of 0.2 and different annealing temperatures, from 1000 to 1200oC for 2h. An impurity α-Fe2O3 phase was noted at a high Li+ concentration of 0.4 and 0.6 at all temperatures. The crystallo-aspects characteristics were altered with Li+ content and annealing temperature. The microstructure of pure hexagonal ferrite sample visualized platelet like structure. A fine spherical shape displayed with platelet shape by enhancing the Li+ content up to 0.4 and 0.6. EDX analysis emphasized Fe, Sr, O, and Li atoms spread between the plate and spherical shapes. Good saturation magnetization (Ms=60.88 emu/g) was realized for Li+ content of 0.2 as the results of increasing the thickness of the nanoplatelet structure.

Whole pair distribution function modeling: the bridging of Bragg and Debye scattering theories

Microstructure-based design of materials requires an atomic level understanding of the mechanisms underlying structure-dependent properties. Methods for analyzing either the traditional diffraction profile or the pair distribution function (PDF) differ in how the information is accessed and in the approximations usually applied. Any variation of structural and microstructural features over the whole sample affects the Bragg peaks as well as any diffuse scattering. Accuracy of characterization relies, therefore, on the reliability of the analysis methods. Methods based on Bragg's law investigate the diffraction peaks in the intensity plot as distinct pieces of information. This approach reaches a limitation when dealing with disorder scenarios that do not conform to such a peak-by-peak basis. Methods based on the Debye scattering equation (DSE) are, otherwise, well suited to evaluate the scattering from a disordered phase but the structure information is averaged over short-range distances usually accessed by experiments. Moreover, statistical reliability is usually sacrificed to recover some of the computing-efficiency loss compared with traditional line-profile-analysis methods. Here, models based on Bragg's law are used to facilitate the computation of a whole PDF and then model powder-scattering data via the DSE. Models based on Bragg's law allow the efficient solution of the dispersion of a crystal's properties in a powder sample with statistical reliability, and the PDF provides the flexibility of the DSE. The whole PDF is decomposed into the independent directional components, and the number of atom pairs separated by a given distance is statistically estimated using the common-volume functions. This approach overcomes the need for an atomistic model of the material sample and the computation of billions of pair distances. The results of this combined method are in agreement with the explicit solution of the DSE although the computing efficiency is comparable with that of methods based on Bragg's law. Most importantly, the method exploits the strengths and different sensitivities of the Bragg and Debye theories.

`Pink'-beam X-ray powder diffraction profile and its use in Rietveld refinement

The powder diffraction profile obtained with a pink-beam synchrotron X-ray source is described as the convolution of a back-to-back pair of exponentials convoluted with the Gaussian and Lorentzian components of a pseudo-Voigt. This new function is employed for the first time in a Rietveld refinement using data collected from a single 100 ps synchrotron X-ray micropulse.

High-Resolution Strain/Stress Measurements by Three-Axis Neutron Diffractometer

Resolution properties of the unconventional high-resolution neutron diffraction three-axis setup for strain/stress measurements of large bulk polycrystalline samples are presented. Contrary to the conventional two-axis setups, in this case, the strain measurement on a sample situated on the second axis is carried out by rocking the bent perfect crystal (BPC) analyzer situated on the third axis of the diffractometer. Thus, the so-called rocking curve provides the sample diffraction profile. The neutron signal coming from the analyzer is registered by a point detector. This new setup provides a considerably higher resolution (at least by a factor of 5), which however, requires a much longer measurement time. The high-resolution neutron diffraction setting can be effectively used, namely, for bulk gauge volumes up to several cubic centimeters, and for plastic deformation studies on the basis of the analysis of diffraction line profiles, thus providing average values of microstructure characteristics over the irradiated gauge volume.

Design of optical meta-structures with applications to beam engineering using deep learning

Nanophotonics is a rapidly emerging field in which complex on-chip components are required to manipulate light waves. The design space of on-chip nanophotonic components, such as an optical meta surface which uses sub-wavelength meta-atoms, is often a high dimensional one. As such conventional optimization methods fail to capture the global optimum within the feasible search space. In this manuscript, we explore a Machine Learning (ML)-based method for the inverse design of the meta-optical structure. We present a data-driven approach for modeling a grating meta-structure which performs photonic beam engineering. On-chip planar photonic waveguide-based beam engineering offers the potential to efficiently manipulate photons to create excitation beams (Gaussian, focused and collimated) for lab-on-chip applications of Infrared, Raman and fluorescence spectroscopic analysis. Inverse modeling predicts meta surface design parameters based on a desired electromagnetic field outcome. Starting with the desired diffraction beam profile, we apply an inverse model to evaluate the optimal design parameters of the meta surface. Parameters such as the repetition period (in 2D axis), height and size of scatterers are calculated using a feedforward deep neural network (DNN) and convolutional neural network (CNN) architecture. A qualitative analysis of the trained neural network, working in tandem with the forward model, predicts the diffraction profile with a correlation coefficient as high as 0.996. The developed model allows us to rapidly estimate the desired design parameters, in contrast to conventional (gradient descent based or genetic optimization) time-intensive optimization approaches.

Separation and imaging of seismic diffractions using a localized rank-reduction method with adaptively selected ranks

Seismic diffractions are weak seismic events hidden within the more dominant reflection events in a seismic profile. Separating diffraction energy from the poststack seismic profiles can help infer the subsurface discontinuities that generate the diffraction events. The separated seismic diffractions can be migrated with a traditional seismic imaging method or a specifically designed migration method to highlight the diffractors, that is, the diffraction image. Traditional diffraction separation methods based on the underlying plane-wave assumption are limited by either the inaccurate slope estimation or the plane-wave assumption of the plane-wave destruction filter and thus will cause reflection leakage into the separated diffraction profile. The leaked reflection energy will deteriorate the resolution of the subsequent diffraction imaging result. We have adopted a new diffraction separation method based on a localized rank-reduction (LRR) method. The LRR method assumes the reflection events to be locally low-rank and the diffraction energy can be separated by a rank-reduction operation. Compared to the global rank-reduction method, the LRR method is more constrained in selecting the rank and is free of separation artifacts. We use a carefully designed synthetic example to demonstrate that the LRR method can help separate the diffraction energy from a poststack seismic profile with kinematically and dynamically accurate performance.

Modification of pseudobrookite Fe1.7Mn0.3-xNixTiO5: Influence of Ni-substitution on the magnetic properties

In this study, the synthesis of pseudobrookite Fe1.7Mn0.3-xNixTiO5 with variations in composition (x = 0.01, 0.05, 0.1, and 0.15) using a mechanical milling technique has been performed. High purity powder of α-Fe2O3, TiO2, MnCO3, and NiO were prepared as raw materials. The mixture was milled for 5 hours using high energy milling equipment, and sintered at 1000 °C for 5 hours. The refinement result of X-ray diffraction profile shows that the all of pseudobrookite Fe1.7Mn0.3-xNixTiO5 samples have a single phase with particle size of less than 1 μm. The VSM result shows all the samples were ferromagnetic behavior. We concluded that the substitution Ni into Mn on the pseudobrookite Fe1.7Mn0.3-xNixTiO5 can change the magnetic properties of the material from paramagnetic to ferromagnetic through a mechanism of double exchange interaction.