Imaging crystal orientations in multicrystalline silicon wafers via photoluminescence

We present a method for monitoring crystal orientations in chemically polished and unpassivated multicrystalline silicon wafers based on band-to-band photoluminescence imaging. The photoluminescence intensity from such wafers is dominated by surface recombination, which is crystal orientation dependent. We demonstrate that a strong correlation exists between the surface energy of different grain orientations, which are modelled based on first principles, and their corresponding photoluminescence intensity. This method may be useful in monitoring mixes of crystal orientations in multicrystalline or so-called “cast monocrystalline” wafers.H. C. Sio acknowledges scholarship support from BT Imaging and the Australian Solar Institute, and the Centre for Advanced Microscopy at ANU for SEM access. This work has been supported by the Australian Research Council

High efficiency single quantum well graded-index separate-confinement heterostructure lasers fabricated with MeV oxygen ion implantation

Single quantum well AlGaAs/GaAs graded-index separate-confinement heterostructure lasers have been fabricated using MeV oxygen ion implantation plus optimized subsequent thermal annealing. A high differential quantum efficiency of 85% has been obtained in a 360-µm-long and 10-µm-wide stripe geometry device. The results have also demonstrated that excellent electrical isolation (breakdown voltage of over 30 V) and low threshold currents (22 mA) can be obtained with MeV oxygen ion isolation. It is suggested that oxygen ion implantation induced selective carrier compensation and compositional disordering in the quantum well region as well as radiation-induced lattice disordering in AlxGa1–xAs/GaAs may be mostly responsible for the buried layer modification in this fabrication process

Investigation of the Viscoelastic Effect on Optical- Fiber Sensing and Its Solution for 3D-Printed Sensor Packages

Viscoelasticity is an effect seen in a wide range of materials and it affects the reliability of static measurements made using Fiber Bragg Grating-based sensors, because either the target structure, the adhesive used, or the fiber itself could be viscoelastic. The effect of viscoelasticity on FBG-based sensing has been comprehensively researched through theoretical analysis and simulation using a finite-element approach and a further data processing method to reconstruct the graphical data has been developed. An integrated sensor package comprising of an FBG-based sensor in a polymer host and manufactured by using three-dimensional printing was investigated and examined through tensile testing to validate the approach. The application of the 3D-printed FBG-based sensor package, coupled to the data process method has been explored to monitor the height of a railway pantograph, a critical measurement requirement to monitor elongation, employing a method that can be used in the presence of electromagnetic interference. The results show that the effect of viscoelasticity can be effectively eliminated, and the graphical system response allows results that are sufficiently precise for field use to be generated

A novel element upstream of the Vgamma2 gene in the murine T cell receptor gamma locus cooperates with the 3 enhancer to act as a locus control region.

Transgenic expression constructs were employed to identify a cis-acting transcription element in the T cell receptor (TCR)-gamma locus, called HsA, between the Vgamma5 and Vgamma2 genes. In constructs lacking the previously defined enhancer (3E(Cgamma1)), HsA supports transcription in mature but not immature T cells in a largely position-independent fashion. 3E(Cgamma1), without HsA, supports transcription in immature and mature T cells but is subject to severe position effects. Together, the two elements support expression in immature and mature T cells in a copy number-dependent, position-independent fashion. Furthermore, HsA was necessary for consistent rearrangement of transgenic recombination substrates. These data suggest that HsA provides chromatin-opening activity and, together with 3E(Cgamma1), constitutes a T cell-specific locus control region for the TCR-gamma locus

Preliminary Study of JPSS-1/NOAA-20 VIIRS Day-Night Band Straylight Characterization and Correction Methods

The JPSS-1 (now named NOAA-20) VIIRS instrument has successfully operated since its launch in November 18, 2017. A panchromatic channel onboard NOAA-20 VIIRS is called the day-night band (DNB). With its large dynamic range and high sensitivity, the DNB detectors can make observations during both daytime and nighttime. However, the DNB night image quality is affected by the straylight contamination. In this study, we focused on Earth view data in the midto-high latitude of the northern and southern hemispheres when spacecraft is crossing the day/night terminators at the beginning of NOAA-20 mission. Based on on-orbit data analysis from previous VIIRS sensor onboard S-NPP mission, straylight contamination mainly depends on the Earth-Sun-spacecraft geometry, and it is also detector and scan-angle dependent. Inter-comparison investigation of straylight behavior in both SNPP and NOAA-20 instruments will be conducted to better understand straylight characteristics. The preliminary study has been performed in this paper to mitigate straylight contamination for NOAA-20VIIRS DNB night images. The effectiveness of the straylight correction algorithm, directly adapted from the S-NPP DNB, is assessed for night images in the day/night terminators. Further work has been identified to improve current straylight correction methodology and DNB-based environmental data products.NOAA-20

A Family of Maximum Margin Criterion for Adaptive Learning

In recent years, pattern analysis plays an important role in data mining and recognition, and many variants have been proposed to handle complicated scenarios. In the literature, it has been quite familiar with high dimensionality of data samples, but either such characteristics or large data have become usual sense in real-world applications. In this work, an improved maximum margin criterion (MMC) method is introduced firstly. With the new definition of MMC, several variants of MMC, including random MMC, layered MMC, 2D^2 MMC, are designed to make adaptive learning applicable. Particularly, the MMC network is developed to learn deep features of images in light of simple deep networks. Experimental results on a diversity of data sets demonstrate the discriminant ability of proposed MMC methods are compenent to be adopted in complicated application scenarios.Comment: 14 page