Microstructure and secondary phases in coevaporated CuInS2 films: Dependence on growth temperature and chemical composition

The microstructure of CuInS2-(CIS2) polycrystalline films deposited onto Mo-coated glass has been analyzed by Raman scattering, Auger electron spectroscopy (AES), transmission electron microscopy, and x-ray diffraction techniques. Samples were obtained by a coevaporation procedure that allows different Cu-to-In composition ratios (from Cu-rich to Cu-poor films). Films were grown at different temperatures between 370 and 520-°C. The combination of micro-Raman and AES techniques onto Ar+-sputtered samples has allowed us to identify the main secondary phases from Cu-poor films such as CuIn5S8 (at the central region of the layer) and MoS2 (at the CIS2/Mo interface). For Cu-rich films, secondary phases are CuS at the surface of as-grown layers and MoS2 at the CIS2/Mo interface. The lower intensity of the MoS2 modes from the Raman spectra measured at these samples suggests excess Cu to inhibit MoS2 interface formation. Decreasing the temperature of deposition to 420-°C leads to an inhibition in observing these secondary phases. This inhibition is also accompanied by a significant broadening and blueshift of the main A1 Raman mode from CIS2, as well as by an increase in the contribution of an additional mode at about 305 cm-1. The experimental data suggest that these effects are related to a decrease in structural quality of the CIS2 films obtained under low-temperature deposition conditions, which are likely connected to the inhibition in the measured spectra of secondary-phase vibrational modes.

Short-term effects of prescribed burning on wood-rotting fungi

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Random-field Potts model with dipolarlike interactions: Hysteresis avalanches and microstructure

A model for the study of hysteresis and avalanches in a first-order phase transition from a single variant phase to a multivariant phase is presented. The model is based on a modification of the random-field Potts model with metastable dynamics by adding a dipolar interaction term truncated at nearest neighbors. We focus our study on hysteresis loop properties, on the three-dimensional microstructure formation, and on avalanche statistics.

Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data.

Microstructure imaging from diffusion magnetic resonance (MR) data represents an invaluable tool to study non-invasively the morphology of tissues and to provide a biological insight into their microstructural organization. In recent years, a variety of biophysical models have been proposed to associate particular patterns observed in the measured signal with specific microstructural properties of the neuronal tissue, such as axon diameter and fiber density. Despite very appealing results showing that the estimated microstructure indices agree very well with histological examinations, existing techniques require computationally very expensive non-linear procedures to fit the models to the data which, in practice, demand the use of powerful computer clusters for large-scale applications. In this work, we present a general framework for Accelerated Microstructure Imaging via Convex Optimization (AMICO) and show how to re-formulate this class of techniques as convenient linear systems which, then, can be efficiently solved using very fast algorithms. We demonstrate this linearization of the fitting problem for two specific models, i.e. ActiveAx and NODDI, providing a very attractive alternative for parameter estimation in those techniques; however, the AMICO framework is general and flexible enough to work also for the wider space of microstructure imaging methods. Results demonstrate that AMICO represents an effective means to accelerate the fit of existing techniques drastically (up to four orders of magnitude faster) while preserving accuracy and precision in the estimated model parameters (correlation above 0.9). We believe that the availability of such ultrafast algorithms will help to accelerate the spread of microstructure imaging to larger cohorts of patients and to study a wider spectrum of neurological disorders.

Decision support systems in wood procurement. A Review

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Microstructure of highly oriented, hexagonal, boron nitride thin films grown on crystalline silicon by radio frequency plasma-assisted chemical vapor deposition

We present a high‐resolution electron microscopy study of the microstructure of boron nitride thin films grown on silicon (100) by radio‐frequency plasma‐assisted chemical vapor deposition using B2H6 (1% in H2) and NH3 gases. Well‐adhered boron nitride films grown on the grounded electrode show a highly oriented hexagonal structure with the c‐axis parallel to the substrate surface throughout the film, without any interfacial amorphous layer. We ascribed this textured growth to an etching effect of atomic hydrogen present in the gas discharge. In contrast, films grown on the powered electrode, with compressive stress induced by ion bombardment, show a multilayered structure as observed by other authors, composed of an amorphous layer, a hexagonal layer with the c‐axis parallel to the substrate surface and another layer oriented at random

Karyotypic variation between wood mouse species: banded chromosomes of Apodemus alpicola and A-microps

The banding pattern (G-, C-, AgNOR-staining) was described in karyotypes of Apodemus alpicola Heinrich, 1952 and A. microps Kratochvil et Rosicky, 1952 collected from the Alps and central Europe, Distinct differences between the two species were revealed in the distribution of C-heterochromatic regions in autosomes and the sex chromosomes, and the distribution of nucleolar organizer regions (NORs). Extensive variation in the distribution pattern of C-heterochromatin and NORs obviously exists among the wood mice of the subgenus Sylvaemus, and individual species can be distinguished according to a specific variation pattern. However, it seems premature to designate individual karyotypic forms as separate species, because the extent of overall geographical interpopulation variation is still not sufficiently known.

A Local DLP-GIS-LP system for geographically decentralized wood procurement planning and decision making

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