Indentation deformation and cracking behavior of hydrated aluminoborate glasses

Aluminoborate glasses have recently been found to feature high resistance to crack initiation during indentation due to a highly flexible network structure. In cesium aluminoborate glasses, it has been found that the use of a simple post-treatment, namely aging in a humid atmosphere, can further improve this resistance. To better understand the mechanical properties of this glass family upon humid aging, we here study the effect of aging conditions on the structure and mechanical properties of Li,K,Cs-aluminoborate glasses. As expected, we find that higher humidity and longer aging time cause more pronounced permeation of atmospheric water into the glasses. Due to their denser structure and stronger modifier-oxygen bonds, the humid aging has a relatively smaller effect on the mechanical properties of Li- and K-containing glasses relative to Cs-containing glasses, with the latter achieving an ultrahigh crack resistance. We find that the humid aging leads to the formation of a hydration layer in the Cs-aluminoborate glass surface, with a thickness of around 26 μm upon aging at 23 °C with 40% relative humidity for 7 days. Moreover, a remarkable indentation behavior, that is, the observation of μm-sized shear bands inside the imprint of the Cs-glass upon aging at 60% relative humidity is reported. Taken as a whole, the work provides guidelines for how to control the humid aging rate as a function of relative humidity and temperature to form a hydration layer and thus achieve improved crack resistance in such glasses.     

Multicriteria optimization as enabler for Sustainable Ceramic Matrix Composites

Over the past 40 years, development of Ceramic Matrix Composites (CMCs) has focused mainly on the improvement of material performance and optimization of cost-efficient production routes. Recently, more fields of application have opened up for CMCs, in which environmental impacts are relevant. These impacts have barely been investigated so far but receive growing interest due to increasing awareness of the environmental consequences. Our innovative approach frames material properties in relation to environmental impacts (e.g., global warming potential in CO₂ emission) by varying process parameters to balance optimum performance against environmental considerations. First, the process of wet filament winding has been investigated up to the Carbon Fiber Reinforced Plastic (CFRP) state by changing both the curing and tempering temperatures. During the production of CFRP plates, mass and energy flows were tracked in each step. Three point-bending and interlaminar shear tests have been performed on the resulting samples to identify basic mechanical properties. The environmental impacts are determined by a cradle-to-gate Life Cycle Assessment (LCA), using the software SimaPro. The resulting tradeoffs between mechanical properties and environmental impacts show nonlinear behavior, thus revealing optimum points above which improved mechanical properties are associated with significantly higher CO₂ emissions.     

Numerical Simulations of Lubricating Grease Flow in a Rectangular Channel with and without Restrictions

This article presents numerical simulations of the laminar flow of lubricating greases in a channel with rectangular cross section. Three greases with different consistencies (NLGI grades 00, 1, and 2) have been considered in three different configurations composed of a rectangular channel without restrictions, one rectangular step restriction, and one double-lip restriction. The driving pressure drop over the channel spans from 30 to 250 kPa. The grease rheology is described by the Herschel-Bulkley rheology model, and both the numerical code and rheology model have been validated with analytical solutions and flow measurements using micro-particle image velocimetry.     

Enhanced performance in the deteriorated area of multicrystalline silicon wafers by internal gettering

The deteriorated area of the multicrystalline silicon (mc‐Si) ingots grown by directional solidification, commonly known as the Red Zone, is usually removed before wafering. This area, characterized by poor minority carrier lifetime, is located on the sides, at the top, and the bottom of the mc‐Si ingots. In this study, the effect of internal gettering by oxygen precipitates and structural defects has been investigated on the bottom zone of a mc‐Si ingot. Nucleation and growth of oxygen precipitates as well as low temperature annealing were studied. Photoluminescence imaging, lifetime mapping, and interstitial iron measurements performed by μ‐PCD reveal a considerable reduction of the bottom Red Zone. An improvement of lifetime from below 1 µs to about 20 µs and a reduction of interstitial iron concentration from 1.32 × 10¹³ at/cm³ to 8.4 × 10¹⁰ at/cm³ are demonstrated in this paper. Copyright © 2013 John Wiley & Sons, Ltd.     

Nanopaper membranes from chitin–protein composite nanofibers—structure and mechanical properties

Chitin nanofibers may be of interest as a component for nanocomposites. Composite nanofibers are therefore isolated from crab shells in order to characterize structure and analyze property potential. The mechanical properties of the porous nanopaper structures are much superior to regenerated chitin membranes. The nanofiber filtration‐processing route is much more environmentally friendly than for regenerated chitin. Minerals and extractives are removed using HCl and ethanol, respectively, followed by mild NaOH treatment and mechanical homogenization to maintain chitin–protein structure in the nanofibers produced. Atomic force microscope (AFM) and scanning transmission electron microscope (STEM) reveal the structure of chitin–protein composite nanofibers. The presence of protein is confirmed by colorimetric method. Porous nanopaper membranes are prepared by simple filtration in such a way that different nanofiber volume fractions are obtained: 43%, 52%, 68%, and 78%. Moisture sorption isotherms, structural properties, and mechanical properties of membranes are measured and analyzed. The current material is environmentally friendly, the techniques employed for both individualization and membrane preparation are simple and green, and the results are of interest for development of nanomaterials and biocomposites. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40121.     

Air Flow and Compression Work in Vacuum Dewatering of Paper

Dewatering on the paper machine takes place by gravity, suction, pressing, and evaporation. Optimizing the operation of the vacuum system is important, since the electricity consumption of the vacuum pumps might be one-fifth of the total electricity consumption of the paper machine. Vacuum dewatering involves large volumes of air penetrating the web. The present study presents four sets of measured air flow rates useful for designing industrial equipment. The mass flux of air increases with increasing applied vacuum and decreases with increasing basis weight. Paper technological parameters, such as fiber size and fiber flexibility, also influence the mass flux.     

Air entrapment in sheet molding compounds (SMC)

Entrapped air can commonly lead to large delaminations in thick walled sheet molding compound (SMC) products. In this work different sources of air entrapment in SMC are investigated. The critical process is shown to be the impregnation of the fibers. If no surface active additives are used, large volumes of air may be entrapped in this process, unless the viscosity of the compound is very low. In this situation of poor wetting, the viscosity of the compound during fiber impregnation will critically determine the interlaminar, tensile strength of the product. However, if surface active additives are used, the air escapes entrapment even at relatively high viscosities. The lowering of the viscosity, which is a side effect of the additives, has practically no importance under these conditions of good wetting. Large numbers of small air bubbles are also entrapped during the mixing of the components, but it is shown that these bubbles have very little effect on the mechanical properties of the finished part.     

Classification of Amyloidosis by Model-Assisted Mass Spectrometry-Based Proteomics

Amyloidosis is a rare disease caused by the misfolding and extracellular aggregation of proteins as insoluble fibrillary deposits localized either in specific organs or systemically throughout the body. The organ targeted and the disease progression and outcome is highly dependent on the specific fibril-forming protein, and its accurate identification is essential to the choice of treatment. Mass spectrometry-based proteomics has become the method of choice for the identification of the amyloidogenic protein. Regrettably, this identification relies on manual and subjective interpretation of mass spectrometry data by an expert, which is undesirable and may bias diagnosis. To circumvent this, we developed a statistical model-assisted method for the unbiased identification of amyloid-containing biopsies and amyloidosis subtyping. Based on data from mass spectrometric analysis of amyloid-containing biopsies and corresponding controls. A Boruta method applied on a random forest classifier was applied to proteomics data obtained from the mass spectrometric analysis of 75 laser dissected Congo Red positive amyloid-containing biopsies and 78 Congo Red negative biopsies to identify novel “amyloid signature” proteins that included clusterin, fibulin-1, vitronectin complement component C9 and also three collagen proteins, as well as the well-known amyloid signature proteins apolipoprotein E, apolipoprotein A4, and serum amyloid P. A SVM learning algorithm were trained on the mass spectrometry data from the analysis of the 75 amyloid-containing biopsies and 78 amyloid-negative control biopsies. The trained algorithm performed superior in the discrimination of amyloid-containing biopsies from controls, with an accuracy of 1.0 when applied to a blinded mass spectrometry validation data set of 103 prospectively collected amyloid-containing biopsies. Moreover, our method successfully classified amyloidosis patients according to the subtype in 102 out of 103 blinded cases. Collectively, our model-assisted approach identified novel amyloid-associated proteins and demonstrated the use of mass spectrometry-based data in clinical diagnostics of disease by the unbiased and reliable model-assisted classification of amyloid deposits and of the specific amyloid subtype.