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Paper des Monats
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A thorough characterization of base materials is the prereq- uisite for further research. In this paper, the characterization data of the reference materials (CEM I 42.5 R, limestone pow- der, calcined clay and a mixture of these three components) used in the second funding phase of the priority program 2005 of the German Research Foundation (DFG SPP 2005) are presented under the aspects of chemical and min- eralogical composition as well as physical and chemical properties. The data were collected based on tests performed by up to eleven research groups involved in this cooperative program.
This paper presents the results of an interlaboratory study of the rheological properties of cement paste and ultrasound gel as reference substance. The goal was to quantify the comparability and reproducibility of measurements of the Bingham parameters yield stress and plastic viscosity when measured on one specific paste composition and one particular ultrasound gel in different laboratories using different rheometers and measurement geometries.
The procedures for both in preparing the cement paste and carrying out the rheological measurements on cement paste and ultrasound gel were carefully defined for all of the study’s participants. Different conversion schemes for comparing the results obtained with the different measurement setups are presented here and critically discussed. The procedure proposed in this paper ensured a reasonable comparability of the results with a coefficient of variation for the yield stress of 27% and for the plastic viscosity of 24%, despite the individual measurement series’ having been performed in different labs with different rheometers and measurement geometries.
A thorough characterization of starting materials is the precondition for further research, especially for cement, which contains various phases and presents quite a complex material for fundamental scientific investigation. In the paper at hand, the characterization data of the reference cement CEM I 42.5 R used within the priority program 2005 of the German Research Foundation (DFG SPP 2005) are presented from the aspects of chemical and mineralogical compositions as well as physical and chemical properties. The data were collected based on tests conducted by nine research groups involved in this cooperative program. For all data received, the mean values and the corresponding errors were calculated. The results shall be used for the ongoing research within the priority program.
Two types of cements were selected as the reference cement in the priority program 2005 of the German Research Foundation (DFG SPP 2005). A thorough characterization of CEM I 42.5 R has been made in a recent publication. In this paper, the characterization data of the other reference cement CEM III/A 42.5 N are presented from the aspects of chemical and mineralogical compositions as well as physical and chemical properties. The characterization data of the slag, which is the second main constituent of this specific cement besides the clinker, are presented independently. For all data received, the mean values and the corresponding errors were calculated. The data shall be used for the ongoing research within the priority program. Also, researchers from outside this priority program can benefit from these data if the same materials are used.
Environmental Risk Assessment of Treated Timber in Service - the Environment Focus Group Approach
(2000)
In the context of the Biocidal Products Directive (98/8/EC), and of the OECD work on wood preservatives, the Environment Focus Group (EFG), comprising 8 institutes and the European Wood Preservative Manufacturers Group, has been working on the environmental risk assessment of treated timber in service. A literature review of emissions from treated timber has revealed that very little existing data is usable for environmental risk assessment; the most relevant data are kinetic curves of emissions over time, which show clearly the non-linear emissions behaviour of treated wood over time. The EFG has suggested real exposure conditions for treated timber in the environment, and listed typical exposure scenarios. Five representative scenarios are characterised in detail, for use in the calculation of Predicted Environmental Concentrations (PECs). The existing methods to determine emissions from treated wood have been reviewed. Most existing experimental models cannot be used to predict environmental emissions. Monitoring of commodities in service has its specific constraints. Chemical analysis and ecotoxicity testing have also been reviewed and their relationship has been discussed. Principles for the design of experimental models, for the determination of emission fluxes from treated wood to the environment, have been established.
The present work shows results on elemental distribution analyses in Cu(In,Ga)Se2 thin films for solar cells performed by use of wavelength-dispersive and energy-dispersive X-ray spectrometry (EDX) in a scanning electron microscope, EDX in a transmission electron microscope, X-ray photoelectron, angle-dependent soft X-ray emission, secondary ion-mass (SIMS), time-of-flight SIMS, sputtered neutral mass, glow-discharge optical emission and glow-discharge mass, Auger electron, and Rutherford backscattering spectrometry, by use of scanning Auger electron microscopy, Raman depth profiling, and Raman mapping, as well as by use of elastic recoil detection analysis, grazing-incidence X-ray and electron backscatter diffraction, and grazing-incidence X-ray fluorescence analysis. The Cu(In,Ga)Se2 thin films used for the present comparison were produced during the same identical deposition run and exhibit thicknesses of about 2 µm. The analysis techniques were compared with respect to their spatial and depth resolutions, measuring speeds, availabilities, and detection limits.
Interfacing artificial devices with the human brain is the central goal of neurotechnology. Yet, our imaginations are often limited by currently available paradigms and technologies. Suggestions for brain−machine interfaces have changed over time, along with the available technology.
Mechanical levers and cable winches were used to move parts of the brain during the mechanical age. Sophisticated electronic wiring and remote control have arisen during the electronic age, ultimately leading to plug-and-play computer interfaces. Nonetheless, our brains are so complex that these visions, until recently, largely remained unreachable dreams. The general problem, thus far, is that most of our technology is mechanically and/or electrically engineered, whereas the brain is a living, dynamic entity. As a result, these worlds are difficult to interface with one another. Nanotechnology, which encompasses engineered solid-state objects and integrated circuits, excels at small length scales of single to a few hundred nanometers and, thus, matches the sizes of biomolecules, biomolecular assemblies, and parts of cells. Consequently, we envision nanomaterials and nanotools as opportunities to interface with the brain in alternative ways. Here, we review the existing literature on the use of nanotechnology in brain−machine interfaces and look forward in discussing perspectives and limitations based on the authors’ expertise across a range of complementary disciplines from neuroscience, engineering, physics, and chemistry to biology and medicine, computer science and mathematics, and social science and jurisprudence. We focus on nanotechnology but also include information from related fields when useful and complementary.
Alkali-activated binders (AAB) can provide a clean alternative to conventional cement in terms of CO2 emissions. However, as yet there are no sufficiently accurate material models to effectively predict the AAB properties, thus making optimal mix design highly costly and reducing the attractiveness of such binders. This work adopts sequential learning (SL) in high-dimensional material spaces (consisting of composition and processing data) to find AABs that exhibit desired properties. The SL approach combines machine learning models and feedback from real experiments. For this purpose, 131 data points were collected from different publications. The data sources are described in detail, and the differences between the binders are discussed. The sought-after target property is the compressive strength of the binders after 28 days. The success is benchmarked in terms of the number of experiments required to find materials with the desired strength. The influence of some constraints was systematically analyzed, e.g., the possibility to parallelize the experiments, the influence of the chosen algorithm and the size of the training data set. The results show the advantage of SL, i.e., the amount of data required can potentially be reduced by at least one order of magnitude compared to traditional machine learning models, while at the same time exploiting highly complex information. This brings applications in laboratory practice within reach.
The device performance of polycrystalline chalcogenide thin film solar cells is strongly influenced by different kinds of defects within the material. The presence of sodium or other alkali metals like potassium during the deposition process is well known to influence the electronic properties of the solar cell and thus to improve the efficiency of the final device. Structural analysis of neutron powder diffraction data collected at low temperatures and subsequent profile analysis by the LeBail and Rietveld method demonstrates the impact of sodium on the point defect characteristics in off stoichiometric CuInSe2. The analyzed materials are powder and thin film solar absorber material with addition of NaF and free of sodium. It is illustrated, the so called “sodium effect” cannot be reduced to one single origin. A range of effects, the reduction of InCu donors with a followed increase of VCu acceptors is possible. The main effect is an increased ordered character of the chalcopyrite crystal structure at off stoichiometric composition, when containing sodium.
Bitumen is a crucial building material in road construction, which is exposed to continuously higher stresses due to higher traffic loads and changing climatic conditions. Therefore, various additives are increasingly being added to the bitumen complicating the characterisation of the bituminous binder, especially concerning the reuse of reclaimed asphalt.
Therefore, this work aimed to demonstrate that the combination of Fourier transform infrared (FTIR) spectroscopy with attenuated total reflexion (ATR) technique and multivariate evaluation is a very wellsuited method to reliable identify and quantify additives in bituminous binders. For this purpose, various unmodified and modified binders, directly and extracted from laboratory and reclaimed asphalts, were investigated with FTIR-ATR spectroscopy. The determined spectra, pre-processed by standard normal variate (SNV) transformation and the determination of the 1st derivation, were evaluated using factor Analysis (FA), linear discriminant analysis (LDA) and partial least square regression (PLSR). With this multivariate evaluation, first, a significant model with a very high hit rate of over 90% was developed allowing for the identification of styrene-butadiene copolymers (SBC), ethylene-copolymer bitumen (ECB) and different waxes (e.g. amide and Fischer-Tropsch wax) even if the additives do not show any additional peaks or the samples are multi-modified. Second, a quantification of the content is possible for SBC, ECB, and Amide wax with a mean error of RMSE B 0.4 wt% and a
coefficient of determination of R2[90%. Based on these results, FTIR identification and quantification of additives in bituminous binders is a very promising method with a great potential.
