Über die Dichten von Soda- und Ätznatron lösungen

Ohne Zusammenfassung     

Die Kautschukchemie im Jahre 1914

Ohne Zusammenfassung     

Strongly confined quantum wire states in strained T-shaped GaAs/InAlAs structures

The confinement energy of T-shaped quantum wires (QWRs), which were fabricated by the cleaved edge overgrowth technique in a way that the QWRs form at the intersection of In_0.2Al_0.8As stressor layers and the overgrown (1 1 0) GaAs quantum well (QW), is examined using micro-photoluminescence spectroscopy. Photoluminescence (PL) signals from individual QWRs can be spatially resolved, since the strained films are separated by 1 μm wide Al_0.3Ga_0.7As layers. We find that due to the tensile strain being transmitted to the QW, the confinement energy of the QWRs rises systematically up to 40 meV with increasing thickness of the stressor layers. By reducing the excitation power to 0.1 μW the QWR PL emission occurs 48 meV redshifted with respect to the QW. All QWR peaks exhibit smooth lineshapes, indicating the absence of pronounced exciton localization.     

Metastable phase in the quantum Hall ferromagnet

Time-dependent capacitance measurements reveal an unstable phase of electrons in gallium arsenide quantum well that occurs when two Landau levels with opposite-spin are brought close to degeneracy by applying a gate voltage. This phase emerges below a critical temperature and displays a peculiar non-equilibrium dynamical evolution. The relaxation dynamics is found to follow a stretched-exponential behaviour and correlates with hysteresis loops observed by sweeping the magnetic field. These experiments indicate that metastable randomly distributed magnetic domains with peculiar excitations are involved in the relaxation process in a way that is equivalently tunable by a change in gate voltage or temperature.     

A neuro-fuzzy system for X-ray spectra interpretation

A decision scheme for the interpretation of spectra from wavelength dispersive X-ray fluorescence spectrometry is described that encompasses elements from three areas of artificial intelligence: fuzzy logic, rule based expert systems and neural net technology.After transforming the recorded spectra to line spectra by appropriate background correction a reasoning scheme is applied that takes into account not only the observed spectra, but also the recording conditions and prior spectroscopic information regarding the relative emission probabilities and the usefulness of the different lines for the purpose of element identification. The latter is done on the basis of a previously described scheme to compute conditional a posteriori Bayes probabilities for a mean matrix. These different pieces of information are then assembled into a battery of fuzzy rules. The importance of the rules as well as the importance of the X-ray lines is determined in a training process, similar to the one in a feedforward back-propagation network.To further stabilize the results this network is pruned in a second training cycle. This, however, had little effect on the quality of interpretation.The advantages of this approach to the interpretation of X-ray spectra over older ones are numerous: the system adapts itself to better interpret spectra that are of greater importance to a laboratory as these are better represented in the training set; the fuzzy logic is capable of working with incomplete and uncertain knowledge, and the neural network results based on these fuzzy rules is readily interpretable by the X-ray spectroscopist as every rule can be expressed also in natural language as in any classical rule based system.On leave from Silesian University, Katowice, Poland     

A fundamental parameters approach including scattered radiation for mono-energetically excited samples in energy-dispersive x-ray fluorescence spectrometry

A fundamental parameters approach that incorporates data on scattered radiation is shown to be a useful tool for the determination of trace elements in light matrices. For thick, transparent samples, a computer program is developed that uses differetial intensity equations adjusted for decreasing geometric efficiency. Various organic and biological reference materials are analysed to assess the reliability of the procedure. A nested design for analysis of variance shows that major errors can originate from the deconvolution process and sample inhomogeneities in many cases. For loose powders, great care must be exercised to avoid errors caused by scatter from the sample cups. The program is also useful for alloys.