Filtern
Erscheinungsjahr
- 2019 (325) (entfernen)
Dokumenttyp
- Posterpräsentation (325) (entfernen)
Referierte Publikation
- nein (325)
Schlagworte
- Fluorescence (15)
- Additive Manufacturing (11)
- LIBS (9)
- Dangerous Goods Database (8)
- Datenbank GEFAHRGUT (8)
- Nanoparticles (8)
- XRF (8)
- Flow cytometry (7)
- Mechanochemistry (7)
- Biocides (6)
Organisationseinheit der BAM
- 1 Analytische Chemie; Referenzmaterialien (88)
- 6 Materialchemie (76)
- 8 Zerstörungsfreie Prüfung (70)
- 5 Werkstofftechnik (31)
- 4 Material und Umwelt (30)
- 6.6 Physik und chemische Analytik der Polymere (27)
- 6.3 Strukturanalytik (22)
- 1.2 Biophotonik (20)
- 7 Bauwerkssicherheit (20)
- 8.1 Sensorik, mess- und prüftechnische Verfahren (20)
Magnesium is a major element in the hydrosphere and biosphere, and it is direct correlated with the carbon cycle. Therefore, the study of its isotopic fractionation in sediments and sea water helps to understand the earth’s climate and global warming. Mg has three stable isotopes, 24Mg, 25Mg and 26Mg, and traditionally isotope amount ratios are measured by mass spectrometric methods. Their drawbacks include the high costs for instruments and their operation, experienced operators and elaborate time-consuming chromatographic sample preparation. Recently, an optical spectrometric method has been proposed as faster and low-cost alternative for the analysis of isotope ratios: high-resolution continuum source graphite furnace molecular absorption spectrometry (HR-CS-GFMAS).
For the determination of Mg isotope ratios in selected rock reference materials, the high-resolution molecular absorption spectrum of in-situ generated MgF molecule was studied applying multivariate analysis and the results compared with MC-ICP-MS. Samples were dissolved by acid digestion and Mg isotopes analyzed with and without matrix extraction. The absorption spectra were recorded for MgF for the electronic transition X 2Σ → B 2Σ+. The MgF spectrum is described as the linear combination of their isotopic components or isotopologues: 24MgF, 25MgF, and 26MgF. The isotope analysis was done by deconvolution of the MgF spectrum by partial least square regression (PLS). A PLS model was built and calibrated with enriched isotope spikes and certified reference materials. Spectra data was preprocessed by a derivate of second order and venetian blinds cross-validation was employed for finding the optimum latent variables. Finally, the model was refined by a genetic algorithm which identified the best subset of variables for a precise and accurate regression. Results are compatible with those obtained by MC-ICP-MS with an accuracy of ± 0.3‰ with uncertainties ranging between 0.02 to 0.6‰. This accuracy and precision discriminate the isotope fractionation in geological samples, and it is suitable for earth’s climate studies.
Black microcolonial fungi (MCF) are persistent inhabitants of rock surfaces in hostile desert environments. In these niches, MCF have evolved mineral-weathering and symbiotic capabilities as well as mechanisms to cope with multiple stresses such as solar irradiation, temperature extremes and low water activity. Due to their stress tolerance these ascomycetes are prominent in modern terrestrial ecosystems – like man-made material surfaces from roof to solar panels. MCF interactive capabilities support their facultative symbiotic relationships with cyanobacteria and ensure their rock-weathering geochemical activity.
Using the rock-inhabiting fungus K. petricola A95 (Chaetothyriales), we developed transformation protocols and deleted genes responsible for production of the protective pigments melanins and carotenoids. To confirm that the mutant phenotypes were not due to hidden mutations, melanin synthesis was restored by complementing the mutants with the respective wild type genes. Strains of K. petricola carrying gene variants for fluorescent proteins EGFP and DsRed are available. We successfully labelled the cytoplasm, nuclei, peroxisomes and mitochondria. Targeted and ectopic integrations result in stable transformants suitable for further phenotypical characterization. As K. petricola is a non-pathogenic fungus with all characteristic features of MCF, including meristematic growth, melanized cell-walls, extracellular polymeric substances and extensive pigment production, our results will shed light on protective role of pigments during cell wall maturation and oxidative stress defence in rock-inhabiting MCF. Genes involved in environmental sensing or substrate and phototroph interactions are currently targeted. With the help of a mutant collection and fluorescently labelled K. petricola we will be able to investigate interactions of MCF with environmental stressors, mineral substrates, soil matrices and phototrophic symbionts.
The separation of two closely located defects in fields of Thermographic NDE is very challenging. The diffusive nature of thermal waves leads to a fundamental limitation in spatial resolution. Therefore, super resolution image reconstruction can be used. A new concerted ansatz based on spatially structured heating and joint sparsity of the signal ensemble allows an improved reconstruction of closely located defects. This new technique has also been studied using 1D laser arrays in active thermography.
The post-processing can be roughly described by two steps: 1. Finding a sparse basis representation using a reconstruction algorithm such as the Fourier transform, 2. Application of an iterative joint sparsity (IJOSP) method to the firstly reconstructed data. For this reason, different methods in post-processing can be compared using the same measured data set.
The focus in this work was the variation of reconstruction algorithms in step 1 and its influence on the results from step 2. More precise, the measured thermal waves can be transformed to virtual (ultrasound) waves that can be processed by applying ultrasound reconstruction algorithms and finally the super resolution algorithm. Otherwise, it is also possible to make use of a Fourier transform with a subsequent super resolution routine. These super resolution thermographic image reconstruction techniques in post-processing are discussed and evaluated regarding performance, accuracy and repeatability.
The diffusive nature of heat propagation complicates the separation of two closely spaced defects. This results in a fundamental limitation in spatial resolution. Therefore, super resolution (SR) image reconstruction can be used. SR processing techniques based on spatially structured heating and joint sparsity of the signal ensemble allows for an improved reconstruction of closely spaced defects. This new technique has been studied using a 1D laser array with randomly chosen illumination pattern.
This paper presents the results after applying SR algorithms such as the iterative joint sparsity (IJOSP) algorithm, to our processed measurement data. Two different data processing strategies are evaluated and discussed regarding their influence on the reconstruction goodness as well as their complexity. Moreover, the degradation of the SR reconstruction by the choice of regularization parameters in data processing is discussed.
The application of both SR techniques that are evaluated in this paper results in a spatial resolution enhancement of approximately a factor of four which leads to a better separation of two closely spaced defects. The fundamental difference between both SR techniques is their complexity.
The separation of two closely located defects in fields of Thermographic NDE is very challenging. The diffusive nature of thermal waves leads to a fundamental limitation in spatial resolution. Therefore, super resolution image reconstruction can be used.
The measured thermal waves can be transformed to virtual (ultrasound) waves that can be processed by applying ultrasound reconstruction algorithms and finally the super resolution algorithm. Otherwise, it is also possible to make use of a Fourier transform with a subsequent super resolution routine.
These super resolution thermographic image reconstruction techniques in post-processing are discussed and evaluated regarding performance, accuracy and repeatability.
The exploration of metal phosphonates has gained great interest during the last decades, because of their structural diversity. They are promising candidates for a variety of applications ranging from adsorbance to electrocatalysis. The knowledge of the Crystal structure is significant for assigning a coordination polymer for a specific function. We investigated the influence of the fluorination degree of the organic linker on the Crystal packing, the interlayer distance, and the hydrophobicity of the resulting compounds. With fluorinated and nonfluorinated benzylphosphonic acids as starting materials in mechanochemical synthesis, four novel cadmium benzylphosphonates were obtained. Their structures were solved from powder X-ray diffraction.
Metal phosphonates are metal-organic compounds consisting of a metal core and a phosphonate ligand. Depending on the nature of the ligand, metal phosphonates appear in different structures covering the range from molecular compounds to three-dimensional networks. Due to their structural diversity, the chemistry of metal phosphonates has gained great interest during the last decades. Metal phosphonates can be used for various applications as gas storage and separation, magnetism, and energy conversion. Especially transition metal phosphonates are promising candidates as electrocatalysts. Mechanochemistry is a versatile approach for green and fast synthesis of pure substances. By milling the reactants, various organic, inorganic, and metal-organic compounds can be obtained in high yields. Here, we present the synthesis of different new metal phosphonates obtained by grinding of metal acetates with respective phosphonic acids. By varying the ratio of the reactants, we are able to determine the composition of the final products. The addition of small amounts of liquid to the grinding process tends to increase the product’s crystallinity. The crystal structures of the new compounds were determined from powder X-ray data.
Additive manufacturing (AM) opens the route to a range of novel applications. However, the complexity of the manufacturing process poses a challenge to produce defect-free parts with a high reliability. Since process dynamics and resulting microstructures of AM parts are strongly influenced by the involved temperature fields and cooling rates, thermography is a valuable tool for process monitoring. Another approach to monitor the energy input into the part during process is the use of optical tomography.
Common visual camera systems reach much higher spatial resolution than infrared thermography cameras, whereas infrared thermography provides a much higher temperature dynamic. Therefore, the combined application increases the depth of information. Here, we present first measurement results using a laser beam melting setup that allows simultaneous acquisition of thermography and optical tomography from the same point of view using a beam splitter. A high-resolution CMOS camera operating in the visible spectral range is equipped with a near infrared bandpass filter and images of the build plate are recorded with long-term exposure during the whole layer exposing time. Thus, areas that reach higher maximum temperature or are at elevated temperature for an extended period of time appear brighter in the images. The used thermography camera is sensitive to the mid wavelength infrared range and records thermal videos of each layer exposure at an acquisition rate close to 1 kHz.
As a next step, we will use computer tomographic data of the built part as a reference for defect detection.
This research was funded by BAM within the focus area Materials.
Microbiologically influenced corrosion is a multidisciplinary research area. To develop successful mitigation strategies, expertise from the industry and research institutes are essential. In Department 4.1, we developed an innovative laboratory flow model (Hi-Tension) that allows effective monitoring of MIC under both standard and non-standard conditions. The flow model allows flexibility with material selection, flow rates, temperature and other environmental parameters changes. Furthermore, the flow model allows integration of electrochemical measurements using microsensors, providing a comprehensive view of corrosion at the biofilm level. Currently, initial results indicate corrosion in the flow model is significantly higher than that of standard laboratory set ups, i.e. static incubations, particularly for methane-producing microorganisms.