Detailed characterisation of batch-manufactured flexible micro-grinding tools for electrochemical assisted grinding of copper surfaces

Precision machining is becoming more and more important with the increasing demands on surface quality for various components. This applies, for example, to mirror components in micro-optics or cooling components in microelectronics. Copper is a frequently used material for this purpose, but its mechanical properties make it difficult to machine. In this study, a process strategy for finishing copper surfaces with batch-manufactured micro-grinding tools in an electrochemically assisted grinding process is demonstrated. The tool heads are manufactured from a polyimide-abrasive-suspension and silicon as a carrier substrate using microsystems technology. The matching shafts are milled from aluminium. The tools are then used on pure copper and oxidised copper surfaces. By using finer abrasives grains (1.6–2.4 µm instead of 4–6 µm) than previously, similar surface roughness values could be achieved (Ra = 0.09 ± 0.02 µm, Rz = 1.94 ± 0.73 µm) with the same grinding process. An optimised grinding process that combines the use of rough and fine tools, on the other hand, achieves significantly better surface finishes in just four grinding iterations (Ra = 0.02 ± 0.01 µm, Rz = 0.83 ± 0.21 µm). In order to achieve a further increase in surface quality, this optimised grinding process is combined with the anodic oxidation of the copper workpieces. The surface modification is done to increase the machinability of the surface by creating an oxide layer. This is confirmed by the results of scratch tests carried out, which showed less force acting on the tool during machining with the oxide layer than with a pure copper surface. To realise this within the machine tool, an electrochemical cell is shown that can be integrated into the machine so that the oxidation can be carried out immediately before the grinding process. The copper layers produced inside the electrochemical cell in the machine tool show similar characteristics to the samples produced outside. Processing the oxidised samples with the optimised grinding process led to a further reduction of about 17% in the Rz values (Ra = 0.03 ± 0.01 µm, Rz = 0.69 ± 0.20 µm). The combination of the shown grinding process and the integration of anodic oxidation within the machine tool for the surface modification of copper workpieces seems to be promising to achieve high surface finishes

A new strategy based on real-time secondary electrospray ionization and high-resolution mass spectrometry to discriminate endogenous and exogenous compounds in exhaled breath

Breath is considered to be an easily accessible matrix, whose chemical composition relates to compounds present in blood. Therefore many metabolites are expected in exhaled breath, which may be used in the future for the development of diagnostic methods. In this article, a new strategy to discriminate between exhaled endogenous metabolites and exhaled exogenous contaminants by direct high-resolution mass spectrometry is introduced. The analysis of breath in real-time by secondary electrospray ionization mass spectrometry allows to interpret the origin of exhaled compounds. Exhaled metabolites that originate in the respiratory system show reproducible and significant patterns if plotted in real-time (>1 data point per second). An exhaled metabolite shows a signal that tends to rise at the end of a complete (forced) exhalation. In contrast, exogenous compounds, which may be present in room air, are gradually diluted by the air from the deeper lung and therefore show a trend of falling intensity. Signals found in breath by using this pattern recognition are linked to potential metabolites by comparison with online databases. In addition to this real-time approach, it is also shown how to combine this method with classical analytical methods in order to potentially identify unknown metabolites. Finally exhaled compounds following smoking a cigarette, chewing gum, or drinking coffee were investigated to underline the usefulness of this new approach

Process Development for Batch Production of Micro-Milling Tools Made of Silicon Carbide by Means of the Dry Etching Process

Downsized and complex micro-machining structures have to meet quality requirements concerning geometry and convince through increasing functionality. The development and use of cutting tools in the sub-millimeter range can meet these demands and contribute to the production of intelligent components in biomedical technology, optics or electronics. This article addresses the development of double-edged micro-cutters, which consist of a two-part system of cutter head and shaft. The cutting diameters are between 50 and 200 μm. The silicon carbide cutting heads are manufactured from the solid material using microsystem technology. The substrate used can be structured uniformly via photolithography, which means that 5200 homogeneous micro-milling heads can be produced simultaneously. This novel batch approach represents a contrast to conventionally manufactured micro-milling cutters. The imprint is taken by means of reactive ion etching using a mask made of electroplated nickel. Within this dry etching process, characteristic values such as the etch rate and flank angle of the structures are critical and will be compared in a parameter analysis. At optimal parameters, an anisotropy factor of 0.8 and an etching rate of 0.34 µm/min of the silicon carbide are generated. Finally, the milling heads are diced and joined. In the final machining tests, the functionality is investigated and any signs of wear are evaluated. A tool life of 1500 mm in various materials could be achieved. This and the milling quality achieved are in the range of conventional micro-milling cutters, which gives a positive outlook for further development

Follow-up investigations of tau protein and S-100B levels in cerebrospinal fluid of patients with Creutzfeldt-Jakob disease

Background: S-100B and tau protein have a high differential diagnostic potential for the diagnosis of Creutzfeldt-Jakob disease (CJD). So far there has been only limited information available about the dynamics of these parameters in the cerebrospinal fluid (CSF). However, there is a special interest in finding biochemical markers to monitor disease progression for differential diagnosis and treatment. Patients and Methods: We analyzed CSF of 45 patients with CJD and of 45 patients with other neurological diseases for tau protein and S-100B in a follow-up setting. All diagnoses of CJD were later neuropathologically verified. A ratio between tau protein differences and the time between lumbar puncture was calculated. The same was done for S-100B. Results: Tau protein levels of 34 cases were above the cut-off level for CJD (>1,300 pg/ml) in the first CSF sample. In 7 of 11 patients with lower tau levels in the first CSF sample, tau levels rose. The above-mentioned ratio was significantly higher in the CJD group than in the group with other neurological diseases. Similar results were obtained for S-100B. Conclusion: We conclude that follow-up investigations and calculation of ratios is a useful tool in the differential diagnosis of CJD. Variations in this pattern were observed in single cases. Copyright (C) 2005 S. Karger AG, Basel

Proteomic analysis of the cerebrospinal fluid of patients with Creutzfeldt-Jakob disease

So far, only the detection of 14-3-3 proteins in cerebrospinal fluid (CSF) has been accepted as diagnostic criterion for Creutzfeldt-Jakob disease (CJD). However, this assay cannot be used for screening because of the high rate of false-positive results, whereas patients with variant CJD are often negative for 14-3-3 proteins. The aim of this study was to compare the spot patterns of CSF by 2-dimensional polyacrylamide gel electrophoresis (2D-PAGE) to search for a CJD-specific spot pattern. We analyzed the CSF of 28 patients {[}11 CJD, 9 Alzheimer's disease ( AD), 8 nondemented controls (NDC)] employing 2D-PAGE which was optimized for minimal volumes of CSF (0.1 ml; 7-cm strips). All samples were run at least three times, gels were silver stained and analyzed by an analysis software and manually revised. We could consistently match 268 spots which were then compared between all groups. By the use of 5 spots, we were able to differentiate CJD from AD or NDC with a sensitivity of 100%. CJD could also be distinguished from both groups by using a heuristic clustering algorithm of 2 spots. We conclude that this proteomic approach can differentiate CJD from other diseases and may serve as a model for other neurodegenerative diseases. Copyright (C) 2007 S. Karger AG, Basel

Controlling the radiation dynamics of MoSe2/WSe2 interlayer excitons via in-situ tuning the electromagnetic environment

We show that the spontaneous emission rate of the interlayer excitons in a twisted WSe2-MoSe2 heterobilayer can be precisely tailored in a low-temperature open optical microcavity via the Purcell effect. We engineer the local density of optical states in our resonator structures in two complementary experimental settings. In the first approach, we utilize an ultra-low quality factor planar vertical cavity structure, which develops multiple longitudinal modes that can be consecutively brought to resonance with the broad interlayer exciton spectrum of our heterostructure. Time-resolved photoluminescence measurements reveal that the interlayer exciton lifetime can thus be periodically tuned with an amplitude of around 100 ps. The resulting oscillations of the exciton lifetime allows us to extract a free-space radiative exciton lifetime of 2.2 ns and an approximately 15 % quantum efficiency of the interlayer excitons. We subsequently engineered the local density of optical states by introducing a spatially confined and fully spectrally tunable Tamm-plasmon resonance. The dramatic redistribution of the local optical modes in this setting allows us to encounter a profound inhibition of spontaneous emission of the interlayer excitons by a factor of 3.3. Our results will further boost the cavity-mediated collective emission phenomena such as super-radiance. We expect that specifically engineering the inhibition of radiation from moire excitons is a powerful tool to steer their thermalization, and eventually their condensation into coherent condensate phases.Comment: 16 pages, 3 figures, DFG SPP2244 fundings, et

Engineering the impact of phonon dephasing on the coherence of a WSe2_{2} single-photon source via cavity quantum electrodynamics

Emitter dephasing is one of the key issues in the performance of solid-state single photon sources. Among the various sources of dephasing, acoustic phonons play a central role in adding decoherence to the single photon emission. Here, we demonstrate, that it is possible to tune and engineer the coherence of photons emitted from a single WSe$_2$ monolayer quantum dot via selectively coupling it to a spectral cavity resonance. We utilize an open cavity to demonstrate spectral enhancement, leveling and suppression of the highly asymmetric phonon sideband, finding excellent agreement with our microscopic theory. Most importantly, the impact of cavity tuning on the dephasing is directly assessed via optical interferometry, which clearly points out the capability to utilize light-matter coupling to steer and design dephasing and coherence of the emission properties of atomically thin crystals

GWAS meta-analysis of over 29,000 people with epilepsy identifies 26 risk loci and subtype-specific genetic architecture

Epilepsy is a highly heritable disorder affecting over 50 million people worldwide, of which about one-third are resistant to current treatments. Here we report a multi-ancestry genome-wide association study including 29,944 cases, stratified into three broad categories and seven subtypes of epilepsy, and 52,538 controls. We identify 26 genome-wide significant loci, 19 of which are specific to genetic generalized epilepsy (GGE). We implicate 29 likely causal genes underlying these 26 loci. SNP-based heritability analyses show that common variants explain between 39.6% and 90% of genetic risk for GGE and its subtypes. Subtype analysis revealed markedly different genetic architectures between focal and generalized epilepsies. Gene-set analyses of GGE signals implicate synaptic processes in both excitatory and inhibitory neurons in the brain. Prioritized candidate genes overlap with monogenic epilepsy genes and with targets of current antiseizure medications. Finally, we leverage our results to identify alternate drugs with predicted efficacy if repurposed for epilepsy treatment

A new strategy based on real-time secondary electrospray ionization and high-resolution mass spectrometry to discriminate endogenous and exogenous compounds in exhaled breath

Breath is considered to be an easily accessible matrix, whose chemical composition relates to compounds present in blood. Therefore many metabolites are expected in exhaled breath, which may be used in the future for the development of diagnostic methods. In this article, a new strategy to discriminate between exhaled endogenous metabolites and exhaled exogenous contaminants by direct high-resolution mass spectrometry is introduced. The analysis of breath in real-time by secondary electrospray ionization mass spectrometry allows to interpret the origin of exhaled compounds. Exhaled metabolites that originate in the respiratory system show reproducible and significant patterns if plotted in real-time (>1 data point per second). An exhaled metabolite shows a signal that tends to rise at the end of a complete (forced) exhalation. In contrast, exogenous compounds, which may be present in room air, are gradually diluted by the air from the deeper lung and therefore show a trend of falling intensity. Signals found in breath by using this pattern recognition are linked to potential metabolites by comparison with online databases. In addition to this real-time approach, it is also shown how to combine this method with classical analytical methods in order to potentially identify unknown metabolites. Finally exhaled compounds following smoking a cigarette, chewing gum, or drinking coffee were investigated to underline the usefulness of this new approach.ISSN:1573-3882ISSN:1573-389

Predicting Flow Stress Behavior of an AA7075 Alloy Using Machine Learning Methods

The present work focuses on the prediction of the hot deformation behavior of thermo-mechanically processed precipitation hardenable aluminum alloy AA7075. The data considered focus on a novel hot forming process at different tool temperatures ranging from 24∘C to 350∘C to set different cooling rates after solution heat-treatment. Isothermal uniaxial tensile tests in the temperature range of 200∘C to 400∘C and at strain rates ranging from 0.001 s−1 to 0.1 s−1 were carried out on four different material conditions. The present paper mainly focuses on a comparative study of modeling techniques based on Machine Learning (ML) and the Zerilli–Armstrong model (Z–A) as reference. Related work focuses on predicting single data points of the curves that the model was trained on. Due to the way data were split with respect to training and testing data, it is possible to predict entire stress–strain curves. The model allows to decrease the number of required laboratory experiments, eventually saving costs and time in future experiments. While all investigated ML methods showed a higher performance than the Z–A model, the extreme Gradient Boosting model (XGB) showed superior results, i.e., the highest error reduction of 91% with respect to the Mean Squared Error