Die Bewertung von Wurstwaren auf Grund des Verh?ltnisses Leimgebende Substanz: Gesamt-Stickstoffsubstanz

Ohne ZusammenfassungMitteilung aus der Nahrungsmittel-Untersuchungsstelle an der Technischen Hochschule in Braunschweig.     

Fast, ultrasensitive virus detection using a Young interferometer sensor

We report the application of an integrated optical Young interferometer sensor for ultrasensitive, real-time, direct detection of viruses. We have validated the sensor by detecting herpes simplex virus type 1 (HSV-1), but the principle is generally applicable. Detection of HSV-1 virus particles was performed by applying the virus sample onto a sensor surface coated with a specific antibody against HSV-1. The performance of the sensor was tested by monitoring virus samples at clinically relevant concentrations. We show that the Young interferometer sensor can specifically and sensitively detect HSV-1 at very low concentrations (850 particles/mL). We have further demonstrated that the sensor can specifically detect HSV-1 suspended in serum. Extrapolation of the results indicates that the sensitivity of the sensor approaches the detection of a single virus particle binding, yielding a sensor of unprecedented sensitivity with wide applications for viral diagnostics.     

Gyroid‐Structured 3D ZnO Networks Made by Atomic Layer Deposition

3D continuous ZnO morphologies with characteristic feature sizes on the 10 nm length scale are attractive for electronic device manufacture. However, their synthesis remains a challenge because of the low crystallization temperature of ZnO. Here, we report a method for the robust and reliable synthesis of fully crystalline 3D mesoporous ZnO networks by means of atomic layer deposition (ALD) of ZnO into a self‐assembled block copolymer template. By carefully optimizing the processing conditions we are able to synthesize several‐micrometer‐thick layers of mesoporous ZnO networks with a strut width of 30 nm. Two 3D mesoporous morphologies are manufactured: a periodic gyroid structure and a random worm‐like morphology. Exploiting the ALD property to conformally coat complex surfaces of high aspect ratio, the channel network of a 3D continuous channel network of a self‐assembled block copolymer is replicated into ZnO. X‐ray photoemission spectroscopy and x‐ray diffraction measurements reveal that the chemical composition of the mesoporous structures is uniform and consists of wurtzite‐ZnO throughout the film. Scanning electron microscopy reveals an average pore dimension of 30 nm. The potential of this material for a hybrid photovoltaic application is demonstrated by the manufacture of a poly(3‐hexylthiophene)/ZnO solar cell.     

Polarization control in a vertical cavity surface emitting laser submitted to optical feedback

We study experimentally and theoretically two polarization effects in a vertical cavity surface emitting laser submitted to optical feedback. In a first experiment, we obtain flips between two linearly polarized laser modes up to a frequency of 50 MHz using an external cavity with a polarizer. In a second experiment, polarization self modulation is demonstrated up to a frequency of 2.6 GHz, using a quarter wave plate instead. Numerical calculations, based on a four levels model for the active medium, show a good agreement with the experiments.     

Microfluidics-Based Force Spectroscopy Enables High-Throughput Force Experiments with Sub-Nanometer Resolution and Sub-Piconewton Sensitivity

Several techniques have been established to quantify the mechanicals of single molecules. However, most of them show only limited capabilities of parallelizing the measurement by performing many individual measurements simultaneously. Herein, a microfluidics-based single-molecule force spectroscopy method, which achieves sub-nanometer spatial resolution and sub-piconewton sensitivity and is capable of simultaneously quantifying hundreds of single-molecule targets in parallel, is presented. It relies on a combination of total internal reflection microscopy and microfluidics, in which monodisperse fluorescent beads are immobilized on the bottom of a microfluidic channel by macromolecular linkers. Application of a flow generates a well-defined shear force acting on the beads, whereas the nanomechanical linker response is quantified based on the force-induced displacement of individual beads. To handle the high amount of data generated, a cluster analysis which is capable of a semi-automatic identification of measurement artifacts and molecular populations is implemented. The method is validated by probing the mechanical response polyethylene glycol linkers and binding strength of biotin–NeutrAvidin complexes. Two energy barriers (at 3 and 5.7 Å, respectively) in the biotin–NeutrAvidin interaction are resolved and the unfolding behavior of talin's rod domain R3 in the force range between 1 to ≈10 pN is probed.     

Visualizing the performance loss of solar cells by IR thermography — an evaluation study on CIGS with artificially induced defects

Local electric defects may result in considerable performance losses in solar cells. Infrared (IR) thermography is one important tool to detect these defects on photovoltaic modules. Qualitative interpretation of IR images has been carried out successfully, but quantitative interpretation has been hampered by the lack of “calibration” defects. The aims of this study are to (i) establish methods to induce well‐defined electric defects in thin‐film solar cells serving as “calibration” defects and to (ii) assess the accuracy of IR imaging methods by using these artificially induced defects. This approach paves the way for improving quality control methods based on imaging in photovoltaic. We created ohmic defects (“shunts”) by using a focused ion beam and weak diodes (“interface shunts”) by applying a femto‐second laser at rather low power on copper indium gallium selenide cells. The defects can be induced precisely and reproducibly, and the severity of the defects on the electrical performance can be well adjusted by focused ion beam/laser parameters. The successive assessment of the IR measurement (ILIT‐Voc) revealed that this method can predict the losses in P_mpp (maximal power extractable) with a mean error of below 10%. Copyright © 2016 John Wiley & Sons, Ltd.     

Transport properties of 1,1-difluoroethane (R152a)

Based on reliable. carefully selected data sets. equations for the thermal conductivity and the viscosity of the refrigerant R 112a are presented. They are valid at temperatures from 240 to 440 K, pressures up to 20 MPa. and densities up to 1050 kg · m^–3. including the critical region.     

Deep learning for photoacoustic tomography from sparse data

The development of fast and accurate image reconstruction algorithms is a central aspect of computed tomography. In this paper, we investigate this issue for the sparse data problem in photoacoustic tomography (PAT). We develop a direct and highly efficient reconstruction algorithm based on deep learning. In our approach, image reconstruction is performed with a deep convolutional neural network (CNN), whose weights are adjusted prior to the actual image reconstruction based on a set of training data. The proposed reconstruction approach can be interpreted as a network that uses the PAT filtered backprojection algorithm for the first layer, followed by the U-net architecture for the remaining layers. Actual image reconstruction with deep learning consists in one evaluation of the trained CNN, which does not require time-consuming solution of the forward and adjoint problems. At the same time, our numerical results demonstrate that the proposed deep learning approach reconstructs images with a quality comparable to state of the art iterative approaches for PAT from sparse data.