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Scanning Near-Field Optical Microscopy (SNOM) has developed during recent decades into a valuable tool to optically image the surface topology of materials with super-resolution. With aperture-based SNOM systems, the resolution scales with the size of the aperture, but also limits the sensitivity of the detection and thus the application for spectroscopic techniques like Raman SNOM. In this paper we report the extension of solid immersion lens (SIL) technology to Raman SNOM. The hemispherical SIL with a tip on the bottom acts as an apertureless dielectric nanoprobe for simultaneously acquiring topographic and spectroscopic information. The SIL is placed between the sample and the microscope objective of a confocal Raman microscope. The lateral resolution in the Raman mode is validated with a cross section of a semiconductor layer system and, at approximately 180 nm, is beyond the classical diffraction limit of Abbe.
Different types of raw cotton were investigated by a commercial ultraviolet-visible/near infrared (UV-Vis/NIR) spectrometer (210–2200 nm) as well as on a home-built setup for NIR hyperspectral imaging (NIR-HSI) in the range 1100–2200 nm. UV-Vis/NIR reflection spectroscopy reveals the dominant role proteins, hydrocarbons and hydroxyl groups play in the structure of cotton. NIR-HSI shows a similar result. Experimentally obtained data in combination with principal component analysis (PCA) provides a general differentiation of different cotton types. For UV-Vis/NIR spectroscopy, the first two principal components (PC) represent 82 % and 78 % of the total data variance for the UV-Vis and NIR regions, respectively. Whereas, for NIR-HSI, due to the large amount of data acquired, two methodologies for data processing were applied in low and high lateral resolution. In the first method, the average of the spectra from one sample was calculated and in the second method the spectra of each pixel were used. Both methods are able to explain ≥90 % of total variance by the first two PCs. The results show that it is possible to distinguish between different cotton types based on a few selected wavelength ranges. The combination of HSI and multivariate data analysis has a strong potential in industrial applications due to its short acquisition time and low-cost development. This study opens a novel possibility for a further development of this technique towards real large-scale processes.
Auf jeder Stufe der Lebensmittelkette muss von der Herstellung bis zum Inverkehrbringen eine Rückverfolgung der Produkte möglich sein. Erzeuger, Verarbeiter, Transportunternehmen und Händler stehen vor der Herausforderung, Systeme zur Rückverfolgbarkeit effizient in ihre Unternehmensprozesse zu integrieren und gegenseitig zu vernetzen. Für die betriebliche Umsetzung werden die rechtlichen Anforderungen skizziert und die Grundlagen eines Rückverfolgbarkeitssystems vorgestellt.
We report on the reflectance, transmittance and fluorescence spectra (λ=200–1200nm) of four types of chicken eggshells (white, brown, light green, dark green) measured in situ without pretreatment and after ablation of 20–100 μm of the outer shell regions. The color pigment protoporphyrin IX (PPIX) is embedded in the protein phase of all four shell types as highly fluorescent monomers, in the white and light green shells additionally as non-fluorescent dimers, and in the brown and dark green shells mainly as non-fluorescent poly-aggregates. The green shell colors are formed from an approximately equimolar mixture of PPIX and biliverdin. The axial distribution of protein and color pigments were evaluated from the combined reflectances of both the outer and inner shell surfaces, as well as from the transmittances. For the data generation we used the radiative transfer model in the random walk and Kubelka-Munk approaches.
An apparatus and method for analyzing a flow of material having an inlet region, a measurement range and an outlet region, and having a first diverter and a second diverter, and a deflection area, wherein in a first state of operation, the two diverters form a continuous first material flow space from the inlet region via the first diverter through the measurement range, via the second diverter to the outlet region, and in a second state of operation, form a continuous second material flow space from the inlet region via the first diverter through the deflection area, via the second diverter to the outlet region.
Die Erfindung betrifft eine Vorrichtung und Verfahren zur Analyse eines Materialstroms S mit einem Einlassbereich E, einem Messbereich M und einen Auslassbereich A sowie mit einer ersten Weiche W1 und einer zweiten Weiche W2 und einem Umlenkbereich U, wobei die beiden Weichen W1, W2 in einem ersten Schaltzustand Z1 einen durchgängigen ersten Materialdurchströmungsraum vom Einlassbereich E über die erste Weiche W1 durch den Messbereich M über die zweite Weiche W2 bis zum Auslassbereich A ausbilden und in einem zweiten Schaltzustand einen durchgängigen zweiten Materialdurchströmungsraum vom Einlassbereich E über die erste Weiche W1 durch den Umkenkbereich U über die zweite Weiche W2 bis zum Auslassbereich A ausbilden.
Die Erfindung betrifft eine Vorrichtung und Verfahren zur Analyse eines Materialstroms (S) mit einem Einlassbereich (E), einem Messbereich (M) und einen Auslassbereich (A) sowie mit einer ersten Weiche (W1) und einer zweiten Weiche (W2) und einem Umlenkbereich (U), wobei die beiden Weichen (W1, W2) in einem ersten Schaltzustand (Z1) einen durchgängigen ersten Materialdurchströmungsraum vom Einlassbereich (E) über die erste Weiche (W1) durch den Messbereich (M) über die zweite Weiche (W2) bis zum Auslassbereich (A) ausbilden und in einem zweiten Schaltzustand einen durchgängigen zweiten Materialdurchströmungsraum vom Einlassbereich (E) über die erste Weiche (W1) durch den Umlenkbereich (U) über die zweite Weiche (W2) bis zum Auslassbereich (A) ausbilden.
Characterization of brain tumours requires neuropathological expertise and is generally performed by histological evaluation and molecular analysis. One emerging technique to assist pathologists in future tumour diagnostics is multimodal optical spectroscopy. In the current clinical routine, tissue preprocessing with formalin is widely established and suitable for spectroscopic investigations since degradation processes impede the measurement of native tissue. However, formalin fixation results in alterations of the tissue chemistry and morphology for example by protein cross-linking. As optical spectroscopy is sensitive to these variations, we evaluate the effects of formalin fixation on multimodal brain tumour data in this proof-of-concept study. Nonfixed and formalin-fixed cross sections of different common human brain tumours were subjected to analysis of chemical variations using ultraviolet and Fourier-transform infrared microspectroscopy. Morphological changes were assessed by elastic light scattering microspectroscopy in the visible wavelength range. Data were analysed with multivariate data analysis and compared with histopathology. Tissue type classifications deduced by optical spectroscopy are highly comparable and independent from the preparation and the fixation protocol. However, formalin fixation leads to slightly better classification models due to improved stability of the tissue. As a consequence, spectroscopic methods represent an appropriate additional contrast for chemical and morphological information in neuropathological diagnosis and should be investigated to a greater extent. Furthermore, they can be included in the clinical workflow even after formalin fixation.
The critical process parameters cell density and viability during mammalian cell cultivation are assessed by UV/VIS spectroscopy in combination with multivariate data analytical methods. This direct optical detection technique uses a commercial optical probe to acquire spectra in a label-free way without signal enhancement. For the cultivation, an inverse cultivation protocol is applied, which simulates the exponential growth phase by exponentially replacing cells and metabolites of a growing Chinese hamster ovary cell batch with fresh medium. For the simulation of the death phase, a batch of growing cells is progressively replaced by a batch with completely starved cells. Thus, the most important parts of an industrial batch cultivation are easily imitated. The cell viability was determined by the well-established method partial least squares regression (PLS). To further improve process knowledge, the viability has been determined from the spectra based on a multivariate curve resolution (MCR) model. With this approach, the progress of the cultivations can be continuously monitored solely based on an UV/VIS sensor. Thus, the monitoring of critical process parameters is possible inline within a mammalian cell cultivation process, especially the viable cell density. In addition, the beginning of cell death can be detected by this method which allows us to determine the cell viability with acceptable error. The combination of inline UV/VIS spectroscopy with multivariate curve resolution generates additional process knowledge complementary to PLS and is considered a suitable process analytical tool for monitoring industrial cultivation processes.
The article analyzes experimentally and theoretically the influence of microscope parameters on the pinhole-assisted Raman depth profiles in uniform and composite refractive media. The main objective is the reliable mapping of deep sample regions. The easiest to interpret results are found with low magnification, low aperture, and small pinholes. Here, the intensities and shapes of the Raman signals are independent of the location of the emitter relative to the sample surface. Theoretically, the results can be well described with a simple analytical equation containing the axial depth resolution of the microscope and the position of the emitter. The lower determinable object size is limited to 2–4 μm. If sub-micrometer resolution is desired, high magnification, mostly combined with high aperture, becomes necessary. The signal intensities and shapes depend now in refractive media on the position relative to the sample surface. This aspect is investigated on a number of uniform and stacked polymer layers, 2–160 μm thick, with the best available transparency. The experimental depth profiles are numerically fitted with excellent accuracy by inserting a Gaussian excitation beam of variable waist and fill fraction through the focusing lens area, and by treating the Raman emission with geometric optics as spontaneous isotropic process through the lens and the variable pinhole, respectively. The intersectional area of these two solid angles yields the leading factor in understanding confocal (pinhole-assisted) Raman depth profiles.