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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.
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.
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.
Hyperspectral imaging and reflectance spectroscopy in the range from 200–380 nm were used to rapidly detect and characterize copper oxidation states and their layer thicknesses on direct bonded copper in a non-destructive way. Single-point UV reflectance spectroscopy, as a well-established method, was utilized to compare the quality of the hyperspectral imaging results. For the laterally resolved measurements of the copper surfaces an UV hyperspectral imaging setup based on a pushbroom imager was used. Six different types of direct bonded copper were studied. Each type had a different oxide layer thickness and was analyzed by depth profiling using X-ray photoelectron spectroscopy. In total, 28 samples were measured to develop multivariate models to characterize and predict the oxide layer thicknesses. The principal component analysis models (PCA) enabled a general differentiation between the sample types on the first two PCs with 100.0% and 96% explained variance for UV spectroscopy and hyperspectral imaging, respectively. Partial least squares regression (PLS-R) models showed reliable performance with R2c = 0.94 and 0.94 and RMSEC = 1.64 nm and 1.76 nm, respectively. The developed in-line prototype system combined with multivariate data modeling shows high potential for further development of this technique towards real large-scale processes.
Commercially available homogenized cow- and plant-based milks were investigated by optical spectroscopy in the range of 400–1360 nm. Absorbance spectra, the effective scattering coefficient μs′, and the spectral absorption coefficient μa were recorded for 23 milk varieties and analyzed by multivariate data analysis. Cow- and plant-based milks were compared and discriminated using principal component analysis combined with a quadratic discriminant analysis. Furthermore, it was possible to discriminate the origin of plant-based milk by μa and the fat content in cow-based milk by μs′. Partial least squares regression models were developed to determine the fat content in cow-based milk. The model for μs′ proved to be the most efficient for this task with R2 = 0.98 and RMSEP = 0.19 g/100 mL for the external validation. Thus, optical spectroscopy together with multivariate data analysis is suitable for routine laboratory analysis or quality monitoring in the dairy production.
Current techniques for chromosome analysis need to be improved for rapid, economical identification of complex chromosomal defects by sensitive and selective visualisation. In this paper, we present a straightforward method for characterising unstained human metaphase chromosomes. Backscatter imaging in a dark-field setup combined with visible and short near-infrared spectroscopy is used to monitor morphological differences in the distribution of the chromosomal fine structure in human metaphase chromosomes. The reasons for the scattering centres in the fine structure are explained. Changes in the scattering centres during preparation of the metaphases are discussed. FDTD simulations are presented to substantiate the experimental findings. We show that local scattering features consisting of underlying spectral modulations of higher frequencies associated with a high variety of densely packed chromatin can be represented by their scatter profiles even on a sub-microscopic level. The result is independent of the chromosome preparation and structure size. This analytical method constitutes a rapid, costeffective and label-free cytogenetic technique which can be used in a standard light microscope.
Newly developed active pharmaceutical ingredients (APIs) are often poorly soluble in water. As a result the bioavailability of the API in the human body is reduced. One approach to overcome this restriction is the formulation of amorphous solid dispersions (ASDs), e.g., by hot-melt extrusion (HME). Thus, the poorly soluble crystalline form of the API is transferred into a more soluble amorphous form. To reach this aim in HME, the APIs are embedded in a polymer matrix. The resulting amorphous solid dispersions may contain small amounts of residual crystallinity and have the tendency to recrystallize. For the controlled release of the API in the final drug product the amount of crystallinity has to be known. This review assesses the available analytical methods that have been recently used for the characterization of ASDs
and the quantification of crystalline API content. Well established techniques like near- and mid-infrared spectroscopy (NIR and MIR, respectively), Raman spectroscopy, and emerging ones like UV/VIS, terahertz, and ultrasonic spectroscopy are considered in detail. Furthermore, their advantages and limitations are discussed with regard to general practical applicability as process analytical technology (PAT) tools in industrial manufacturing. The review focuses on spectroscopic methods which have been proven as most suitable for in-line and on-line process analytics. Further aspects are spectroscopic techniques that have been or could be integrated into an extruder.
Different sensor types using chemical and biochemical principles are described. The former are mainly gas sensors, the latter are applied especially to liquids. Those label-free direct detection methods are compared with applications where assays take advantage of labeled receptors.
Furthermore, selected applications in the area of gas sensors are discussed, and sensors for process control, point-of-care diagnostics, environmental analytics, and food analytics are reviewed. In addition, multiplexing approaches used in microplates and microarrays are described.
On account of the huge number of sensor types and the wide range of possible applications, only the most important ones are selected here.
This paper presents an approach for label-free brain tumor tissue typing. For this application, our dual modality microspectroscopy system combines inelastic Raman scattering spectroscopy and Mie elastic light scattering spectroscopy. The system enables marker-free biomedical diagnostics and records both the chemical and morphologic changes of tissues on a cellular and subcellular level. The system setup is described and the suitability for measuring morphologic features is investigated.