Liquid Mixing on Falling Films: Marker-Free, Molecule-Sensitive 3D Mapping Using Raman Imaging.

Following up on a proof of concept, this publication presents a new method for mixing mapping on falling liquid films. On falling liquid films, different surfaces, plain or structured, are common. Regarding mixing of different components, the surface has a significant effect on its capabilities and performance. The presented approach combines marker-free and molecule-sensitive measurements with cross-section mapping to emphasize the mixing capabilities of different surfaces. As an example of the mixing capabilities on falling films, the mixing of sodium sulfate with tap water is presented, followed by a comparison between a plain surface and a pillow plate. The method relies upon point-by-point Raman imaging with a custom-built high-working-distance, low-depth-of-focus probe. To compensate for the long-time measurements, the continuous plant is in its steady state, which means the local mixing state is constant, and the differences are based on the liquids' position on the falling film, not on time. Starting with two separate streams, the mixing progresses by falling down the surface. In conclusion, Raman imaging is capable of monitoring mixing without any film disturbance and provides detailed information on liquid flow in falling films.

Marker-Free, Molecule Sensitive Mapping of Disturbed Falling Fluid Films Using Raman Imaging.

Technical liquid flow films are the basic arrangement for gas fluid transitions of all kinds and are the basis of many chemical processes, such as columns, evaporators, dryers, and different other kinds of fluid/fluid separation units. This publication presents a new method for molecule sensitive, non-contact, and marker-free localized concentration mapping in vertical falling films. Using Raman spectroscopy, no label or marker is needed for the detection of the local composition in liquid mixtures. In the presented cases, the film mapping of sodium sulfate in water on a plain surface as well as an added artificial streaming disruptor with the shape of a small pyramid is scanned in three dimensions. The results show, as a prove of concept, a clear detectable spectroscopic difference between air, back plate, and sodium sulfate for every local point in all three dimensions. In conclusion, contactless Raman scanning on falling films for liquid mapping is realizable without any mechanical film interaction caused by the measuring probe. Surface gloss or optical reflections from a metallic back plate are suppressed by using only inelastic light scattering and the mathematical removal of background noise.

Rapid brain structure and tumour margin detection on whole frozen tissue sections by fast multiphotometric mid-infrared scanning.

Frozen section analysis is a frequently used method for examination of tissue samples, especially for tumour detection. In the majority of cases, the aim is to identify characteristic tissue morphologies or tumour margins. Depending on the type of tissue, a high number of misdiagnoses are associated with this process. In this work, a fast spectroscopic measurement device and workflow was developed that significantly improves the speed of whole frozen tissue section analyses and provides sufficient information to visualize tissue structures and tumour margins, dependent on their lipid and protein molecular vibrations. That optical and non-destructive method is based on selected wavenumbers in the mid-infrared (MIR) range. We present a measuring system that substantially outperforms a commercially available Fourier Transform Infrared (FT-IR) Imaging system, since it enables acquisition of reduced spectral information at a scan field of 1 cm2 in 3 s, with a spatial resolution of 20 µm. This allows fast visualization of segmented structure areas with little computational effort. For the first time, this multiphotometric MIR system is applied to biomedical tissue sections. We are referencing our novel MIR scanner on cryopreserved murine sagittal and coronal brain sections, especially focusing on the hippocampus, and show its usability for rapid identification of primary hepatocellular carcinoma (HCC) in mouse liver.