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Tracking coffee roasting at an industrial scale for quality control is challenging. Bean color is a practical gauge for monitoring and regulating the process but only occurs before and after the process. This study highlights the feasibility of monitoring the process throughout using Raman spectroscopy. Strecker degradation and the Maillard reaction contribute to various aromatic compounds that can serve as markers in quality monitoring. Among these are chlorogenic acids (CGAs), recognized as pivotal factors determining the desired aroma. Here, drum and fluidized bed roaster processes were monitored, capitalizing on the chemical alterations induced by high temperatures (140–200 °C), particularly through the Maillard reaction. These chemical changes manifest in the scattered light signal. For real-time monitoring, Raman spectra were taken every 10 ms in selected ranges, with an average calculated every second. Utilizing a calibration matrix from a High-Pressure Liquid Chromatography (HPLC) method, CGA concentration becomes the control variable for assessing roasting progress. This study reveals the potential of Raman spectroscopy for tracking CGA during roasting. It establishes a correlation between inelastic scattered light and CGA validated through laboratory measurements and fixed roasting conditions, resulting in a theoretical CGA concentration that can be used as a process termination criterion.

In this paper, a dispersion of glass beads of different sizes in an ammonium nitrate solution is investigated with the aid of Raman spectroscopy. The signal losses caused by the dispersion are quantified by an additional scattered light measurement and used to correct the measured ammonium nitrate concentration. Each individual glass bead represents an interface at which the excitation laser is deflected from its direction causing distortion in the received Raman signal. It is shown that the scattering losses measured with the scattered light probe correlate with the loss of the Raman signal, which means that the data obtained can be used to correct the measured values. The resulting correction function considers different particle sizes in the range of 2–99 µm as well as ammonium nitrate concentrations of 0–20 wt% and delivers an RMSEP of 1.952 wt%. This correction provides easier process access to dispersions that were previously difficult or impossible to measure.

With the goal to better process the monitoring of occurring fouling, a backscatter probe was developed to perform in-line measurements in a half-shell reactor during the reaction of N-vinylpyrrolidone (NVP) to polyvinylpyrrolidone (PVP). The measurement technique detects the changes of bands in the UV range, which allows a direct correlation with the concentration. Thus, the measured absorbance signal allows a conclusion on the accumulation of fouling in the reactor and on changes in the conversion at the measurement location.

In the present study, the influence of disperse systems on Raman scattering was investigated. How an increasing particle concentration weakens the quantitative signal of the Raman spectrum is shown. Furthermore, the change in the position of the optimal measurement point in the fluid was considered in detail. Additional transmission measurements can be used to derive a simple and robust correction method that allows the actual concentration of the continuous phase to be determined with a standard deviation of 2.6%.

Abstract 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.

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.

Due to their nested structure, double emulsions have the potential to encapsulate value-adding substances until their application, making them of interest to various industries. However, the complex, nested structure negatively affects the stability of double emulsions. Still, there is a lack of suitable measurement technology to fundamentally understand the cause of the instability mechanisms taking place. This study presents a novel measurement method to continuously track filling degree changes due to water diffusion in a water-in-oil-in-water (W1/O/W2) double emulsion droplet. The measurement method is based on the Raman effect and provides both photometric and spectrometric data. No sample preparation is required, and the measurement does not affect the double emulsion droplet.

One of the main topics within research activities is the management of research data. Large amounts of data acquired by heterogeneous scientific devices, sensor systems, measuring equipment, and experimental setups have to be processed and ideally be managed by Findable, Accessible, Interoperable, and Reusable (FAIR) data management approaches in order to preserve their intrinsic value to researchers throughout the entire data lifecycle. The symbiosis of heterogeneous measuring devices, FAIR principles, and digital twin technologies is considered to be ideally suited to realize the foundation of reliable, sustainable, and open research data management. This paper contributes a novel architectural approach for gathering and managing research data aligned with the FAIR principles. A reference implementation as well as a subsequent proof of concept is given, leveraging the utilization of digital twins to overcome common data management issues at equipment-intense research institutes. To facilitate implementation, a top-level knowledge graph has been developed to convey metadata from research devices along with the produced data. In addition, a reactive digital twin implementation of a specific measurement device was devised to facilitate reconfigurability and minimized design effort.

Falling film evaporation processes involve high fluid velocities with continuous variations in local film thickness, fluid composition, and viscosity. This contribution presents a parallel and complementary film thickness and concentration mapping distribution in falling films using a non-invasive fluorescence and near-infrared imaging technique. The experiments were performed with a mixture of glycerol/water with a mass fraction from 0 to 0.65 gglycgtotal−1 and operating ranges similar to evaporation processes. The measurement system was designed by integrating two optical measurement methods for experimental image analysis. The film thickness was evaluated using a VIS camera and high-power LEDs at 470 nm. The local glycerol concentration gglycgtotal−1 was determined using a NIR camera and high-power LEDs at 1050, 1300, 1450 and 1550 nm. A multiwavelength analysis with all NIR wavelengths was implemented with a better correlation for falling films at low flow velocity. The results show an improvement in the analysis of falling films with high flow velocities up to almost 500 mm/s by using only the 1450 nm wavelength and the fluorescence measurement. Simultaneous imaging analysis of film thickness and concentration in falling films provides further insight into understanding mass and heat transport and thus supports the optimization of falling film evaporators.

Double emulsions arouse great interest in various industries due to their ability to encapsulate value-adding ingredients. However, they tend to be unstable due to their complex structure. Several measurement techniques have already been developed to study and monitor the stability of double emulsions. Especially for the measurement of the filling degree of double emulsions, so far there is no reliable method available. In this paper, a measurement system is presented that can measure the filling degree of water-in-oil-in-water (W/O/W) double emulsions by both spectrometrical and photometrical means. The method is based on the Raman effect and does not require any sample preparation, and the measurement has no negative influence on the double emulsion. It is shown that both spectrometric and photometric Raman techniques can reliably distinguish between double emulsions with filling degrees that have a 0.5% difference. Additionally, oil droplet sizes can be photometrically measured. Furthermore, the measurement system can be integrated into both inline and online emulsification processes.

Double emulsions show great potential for encapsulating active substances and protecting them against external influences. However, they tend to become unstable during storage. Research on double emulsions, therefore, focuses on maintaining their microstructure during their shelf life. Optical measurement methods, such as Raman spectroscopy, have hardly been used to date to analyze the microstructure of double emulsions, mainly due to multiple scattering effects. This study investigates the influence of refractive index matching of double emulsion phases by measuring the Raman signal strength of the inner water phase for different refractive index combinations. Ammonium nitrate and glycerol are added to the inner and outer water phase, respectively, to change the refractive indices of both phases. Additionally, polyvinyl alcohol serves as an emulsifier in the outer water phase. The oil phase consists of silicone oil and Dowsil Resin XR 0497 as the emulsifier. The refractive index of the oil phase is kept constant. For individual phase boundaries of single droplets, the refractive index matching plays a minor role. However, if there are many droplets with correspondingly numerous phase boundaries, which leads to multiple scattering during the measurement, the matching has a significant influence on the signal strength of the inner phase. When measuring double emulsions, the phases should always be matched, as this results in higher signals and improves the sensitivity of the measurement.

Quality control and reaction monitoring are necessary to ensure the consistency of any kind of mixing or reaction process. In this context, a novel portable high-sensitivity sensor prototype based on the Raman effect is presented in this study. The elongated probe head is designed for (but not limited to) monitoring high temperature batch processes for quality assurance. Thanks to the highly sensitive special detectors, concentration differences of up to 50 mmol/L can currently be detected, which facilitates compliance with high product quality standards. In addition, seamless reaction tracking is possible. Small individual adjustments through simple, intuitive mechanical components provide a high degree of flexibility in reaction selection by the end user. Specially developed software automates the evaluation process and gives the user visual signals about the current status and progress of the batch as well as an emergency stop if temperature limits could damage individual components. By using all the individual components developed, the problem of the limited integration times of previous spectrometric measuring instruments could be reduced. The prototype was validated using concentration measurements of various substances that occur as standard in batch processes. In addition, this article provides an outlook on the fact that Raman measurements can also be carried out successfully and reliably in explosive environments in the future with the prototype presented.

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.

The work presents an efficient and non-invasive method to visualize the local concentration and viscosity distribution of two miscible and non-reacting substances with a significant viscosity difference in a microchannel with a Y-shape cell. The proof-of-concept setup consists of a near-infrared (NIR) camera and cost-effective dome lighting with NIR light-emitting diodes (LED) covering the wavelength range of 1050 to 1650 nm. Absorption differences of glycerol and water and their mixtures with a mass fraction of glycerol from 0 to 0.95 gGlycgtotal−1 were analyzed in the NIR spectral area. The resulting measurement images were converted in a concentration profile by using absorbance calculated with Lambert–Beer law. A linear behavior between the concentration and the absorption coefficient is demonstrated. The result of local concentration in mass fraction was used to determine the local viscosity and illustrated as distribution images. By variating the fluid parameters, the influences of the highly different original viscosities in the mixing procedure were investigated and visualized.

In this study, we present an efficient and innovative method to visualize absorption differences in the mid-infrared range with spatial resolution using laser technology. We focus on only two lasers with wavelengths between 3.4 μm and 3.6 μm and a spatial resolution of 20 μm and thus achieve a scanning speed up to 300 kS/s for fast image generation. In this article, we focus especially on the detection of C–H bands in this region of the absorption spectrum. Concealed structures are examined by calculating the measured structures with both wavelengths. In our results, we demonstrate exemplary measurements on 130-μm-thick polyvinyl chloride layers. In turn, these structures are suitable for further processing in rapid quantitative quality control.

Multimodal imaging gains increasing popularity for biomedical applications. This article presents the design of a novel multimodal imaging system. The centerpiece is a light microscope operating in the incident and transmitted light mode. Additionally, Raman spectroscopy and VIS/NIR reflectance spectroscopy are adapted. The proof-of-concept is realized to distinguish between grey matter (GM) and white matter (WM) of normal mouse brain tissue. Besides Raman and VIS/NIR spectroscopy, the following optical microscopy techniques are applied in the incident light mode: brightfield, darkfield, and polarization microscopy. To complement the study, brightfield images of a hematoxylin and eosin (H&E) stained cryosection in the transmitted light mode are recorded using the same imaging system. Data acquisition based on polarization microscopy and Raman spectroscopy gives the best results regarding the tissue differentiation of the unstained section. In addition to the discrimination of GM and WM, both modalities are suited to highlight differences in the density of myelinated axons. For Raman spectroscopy, this is achieved by calculating the sum of two intensity peak ratios (I2857 + I2888)/I2930 in the high-wavenumber region. For an optimum combination of the modalities, it is recommended to apply the molecule-specific but time-consuming Raman spectroscopy to smaller regions of interest, which have previously been identified by the microscopic modes.

To meet the demands of the chemical and pharmaceutical process industry for a combination of high measurement accuracy, product selectivity, and low cost of ownership, the existing measurement and evaluation methods have to be further developed. This paper demonstrates the attempt to combine future Raman photometers with promising evaluation methods. As part of the investigations presented here, a new and easy-to-use evaluation method based on a self-learning algorithm is presented. This method can be applied to various measurement methods and is carried out here using an example of a Raman spectrometer system and an alcohol-water mixture as demonstration fluid. The spectra’s chosen bands can be later transformed to low priced and even more robust Raman photometers. The evaluation method gives more precise results than the evaluation through classical methods like one primarily used in the software package Unscrambler. This technique increases the accuracy of detection and proves the concept of Raman process monitoring for determining concentrations. In the example of alcohol/water, the computation time is less, and it can be applied to continuous column monitoring.

This work presents a novel method for the non-invasive, in-line monitoring of mixing processes in microchannels using the Raman photometric technique. The measuring set-up distinguishes itself from other works in this field by utilizing recent state-of-the-art customized photon multiplier (CPM) detectors, bypassing the use of a spectrometer. This addresses the limiting factor of integration times by achieving measuring rates of 10 ms. The method was validated using the ternary system of toluene–water–acetone. The optical measuring system consists of two functional units: the coaxial Raman probe optimized for excitation at a laser wavelength of 532 nm and the photometric detector centered around the CPMs. The spot size of the focused laser is a defining factor of the spatial resolution of the set-up. The depth of focus is measured at approx. 85 µm with a spot size of approx. 45 µm, while still maintaining a relatively high numerical aperture of 0.42, the latter of which is also critical for coaxial detection of inelastically scattered photons. The working distance in this set-up is 20 mm. The microchannel is a T-junction mixer with a square cross section of 500 by 500 µm, a hydraulic diameter of 500 µm and 70 mm channel length. The extraction of acetone from toluene into water is tracked at an initial concentration of 25% as a function of flow rate and accordingly residence time. The investigated flow rates ranged from 0.1 mL/min to 0.006 mL/min. The residence times from the T-junction to the measuring point varies from 1.5 to 25 s. At 0.006 mL/min a constant acetone concentration of approx. 12.6% was measured, indicating that the mixing process reached the equilibrium of the system at approx. 12.5%. For prototype benchmarking, comparative measurements were carried out with a commercially available Raman spectrometer (RXN1, Kaiser Optical Systems, Ann Arbor, MI, USA). Count rates of the spectrophotometer surpassed those of the spectrometer by at least one order of magnitude at identical target concentrations and optical power output. The experimental data demonstrate the suitability and potential of the new measuring system to detect locally and time-resolved concentration profiles in moving fluids while avoiding external influence.

The industrial particle sensor market lacks simple, easy to use, low cost yet robust, safe and fast response solutions. Towards development of such a sensor, for in-line use in micro channels under continuous flow conditions, this work introduces static light scattering (SLS) determination of particle diameter using a laser with an emission power of less than 5 µW together with sensitive detectors with detection times of 1 ms. The measurements for the feasibility studies are made in an angular range between 20° and 160° in 2° increments. We focus on the range between 300 and 1000 nm, for applications in the production of paints, colors, pigments and crystallites. Due to the fast response time, reaction characteristics in microchannel designs for precipitation and crystallization processes can be studied. A novel method for particle diameter characterization is developed using the positions of maxima and minima and slope distribution. The novel algorithm to classify particle diameter is especially developed to be independent of dispersed phase concentration or concentration fluctuations like product flares or signal instability. Measurement signals are post processed and particle diameters are validated against Mie light scattering simulations. The design of a low cost instrument for industrial use is proposed.

This paper provides an overview of how molecule-sensitive, spatially-resolved technologies can be applied for monitoring and measuring in microchannels. The principles of elastic light scattering, fluorescence, near-infrared, mid-infrared, and Raman imaging, as well as combination techniques, are briefly presented, and their advantages and disadvantages are explained. With optical methods, images can be acquired both scanning and simultaneously as a complete image. Scanning technologies require more acquisition time, and fast moving processes are not easily observable. On the other hand, molecular selectivity is very high, especially in Raman and mid-infrared (MIR) scanning. For near-infrared (NIR) images, the entire measuring range can be simultaneously recorded with indium gallium arsenide (InGaAs) cameras. However, in this wavelength range, water is the dominant molecule, so it is sometimes necessary to use complex learning algorithms that increase the preparation effort before the actual measurement. These technologies excite molecular vibrations in a variety of ways, making these methods suitable for specific products. Besides measurements of the fluid composition, technologies for particle detection are of additional importance. With scattered light techniques and evaluation according to the Mie theory, particles in the range of 0.2–1 µm can be detected, and fast growth processes can be observed. Local multispectral measurements can also be carried out with fiber optic-coupled systems through small probe heads of approximately 1 mm diameter.

To date, few optical imaging systems are available in clinical practice to perform noninvasive measurements transcutaneously. Instead, functional imaging is performed using ionizing radiation or intense magnetic fields in most cases. The applicability of fluorescence imaging (e.g., for the detection of fluorescently labeled objects, such as tumors) is limited due to the restricted tissue penetration of light and the required long exposure time. Thus, the development of highly sensitive and easily manageable instruments is necessary to broaden the utility of optical imaging. To advance these developments, an improved fluorescence imaging system was designed in this study that operates on the principle of noncontact laser-induced fluorescence and enables the detection of fluorescence from deeper tissue layers as well as real-time imaging. The high performance of the developed optical laser scanner results from the combination of specific point illumination, an intensified charge-coupled device (ICCD) detector with a novel light trap, and a filtering strategy. The suitability of the laser scanner was demonstrated in two representative applications and an in vivo evaluation. In addition, a comparison with a planar imaging system was performed. The results show that the exposure time with the developed laser scanner can be reduced to a few milliseconds during measurements with a penetration depth of up to 32 mm. Due to these short exposure times, real-time fluorescence imaging can be easily achieved. The ability to measure fluorescence from deep tissue layers enables clinically relevant applications, such as the detection of fluorescently labeled malignant tumors.

Raman and mid-infrared (MIR) spectroscopy are useful tools for the specific detection of molecules, since both methods are based on the excitation of fundamental vibration modes. In this study, Raman and MIR spectroscopy were applied simultaneously during aerobic yeast fermentations of Saccharomyces cerevisiae. Based on the recorded Raman intensities and MIR absorption spectra, respectively, temporal concentration courses of glucose, ethanol, and biomass were determined. The chemometric methods used to evaluate the analyte concentrations were partial least squares (PLS) regression and multiple linear regression (MLR). In view of potential photometric sensors, MLR models based on two (2D) and four (4D) analyte-specific optical channels were developed. All chemometric models were tested to predict glucose concentrations between 0 and 30 g L−1, ethanol concentrations between 0 and 10 g L−1, and biomass concentrations up to 15 g L−1 in real time during diauxic growth. Root-mean-squared errors of prediction (RMSEP) of 0.68 g L−1, 0.48 g L−1, and 0.37 g L−1 for glucose, ethanol, and biomass were achieved using the MIR setup combined with a PLS model. In the case of Raman spectroscopy, the corresponding RMSEP values were 0.92 g L−1, 0.39 g L−1, and 0.29 g L−1. Nevertheless, the simple 4D MLR models could reach the performance of the more complex PLS evaluation. Consequently, the replacement of spectrometer setups by four-channel sensors were discussed. Moreover, the advantages and disadvantages of Raman and MIR setups are demonstrated with regard to process implementation.

In this technical report we demonstrate a low-cost online unit allowing movement tracking of flagellated bacteria on a single-cell level during fermentation processes. The system's ability to distinguish different metabolic states (viability) of bacteria by movement velocity was investigated. A flow-through cuvette with automatically adjustable layer thickness was developed. The cuvette can be used with most commercially available laboratory microscopes equipped with 40× amplification and a digital camera. In addition, an automated sample preparation unit and a software module was developed measuring size, moved distance, and speed of bacteria. In a proof of principle study the movement velocities of Bacillus amyloliquefaciens FZB42 during three batch fermentation processes were investigated. In this process the bacteria went through different metabolic states, vegetative growth, diauxic shift, vegetative growth after diauxic shift, and sporulation. It was shown that the movement velocities during the different metabolic states significantly differ from each other. Therefore, the described setup has the potential to be used as a bacteria viability monitoring tool. In contrast to some other techniques, such as electro-optical techniques, this method can even be used in turbid production media.

Robust detection of prostatic cancer is a challenge due to the multitude of variants and their representation in MR images. We propose a pattern recognition system with an incremental learning ensemble algorithm using support vector machines (SVM) tackling this problem employing multimodal MR images and a texture-based information strategy. The proposed system integrates anatomic, texture, and functional features. The data set was preprocessed using B-Spline interpolation, bias field correction and intensity standardization. First- and second-order angular independent statistical approaches and rotation invariant local phase quantization (RI-LPQ) were utilized to quantify texture information. An incremental learning ensemble SVM was implemented to suit working conditions in medical applications and to improve effectiveness and robustness of the system. The probability estimation of cancer structures was calculated using SVM and the corresponding optimization was carried out with a heuristic method together with a 3-fold cross-validation methodology. We achieved an average sensitivity of 0.844 ± 0.068 and a specificity of 0.780 ± 0.038, which yielded superior or similar performance to current state of the art using a total database of only 41 slices from twelve patients with histological confirmed information, including cancerous, unhealthy non-cancerous and healthy prostate tissue. Our results show the feasibility of an ensemble SVM being able to learn additional information from new data while preserving previously acquired knowledge and preventing unlearning. The use of texture descriptors provides more salient discriminative patterns than the functional information used. Furthermore, the system improves selection of information, efficiency and robustness of the classification. The generated probability map enables radiologists to have a lower variability in diagnosis, decrease false negative rates and reduce the time to recognize and delineate structures in the prostate.