No abstract

A methodology was developed to select adequate, commercially available micromixers for mixing sensitive chemical reactions. The range of flow rates can be derived at which the selected micromixers have to be operated to ensure the required mixing intensity. This methodology enables the selection of adequate micromixers for the scale up of the chemical reactions to higher flow rates. Two chemical test reactions were used for an experimental approach to characterize the selected microreactors. Both reactions are based on the effect of micromixing on the product distribution of competitive reaction systems. Flow rates and pressure drop were determined at which the mixing times are short relative to the reaction times. In this case, influences of mixing on the selectivity of the reference reaction can be neglected. Since two reference reactions with different time scales for mixing and reaction were tested, it was possible to study the mixing performance of a variety of micromixers over a wide range of flow rates. The investigated micromixers differ in their dimensions, internal geometry, and mixing principle. In the present work, overview tables are provided as a tool to evaluate the commercially available micromixers for specific applications. Further, the influence of mixing principle and pressure drop is discussed.

This work describes a simple approach for the untargeted profiling of volatile compounds for the authentication of the botanical origins of honey based on resolution-optimized HS-GC-IMS combined with optimized chemometric techniques, namely PCA, LDA, and kNN. A direct comparison of the PCA-LDA models between the HS-GC-IMS and H NMR data demonstrated that HS-GC-IMS profiling could be used as a complementary tool to NMR-based profiling of honey samples. Whereas NMR profiling still requires comparatively precise sample preparation, pH adjustment in particular, HS-GC-IMS fingerprinting may be considered an alternative approach for a truly fully automatable, cost-efficient, and in particular highly sensitive method. It was demonstrated that all tested honey samples could be distinguished on the basis of their botanical origins. Loading plots revealed the volatile compounds responsible for the differences among the monofloral honeys. The HS-GC-IMS-based PCA-LDA model was composed of two linear functions of discrimination and 10 selected PCs that discriminated canola, acacia, and honeydew honeys with a predictive accuracy of 98.6%. Application of the LDA model to an external test set of 10 authentic honeys clearly proved the high predictive ability of the model by correctly classifying them into three variety groups with 100% correct classifications. The constructed model presents a simple and efficient method of analysis and may serve as a basis for the authentication of other food types.

This study demonstrates that a microreactor setup with fast in-line reaction monitoring by Raman spectroscopy can be a highly efficient laboratory tool for kinetic studies and process development. Using a coaxial probe and commercial spectrometer to perform real-time measurements in the microchannel prevents the need for reaction quenching, sampling, and time-consuming off-line analysis methods such as GC or HPLC. A specially designed, temperature-controlled aluminum plate microreactor was developed and tested in the exothermic synthesis of 3-piperidino propionic acid ethyl ester by Michael addition. In-line measurements through a fused quartz screen in the reactor channel, which had an increasing cross-sectional area, allowed time-series kinetic data to be collected over nearly the full range of reaction conversions. An optimum flow rate range in which nearly ideal plug flow behavior can be assumed was identified. Furthermore, a time gradient was applied to the reactant flow rates, and the product concentration was simultaneously and repeatedly measured at various locations in the reactor channel. With this approach, the experiment duration and material consumption are significantly reduced relative to those of conventional steadystate experiments. Two hundred data points with residence times ranging from 0.3 to 49 s were collected in less than 1 h. Thus, this method can be used for the high-throughput screening of reaction parameters in a microreactor.

Microreactors are an efficient tool for process development and intensification. However, the scale-up from lab studies to small-scale commercial production is challenging, since a change in the channel dimensions requires good knowledge of heat and mass transfer phenomena. In this work, complete process development for an exothermic Michael addition is presented. In a systematic scale-up approach, kinetic studies and experimental characterization of the employed reactors provide key parameters for detailed reactor modelling. The residence time distribution, reactant mixing, and removal of reaction heat are taken into account. It is exemplarily shown how preliminary experiments can be the basis for the prediction of scale-up effects and the development of a continuous production process. Plug flow behavior and short mixing times could be confirmed for all investigated flow reactors. Furthermore, interactions of reaction kinetics and the formation of hot spots in the reactor channel were investigated. For the examined reaction, the simulations predicted the product yield under production conditions in good accuracy.