Analytische Chemie
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This study shows remarkably different features between the oxidation of secondary and primary C₃-C₅ alcohols. The oxidation of primary alcohols is controlled by the oxidative removal of blocking adsorbates, such as CO, formed after the dissociative adsorption of alcohol molecules. Conversely, secondary alcohols do not undergo dissociative adsorption and therefore their oxidation is purely controlled by the energetics of the elementary reaction steps. In this respect, a different role of ruthenium is revealed for the electrooxidation of primary and secondary alcohols on bimetallic platinum-ruthenium catalysts. Ruthenium enhances the oxidation of primary alcohols via the established bifunctional mechanism, in which the adsorption of (hydr)oxide species that are necessary to remove the blocking adsorbates is favored. In contrast, the oxidation of secondary alcohols is enhanced by the Ru-assisted stabilization of an O-bound intermediate that is involved in the potential-limiting step. This alternative pathway enables the oxidation of secondary alcohols close to the equilibrium potential.
Understanding on how a machine learning model interprets data is a crucial step to verify its reliability and avoid overfitting. While the focus of the scientific community is nowadays orientated towards deep learning approaches, which are considered as black box approaches, this work presents a toolbox that is based on complementary methods of feature extraction and selection, where the classification decisions of the model are transparent and can be physically interpreted. On the example of guided wave benchmark data from the open guided waves platform, where delamination defects were simulated at multiple positions on a carbon fiber reinforced plastic plate under varying temperature conditions, the authors could identify suitable frequencies for further investigations and experiments. Furthermore, the authors presented a realistic validation scenario which ensures that the machine learning model learns global damage characteristics rather than position specific characteristics.
Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are critical components of every industrial chemical process as they provide information on the concentrations of individual compounds and by-products. These processes are carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been developed to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra to train an ANN with better prediction performance and speed than state-of-theart analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a possible strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control.
Recent progress has shown that using wavelengths between 1,000 and 2,000 nm, referred to as the shortwave-infrared or near-infrared (NIR)-II range, can enable high-resolution in vivo imaging at depths not possible with conventional optical wavelengths.
However, few bioconjugatable probes of the type that have proven invaluable for multiplexed imaging in the visible and NIR range are available for imaging these wavelengths. Using rational design, we have generated persulfonated indocyanine dyes with absorbance maxima at 872 and 1,072 nm through catechol-ring and aryl-ring fusion, respectively, onto the nonamethine scaffold. Multiplexed two-color and three-color in vivo imaging using monoclonal antibody and dextran conjugates in several tumor models illustrate the benefits of concurrent labeling of the tumor and healthy surrounding tissue and lymphatics.
These efforts are enabled by complementary advances in a custom-built NIR/shortwave-infrared imaging setup and software package for multicolor real-time imaging.
Carbamazepine Dihydroxybenzoic Acid Cocrystals: Exploring Packing Interactions and Reaction Kinetics
(2021)
Herein, we present the mechanochemical formation of three new cocrystals containing the active pharmaceutical ingredient carbamazepine and dihydroxybenzoic acids as coformers (CBZ:2,4-DHBA 1:1, CBZ:2,5-DHBA 1:1, and CBZ:2,6-DHBA 1:1). Rietveld methods were used for three different purposes: (i) refining all structures solved using powder X-ray diffraction, (ii) performing a quantitative phase analysis of the diffraction data collected from ex situ mechanochemical reactions at different milling times, and (iii) determining the cocrystallization kinetic profiles. The rate of cocrystallization was found to be higher for the formation of CBZ:2,4-DHBA and CBZ:2,6-DHBA, reaching an equilibrium after 600 s of milling. In the case of CBZ:2,5-DHBA a short induction period of 20 s was detected prior to the start of the reaction and an equilibrium was reached after 1200 s. An empirical trend between the rate of cocrystallization and the structural complexity of the cocrystal product was found. The slowest cocrystallization rate observed for CBZ:2,5-DHBA corresponds to the crystal structure deviating substantially from the hydrogen-bonding motif found in the reactants.
We obtained concomitant dimorphic forms of Anthracene Schiffbase (N-(anthracen-9-yl methylene)-2,5- dichloroaniline) from hexane solvent. Two polymorphs can be differentiated by their morphology and mechanical properties. One form is long acicular type and elastically bendable while another form is block shaped and brittle in nature. Mechanical property is attributed to underlying crystal packing. Hirsh- feld analysis and energy framework calculations were done to corroborate structure-property correlation of two forms.
The aim of this paper is to present the productive interplay of connoisseurship and material analysis when dealing with drawings by Rembrandt – or previously attributed to him – in the collection of the Klassik Stiftung Weimar. This concerns the more precise determination of the drawing materials used and the reconstruction of the genesis of the drawings discussed. The material analysis allows us to decide whether and how Rembrandt’s inks can be used to determine authorship at all. The “material turn” in drawing studies thus intervenes in the discussion about authorship and opens up a broader production aesthetic perspective. No longer the “style” but rather the handeling becomes the decisive criterion for answering the question “Rembrandt, or not?”
Increasing contamination of environmental waters with pharmaceuticals represents an emerging threat for the drinking water quality and safety. In this regard, fast and reliable analytical methods are required to allow quick countermeasures in case of contamination. Here, we report the development of a magnetic bead-based immunoassay (MBBA) for the fast and cost-effective determination of the analgesic diclofenac (DCF) in water samples, based on diclofenac-coupled magnetic beads and a robust monoclonal anti-DCF antibody. A novel synthetic strategy for preparation of the beads resulted in an assay that enabled for the determination of diclofenac with a significantly lower limit of detection (400 ng/L) than the respective enzyme-linked immunosorbent assay (ELISA). With shorter incubation times and only one manual washing step required, the assay demands for remarkably shorter time to result (< 45 min) and less equipment than ELISA. Evaluation of assay precision and accuracy with a series of spiked water samples yielded results with low to moderate intra- and inter-assay variations and in good agreement with LC–MS/MS reference analysis. The assay principle can be transferred to other, e.g., microfluidic, formats, as well as applied to other analytes and may replace ELISA as the standard immunochemical method.
Through connecting genomic and metabolic information, metaproteomics is an essential approach for understanding how microbiomes function in space and time. The international metaproteomics community is delighted to announce the launch of the Metaproteomics Initiative (www.metaproteomics.org), the goal of which is to promote dissemination of metaproteomics fundamentals, advancements, and applications through collaborative networking in microbiome research. The Initiative aims to be the central information hub and open meeting place where newcomers and experts interact to communicate, standardize, and accelerate experimental and bioinformatic methodologies in this feld. We invite the entire microbiome community to join and discuss potential synergies at the interfaces with other disciplines, and to collectively promote innovative approaches to gain deeper insights into microbiome functions and dynamics.