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Redox switches are applied in various fields of research, including molecular lifts, electronic devices and sensors. Switching the absorbance between UV and Vis/NIR by redox processes is of interest for applications in light harvesting or biomedicine.
Here, we present a series of push-pull benzothiadiazole derivatives with high fluorescence quantum yields in solution and in the crystalline solid state. Spectroelectrochemical analysis reveals the switching of UV-absorption in the neutral state to Vis/NIR absorption in the reduced state. We identify the partial irreversibility of the switching process, which appears to be reversible on the cyclic voltammetry timescale.
Tempo-spectral multiplexing in flow cytometry with lifetime detection using QD-encoded polymer beads
(2020)
Semiconductor quantum dots (QDs) embedded into polymer microbeads are known to be very attractive emitters for spectral multiplexing and colour encoding. Their luminescence lifetimes or decay kinetics have been, however, rarely exploited as encoding parameter, although they cover time ranges which are not easily accessible with other luminophores. We demonstrate here the potential of QDs made from II/VI semiconductors with luminescence lifetimes of several 10 ns to expand the lifetime range of organic encoding luminophores in multiplexing applications using time-resolved flow cytometry (LT-FCM). For this purpose, two different types of QD-loaded beads were prepared and characterized by photoluminescence measurements on the ensemble level and by single-particle confocal laser scanning microscopy. Subsequently, these lifetime-encoded microbeads were combined with dye-encoded microparticles in systematic studies to demonstrate the potential of these QDs to increase the number of lifetime codes for lifetime multiplexing and combined multiplexing in the time and colour domain (tempo-spectral multiplexing). These studies were done with a recently developed novel luminescence lifetime flow cytometer (LT-FCM setup) operating in the time-domain, that presents an alternative to reports on phase-sensitive lifetime detection in flow cytometry.
The growth of ultrathin layers of VOx (<12 monolayers) on Pt(111) and the activity of these layers in catalytic methanol oxidation at 10−4 mbar have been studied with low-energy electron difraction, Auger electron spectroscopy, rate measurements, and with photoemission electron microscopy. Reactive deposition of V in O2 at 670 K obeys a Stranski–Krastanov growth mode with a (√3 × √3)R30° structure representing the limiting case for epitaxial growth of 3D-VOx. The activity of VOx/Pt(111) in catalytic methanol oxidation is very low and no redistribution dynamics is observed lifting the initial spatial homogeneity of the VOx layer. Under reaction conditions, part of the surface vanadium difuses into the Pt subsurface region.
Exposure to O2 causes part of the V to difuse back to the surface, but only up to one monolayer of VOx can be stabilized in this way at 10−4 mbar.
The continuous improvement of analytical procedures using multi-collector technologies in ICP-mass spectrometry has led to an increased demand for isotope standards with improved homogeneity and reduced measurement uncertainty. For magnesium, this has led to a variety of available standards with different quality levels ranging from artefact standards to isotope reference materials certified for absolute isotope ratios. This required an intercalibration of all standards and reference materials, which we present in this interlaboratory comparison study. The materials Cambridge1, DSM3, ERMAE143, ERM-AE144, ERM-AE145, IRMM-009 and NIST SRM 980 were cross-calibrated with expanded measurement uncertainties (95% confidence level) of less than 0.030‰ for the δ25/24Mg values and less than 0.037‰ for the δ26/24Mg values. Thus, comparability of all magnesium isotope delta (δ) measurements based on these standards and reference materials is established. Further, ERM-AE143 anchors all magnesium δ-scales to absolute isotope ratios and therefore establishes SI traceability, here traceability to the SI base unit mole. This applies especially to the DSM3 scale, which is proposed to be maintained. With ERM-AE144 and ERM-AE145, which are product and educt of a sublimation-condensation process, for the first time a set of isotope reference materials is available with a published value for the apparent triple isotope fractionation exponent θapp, the fractionation relationship ln α(25/24Mg)/ln α(26/24Mg).
Since 1 January 2019 a maximum content of 0.6 mg kg−1 cadmium (Cd) in cocoa powder sold to the final consumer or as an ingredient in sweetened cocoa powder sold to the final consumer (drinking chocolate) is set by the Commission Regulation (EU) No. 488/2014. Monitoring compliance with the specified limit value requires analytical measuring methods and reference materials for quality control. However, suitable certified reference materials intended for quality assurance and quality control purposes are still lacking. Therefore, three cocoa reference materials (ERM®-BD513, ERM®-514 and ERM®-515) were developed according to the requirements of ISO 17034 and the recommendations of ISO Guide 35. The whole process of reference material development, including material preparation, assessment of homogeneity and stability, characterisation and value assignment is presented. The assignment of the certified mass fractions was based upon an interlaboratory comparison study involving 19 expert laboratories for Cd and 12 laboratories for acrylamide. The certified mass fractions and expanded uncertainties (k = 2) of the reference materials were (0.181 ± 0.009) mg kg−1 Cd (ERM®-BD513), (0.541 ± 0.024) mg kg−1 Cd (ERM®-BD514) and (0.690 ± 0.029) mg kg−1 Cd (ERM®-BD515). Acrylamide contents are given for information.
The theory of a new calibration approach for obtaining absolute isotope ratios of multi-isotopic elements without the use of any standard has been developed. The calibration approach basically uses the difference in the instrumental isotope fractionation of two different types of mass spectrometers, leading to two different fractionation lines in a three-isotope diagram. When measuring the same sample with both mass spectrometers, the different fractionation lines have one point in common: this is the ‘true’ logarithmized isotope ratio pair of the sample. Thus, the intersection of both fractionation lines provides us with the absolute isotope ratios of the sample. This theory has been tested in practice by measuring Cd and of Pb isotope ratios in the certified reference materials BAM-I012 and NIST SRM981 by thermal ionization mass spectrometry and by inductively coupled plasma mass spectrometry while varying the ionization conditions for both mass spectrometers. With this experiment, the theory could be verified, and absolute isotope ratios were obtained, which were metrologically compatible with the certified isotope ratios. The so-obtained absolute isotope ratios are biased by − 0.5% in average, which should be improved with further developments of the method. This calibration approach is universal, as it can be applied to all elements with three or more isotopes and it is not limited to the type of mass spectrometers applied; it can be applied as well to secondary ion mass spectrometry or others. Additionally, this approach provides information on the fractionation process itself via the triple-isotope fractionation exponent θ.
The Tutzing Symposium "100 % digital: survival strategies for the process industry" (see 4.1) in April 2018 was characterized by a great momentum which has been taken up and continued until today. The aim was to implement the ideas from the Tutzing Symposium in a coordinated and targeted manner. For this purpose, development needs as well as the numerous currently planned or already started research and development activities in the context of digitalisation were first compiled and analysed. This resulted in the current research landscape for digitalization in the process industry. It now enables to identify open topics and to translate them into research funding programs as well as to define new projects in the dialogue between users, suppliers and research, which are to be meaningfully interlinked and consolidated with existing projects.
Due to the strong interest in digitalisation, activities are constantly being added, so that this paper can only provide a snapshot of the situation in the period 2019-2020.
Industry 4.0 is all about interconnectivity, sensor-enhanced process control, and data-driven systems. Process analytical technology (PAT) such as online nuclear magnetic resonance (NMR) spectroscopy is gaining in importance, as it increasingly contributes to automation and digitalization in production. In many cases up to now, however, a classical evaluation of process data and their transformation into knowledge is not possible or not economical due to the insufficiently large datasets available. When developing an automated method applicable in process control, sometimes only the basic data of a limited number of batch tests from typical product and process development campaigns are available. However, these datasets are not large enough for training machine-supported procedures. In this work, to overcome this limitation, a new procedure was developed, which allows physically motivated multiplication of the available reference data in order to obtain a sufficiently large dataset for training machine learning algorithms. The underlying example chemical synthesis was measured and analyzed with both application-relevant low-field NMR and high-field NMR spectroscopy as reference method. Artificial neural networks (ANNs) have the potential to infer valuable process information already from relatively limited input data. However, in order to predict the concentration at complex conditions (many reactants and wide concentration ranges), larger ANNs and, therefore, a larger Training dataset are required. We demonstrate that a moderately complex problem with four reactants can be addressed using ANNs in combination with the presented PAT method (low-field NMR) and with the proposed approach to generate meaningful training data.
Current and future requirements to industrial analytical infrastructure—part 2: smart sensors
(2020)
Complex processes meet and need Industry 4.0 capabilities. Shorter product cycles, flexible production needs, and direct assessment of product quality attributes and raw material attributes call for an increased need of new process analytical technologies (PAT) concepts. While individual PAT tools may be available since decades, we need holistic concepts to fulfill above industrial needs. In this series of two contributions, we want to present a combined view on the future of PAT (process analytical technology), which is projected in smart labs (Part 1) and smart sensors (Part 2). Part 2 of this feature article series describes the future functionality as well as the ingredients of a smart sensor aiming to eventually fuel full PAT functionality. The smart sensor consists of (i) chemical and process information in the physical twin by smart field devices, by measuring multiple components, and is fully connected in the IIoT 4.0 environment. In addition, (ii) it includes process intelligence in the digital twin, as to being able to generate knowledge from multi-sensor and multi-dimensional data. The cyber-physical system (CPS) combines both elements mentioned above and allows the smart sensor to be self-calibrating and self-optimizing. It maintains its operation autonomously. Furthermore, it allows—as central PAT enabler—a flexible but also target-oriented predictive control strategy and efficient process development and can compensate variations of the process and raw material attributes. Future cyber-physical production systems—like smart sensors—consist of the fusion of two main pillars, the physical and the digital twins. We discuss the individual elements of both pillars, such as connectivity, and chemical analytics on the one hand as well as hybrid models and knowledge workflows on the other. Finally, we discuss its integration needs in a CPS in order to allow is versatile deployment in efficient process development and advanced optimum predictive process control.
The competitiveness of the chemical and pharmaceutical industry is based on ensuring the required product quality while making optimum use of plants, raw materials, and energy. In this context, effective process control using reliable chemical process analytics secures global competitiveness. The setup of those control strategies often originate in process development but need to be transferable along the whole product life cycle. In this series of two contributions, we want to present a combined view on the future of PAT (process analytical technology), which is projected in smart labs (part 1) and smart sensors (part 2). In laboratories and pilot plants, offline chemical analytical methods are frequently used, where inline methods are also used in production. Here, a transferability from process development to the process in operation would be desirable. This can be obtained by establishing PAT methods for production already during process development or scale-up. However, the current PAT (Bakeev 2005, Org Process Res 19:3–62; Simon et al. 2015, Org Process Res Dev 19:3–62) must become more flexible and smarter. This can be achieved by introducing digitalization-based knowledge management, so that knowledge from product development enables and accelerates the integration of PAT. Conversely, knowledge from the production process will also contribute to product and process development. This contribution describes the future role of the laboratory and develops requirements therefrom. In part 2, we examine the future functionality as well as the ingredients of a smart sensor aiming to eventually fuel full PAT functionality—also within process development or scale-up facilities (Eifert et al. 2020, Anal Bioanal Chem).