New cationic group 4 metal alkyl complexes

Cationic group 4 metal alkyl complexes containing tetradentate Schiff base ligands, (acen) Zr(R)⁺ and (F6-acen) Zr(R)⁺, are prepared by protonolysis of suitable neutral dialkyl precursors. These complexes display electrophilic behavior and are moderately active ethylene polymerization catalysts in the presence of 1 molar equivalent of AlR₃.     

Defined carrageenan derivatives as angiogenesis inhibitors

Three carrageenans derived from red algae and three partially modified carrageenans were tested for their ability to inhibit the formation of new blood capillaries on the chorionallantois membrane of the hen egg. It could be clearly demonstrated that they were better angiogenesis inhibitors than the standard compound suramin.     

Highly charged ions in a new era of high resolution X-ray astrophysics

X-ray astronomy and ground-based atomic physics have a long history of fruitful collaboration: Sound understanding of the underlying atomic physics is the key to reliable interpretation of the spectra from celestial sources; conversely, astronomical spectra have been used to benchmark and advance atomic physics. This interplay is about to become even more important as we enter a new era of high-resolution X-ray astrophysics with large effective collection area. Although high-resolution observations with the gratings on the Chandra and XMM-Newton observatories continue to drive new science, upcoming planned and proposed missions will open up new discovery space in the near future that is currently challenging to access: high-resolution spectroscopy on extended sources, in the Fe K band, and on short time scales. This review summarizes open questions in these areas and the design parameters for the Hitomi, XRISM, Athena, and Arcus observatories. The expected high quality of spectra taken with these observatories puts new constraints on the accuracy of atomic reference data required to take full advantage of the diagnostic potential of these spectra.     

Optimization of STEM-HAADF Electron Tomography Reconstructions by Parameter Selection in Compressed Sensing Total Variation Minimization-Based Algorithms

A novel procedure to optimize the 3D morphological characterization of nanomaterials by means of high angle annular dark field scanning-transmission electron tomography is reported and is successfully applied to the analysis of a metal- and halogen-free ordered mesoporous carbon material. The new method is based on a selection of the two parameters (μ and β) which are key in the reconstruction of tomographic series by means of total variation minimization (TVM). The parameter-selected TVM reconstructions obtained using this approach clearly reveal the porous structure of the carbon-based material as consisting of a network of parallel, straight channels of ≈6 nm diameter ordered in a honeycomb-type arrangement. Such an unusual structure cannot be retrieved from a TVM 3D reconstruction using default reconstruction values. Moreover, segmentation and further quantification of the optimized 3D tomographic reconstruction provide values for different textural parameters, such as pore size distribution and specific pore volume that match very closely with those determined by macroscopic physisorption techniques. The approach developed can be extended to other reconstruction models in which the final result is influenced by parameter choice.     

Geometry Optimization of Thermoelectric Modules: Deviation of Optimum Power Output and Conversion Efficiency

Besides the material research in the field of thermoelectrics, the way from a material to a functional thermoelectric (TE) module comes alongside additional challenges. Thus, comprehension and optimization of the properties and the design of a TE module are important tasks. In this work, different geometry optimization strategies to reach maximum power output or maximum conversion efficiency are applied and the resulting performances of various modules and respective materials are analyzed. A Bi₂Te₃-based module, a half-Heusler-based module, and an oxide-based module are characterized via FEM simulations. By this, a deviation of optimum power output and optimum conversion efficiency in dependence of the diversity of thermoelectric materials is found. Additionally, for all modules, the respective fluxes of entropy and charge as well as the corresponding fluxes of thermal and electrical energy within the thermolegs are shown. The full understanding and enhancement of the performance of a TE module may be further improved.     

New Interfaces and Approaches to Machine Learning When Classifying Gestures within Music

Interactive music uses wearable sensors (i.e., gestural interfaces—GIs) and biometric datasets to reinvent traditional human–computer interaction and enhance music composition. In recent years, machine learning (ML) has been important for the artform. This is because ML helps process complex biometric datasets from GIs when predicting musical actions (termed performance gestures). ML allows musicians to create novel interactions with digital media. Wekinator is a popular ML software amongst artists, allowing users to train models through demonstration. It is built on the Waikato Environment for Knowledge Analysis (WEKA) framework, which is used to build supervised predictive models. Previous research has used biometric data from GIs to train specific ML models. However, previous research does not inform optimum ML model choice, within music, or compare model performance. Wekinator offers several ML models. Thus, we used Wekinator and the Myo armband GI and study three performance gestures for piano practice to solve this problem. Using these, we trained all models in Wekinator and investigated their accuracy, how gesture representation affects model accuracy and if optimisation can arise. Results show that neural networks are the strongest continuous classifiers, mapping behaviour differs amongst continuous models, optimisation can occur and gesture representation disparately affects model mapping behaviour; impacting music practice.     

Separation technology of used polymers

The technology of separating plastics from the municipal waste stream for reuse is reviewed, with emphasis on the key role played by the bottle sorting step. Experience gained in the first year's operation of two large commercial recycling plants provides a better understanding of practical problems encountered, their relative importance, and technical advances needed for improved operation. It is concluded that purity of feedstock and processing rate are two critical independent variables requiring technical and business understanding and management. Hypothetical examples illustrate the interplay of these with dependent variables of yield and sorting cost.     

New 19F NMR methodology reveals structures of molecules in complex mixtures of fluorinated compounds

Although the number of natural fluorinated compounds is very small, fluorinated pharmaceuticals and agrochemicals are numerous. ¹⁹F NMR spectroscopy has a great potential for the structure elucidation of fluorinated organic molecules, starting with their production by chemical or chemoenzymatic reactions, through monitoring their structural integrity, to their biotic and abiotic transformation and ultimate degradation in the environment. Additionally, choosing to incorporate ¹⁹F into any organic molecule opens a convenient route to study reaction mechanisms and kinetics. Addressing limitations of the existing ¹⁹F NMR techniques, we have developed methodology that uses ¹⁹F as a powerful spectroscopic spy to study mixtures of fluorinated molecules. The proposed ¹⁹F-centred NMR analysis utilises the substantial resolution and sensitivity of ¹⁹F to obtain a large number of NMR parameters, which enable structure determination of fluorinated compounds without the need for their separation or the use of standards. Here we illustrate the ¹⁹F-centred structure determination process and demonstrate its power by successfully elucidating the structures of chloramination disinfectant by-products of a single mono-fluorinated phenolic compound, which would have been impossible otherwise. This novel NMR approach for the structure elucidation of molecules in complex mixtures represents a major contribution towards the analysis of chemical and biological processes involving fluorinated compounds.

¹⁹F-centred NMR structure determination protocol alleviates the need for compound separation. Disinfection byproducts of chloramination were unraveled by analyzing the reaction pathways of a single fluorinated molecule.     

Synthesis of Novel C/D Ring Modified Bile Acids

Bile acid receptors have been identified as important targets for the development of new therapeutics to treat various metabolic and inflammatory diseases. The synthesis of new bile acid analogues can help elucidate structure–activity relationships and define compounds that activate these receptors selectively. Towards this, access to large quantities of a chenodeoxycholic acid derivative bearing a C-12 methyl and a C-13 to C-14 double bond provided an interesting scaffold to investigate the chemical manipulation of the C/D ring junction in bile acids. The reactivity of this alkene substrate with various zinc carbenoid species showed that those generated using the Furukawa methodology achieved selective α-cyclopropanation, whereas those generated using the Shi methodology reacted in an unexpected manner giving rise to a rearranged skeleton whereby the C ring has undergone contraction to form a novel spiro–furan ring system. Further derivatization of the cyclopropanated steroid included O-7 oxidation and epimerization to afford new bile acid derivatives for biological evaluation.