Conformational analysis of self-organized monolayers with scanning tunneling microscopy at near-atomic resolution

We describe the synthesis and a novel approach to the conformational analysis of 2,2'-bipyridines (bpy) bearing aromatic rich Frechet-type dendritic wedges of the first and second generation as substituents. The evaporation of solutions of these new ligands on graphite surfaces under ambient conditions results in the formation of self-organized monolayers. Scanning tunneling microscopy (STM) investigations of the monolayers under ambient conditions (air, 298 K) gave images at submolecular and near-atomic resolution. The analysis of the STM images includes the following processes: (i) identification and reproduction of potential homoconformational domains, (ii) exclusion of improper data using quality criteria for drift and feedback artifacts, (iii) compilation of running averages and checking for averaging artifacts, (iv) analysis of three-dimensional and contour plots, (v) calculation of the HOMO properties of the free molecules, and (vi) final conformational assignment based on all accessible information. Following this procedure, two different conformations could be assigned to domains observed in the monolayers of the first-generation (G1) and second-generation (G2) dendritic compounds. Homoconformational domains are observed side-by-side. The different conformations arise from syn or anti arrangements at the ether substituents. An additional conformational effect is found upon treating the G1 domains with HCl gas, when a partial rearrangement of the bpy from trans to cis occurs, concomitant with protonation.     

Photochemical Sandmeyer-type Halogenation of Arenediazonium Salts

Trihalide salts were found to efficiently promote photochemical dediazotizing halogenations of diazonium salts. In contrast to classical Sandmeyer reactions, no metal catalysts are required to achieve high yields and outstanding selectivities for halogenation over competing hydridodediazotization. Convenient protocols are disclosed for synthetically meaningful brominations, iodinations, and chlorinations of diversely functionalized derivatives.     

Facile synthesis of potassium tetrathiooxalate – The “true” monomer for the preparation of electron-conductive poly(nickel-ethylenetetrathiolate)

Herein, aiming at optimization of the polymerization process leading to a family of hole- and electron-conducting 1,1,2,2-ethenetetrathiolate-based polymers, such as poly(nickel-1,1,2,2-ethenetetrathiolate), poly[K_x(Ni-ett)], we investigated transformations of the monomer precursor 1,3,4,6-tetrathiapentalene-2,5-dione (TPD) occurring under polymerization conditions. We found that only one ring of TPD opens upon its reaction with potassium methoxide under inert conditions at room temperature which leads to the formation of potassium 2-oxo-1,3-dithiol-4,5-dithiolate (K₂[3]). Heating of K₂[3] under reflux in methanol solution under inert conditions opens the second ring, however the resulting product is not potassium ethenetetrathiolate (K₄[2]), the product of an exhaustive methanolysis of TPD, but potassium tetrathiooxalate (K₂[4]), the product of the decarbonylation of K₂[3]. Preliminary experiments reveal that the involvement of K₂[4] in the polymerization process is beneficial for reproducible formation of high quality 1,1,2,2-ethenetetrathiolate-based polymers suitable for thermoelectric applications.     

Synthesis of Structurally Complex Silicon Frameworks through the First Sila-Aldol Reaction

Herein, we report on the first sila-aldol reaction, which emphasizes the tight connection between silicon and carbon chemistry. This novel synthetic method provides straightforward access to 2-oxahexasilabicyclo[3.2.1]octan-8-ide, a structurally complex silicon framework, in quantitative yield. Its structure was confirmed by NMR spectroscopy and X-ray crystallography, and it displays a distinctive charge-transfer transition. The complete mechanism of this highly selective rearrangement cascade is outlined and supported by density functional theory (DFT) calculations, which highlight the thermodynamic driving force and the low activation barriers of this powerful silicon–carbon bond-forming strategy.     

Highly Stable,Low Gas Crossover,Proton-Conducting Phenylated Polyphenylenes

Two classes of novel sulfonated phenylated polyphenylene ionomers are investigated as polyaromatic-based proton exchange membranes. Both types of ionomer possess high ion exchange capacities yet are insoluble in water at elevated temperatures. They exhibit high proton conductivity under both fully hydrated conditions and reduced relative humidity, and are markedly resilient to free radical attack. Fuel cells constructed with membrane-electrode assemblies containing each ionomer membrane yield high in situ proton conductivity and peak power densities that are greater than obtained using Nafion reference membranes. In situ chemical stability accelerated stress tests reveal that this class of the polyaromatic membranes allow significantly lower gas crossover and lower rates of degradation than Nafion benchmark systems. These results point to a promising future for molecularly designed sulfonated phenylated polyphenylenes as proton-conducting media in electrochemical technologies.     

A moment method for splashing and evaporation processes of polydisperse sprays

A new moment method for the modelling of polydisperse sprays is proposed that simultaneously takes into account the dispersion in droplet size and droplet velocity. For the derivation of this Eulerian method the kinetic spray equation is used which constitutes a partial differential equation for the probability density function of droplets. To reduce the complex kinetic spray equation to a form that can be managed with the available numerical procedures, moment transforms with respect to the droplet velocity and the droplet size are conducted. The resulting moment equations are closed by choosing an approximate probability density function which applies to polydisperse sprays. The method is successfully tested for configurations in which a polydisperse spray is either splashed, evaporated or effected by a Stokes drag force. The tests are organised in such a way that crossing of two spray distributions is always included. The new method is able to capture the polydisperse nature of sprays as well as the bi-(or multi-) modal character of the droplet velocity distribution function, for example, when droplets cross each other.     

Selective reagent ionisation‐time of flight‐mass spectrometry: a rapid technology for the novel analysis of blends of new psychoactive substances

In this study we demonstrate the potential of selective reagent ionisation‐time of flight‐mass spectrometry for the rapid and selective identification of a popular new psychoactive substance blend called ‘synthacaine’, a mixture that is supposed to imitate the sensory and intoxicating effects of cocaine. Reactions with H₃O⁺ result in protonated parent molecules which can be tentatively assigned to benzocaine and methiopropamine. However, by comparing the product ion branching ratios obtained at two reduced electric field values (90 and 170 Td) for two reagent ions (H₃O⁺ and NO⁺) to those of the pure chemicals, we show that identification is possible with a much higher level of confidence then when relying solely on the m/z of protonated parent molecules. A rapid and highly selective analytical identification of the constituents of a recreational drug is particularly crucial to medical personnel for the prompt medical treatment of overdoses, toxic effects or allergic reactions. Copyright © 2015 John Wiley & Sons, Ltd.     

Material-based process-chain optimization in metal forming

The characteristics of a manufacturing product are influenced by a variety of different factors, such as the material properties of the base product. The prediction of properties that give optimal results in metal forming applications is a complex task but of high interest for the manufacturer. To realize such a prediction scheme, the process chain is split up into individual process steps and for each of them an inverse modeling is required. The specific aim of this work is to present an approach for the inverse problem formulation of a process step and to solve it using methods of machine learning. Moreover, the challenges that often arise due to the ill-posed nature of inverse problems will be discussed. The main focus is on the crystallographic texture of metals, which strongly affects the deformation behavior during a process step and highly influences the characteristics of the final product. (© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)