Influence of Gd and Fe on crystallization of Al87Y5Ni8 amorphous alloy

Crystallization of amorphous Al-based alloys (Al-Y-Gd-Ni-Fe) was investigated by applying differential scanning calorimetry (DSC), X-ray diffraction (XRD) and high resolution electron microscopy (HREM). It was shown that the crystallization in the examined alloys proceeds in three stages (DSC maxima). The two first stages are attributed to formation of solid solution of fcc Al(RE) nanograins in amorphous matrix. In the third stage the precipitation of ternary compound Al₁₉Ni₅RE₃ of the orthorhombic Al₁₉Ni₅Gd₃-type structure was observed. A partial substitution of Ni by Fe causes a change of stoichiometry and crystal structure of the ternary compounds: Al₈TM₄RE (TM = Fe, Ni; RE = Y, Gd) of the tetragonal ThMn₁₂ (Al₈Mn₄Ce)-type structure. A partial replacing of Y atoms by Gd in the Al₈₇Y₅Ni₈ based alloy shifts the Al(RE) nanocrystallization to lower temperatures. In contrast to this a partial replacing of Ni by Fe shifts the nanocrystallization to higher temperatures.     

Planarized Phenyldithienylboranes: Effects of the Bridging Moieties and π-Extension on the Photophysical Properties and Lewis Acidity

Two kinds of planarized phenyldithienylboranes, which contain (CH₃)₂C- or CH₂-bridging moieties, were synthesized. The difference of the bridging moieties affects their packing structures and photophysical properties. In particular, the (CH₃)₂C-bridged derivative exhibits a large Stokes shift, unusual for such planarized compounds, that results from a large structural relaxation in the excited state. A series of π-extended derivatives was synthesized, among which a p-(diphenylamino)phenyl-substituted derivative shows large solvatochromism in the fluorescence spectra, while maintaining high quantum yields even in polar solvents. The Lewis acidity of the phenyldithienylborane derivatives was also assessed by titration with pyridine. The Lewis acidity of the boron center is affected not only by the difference in the steric bulk of the bridging moieties, but also by the electronic effect of the substituents introduced at remote positions relative to the boron atom. These results demonstrate the characteristic features of planarized phenyldithienylboranes as building blocks for boron-based π-electron materials.     

Um den Nachweis von Substanzen mittels der Boraxperle

Ohne Zusammenfassung     

Eine Methode zur Berechnung des mittleren Fehlers bei der konduktometrisehen Titration

Zusammenfassung Es wird eine Methode beschrieben, mit der man bei konduktometrischen Titrationen den mittleren Fehler des wahrscheinlichsten Resultates berechnen kann. Es wird ferner zur Bestimmung des Äquivalenzpunktes mit Hilfe des Prinzips der kleinsten Fehlerquadrate ein neues rechnerisches Verfahren abgeleitet, das trotz seiner Einfachheit das den Messungsergebnissen am besten entsprechende Resultat frei von jeder persönlichen Willkür liefert. Die Auswertung der Leitfähigkeitstitrationen auf Grund der abgeleiteten Methode wird an Beispielen gezeigt; hierbei wird darauf hingewiesen, daß die graphische Auswertung oft nicht verläßlich genug ist.     

A probabilistic approach to classifying metabolic stability

Metabolic stability is an important property of drug molecules that should-optimally-be taken into account early on in the drug design process. Along with numerous medium- or high-throughput assays being implemented in early drug discovery, a prediction tool for this property could be of high value. However, metabolic stability is inherently difficult to predict, and no commercial tools are available for this purpose. In this work, we present a machine learning approach to predicting metabolic stability that is tailored to compounds from the drug development process at Bayer Schering Pharma. For four different in vitro assays, we develop Bayesian classification models to predict the probability of a compound being metabolically stable. The chosen approach implicitly takes the "domain of applicability" into account. The developed models were validated on recent project data at Bayer Schering Pharma, showing that the predictions are highly accurate and the domain of applicability is estimated correctly. Furthermore, we evaluate the modeling method on a set of publicly available data.     

Fluorescence imaging of intracellular cadmium using a dual-excitation ratiometric chemosensor

We described here a coumarin-based dual-excitation ratiometric probe for cadmium, CadMQ. This fluorescence sensor has high quantum yields of 0.59 and 0.70 in the metal-free and Cd2+-bound forms, respectively, and has a dissociation constant of 0.16 nM for Cd2+. CadMQ is cell permeable and locates within the acidic compartments of the cells. We further show that CadMQ is a useful tool to ratiometrically probe the change in the intracellular Cd2+ levels with the use of two excited wavelengths.     

Accurate solubility prediction with error bars for electrolytes: a machine learning approach

Accurate in silico models for predicting aqueous solubility are needed in drug design and discovery and many other areas of chemical research. We present a statistical modeling of aqueous solubility based on measured data, using a Gaussian Process nonlinear regression model (GPsol). We compare our results with those of 14 scientific studies and 6 commercial tools. This shows that the developed model achieves much higher accuracy than available commercial tools for the prediction of solubility of electrolytes. On top of the high accuracy, the proposed machine learning model also provides error bars for each individual prediction.