Evaluation of a purge-and-trap injection system for capillary gas chromatography-microwave induced plasma-atomic emission spectrometry for the determination of volatile selenium compounds in water

A method is presented for the selective determination of the volatile selenium species dimethylselenide and dimethyldiselenide, using a commercially available purge-and-trap injection system coupled to capillary gas chromatography-microwave induced plasma-atomic emission spectrometry. The efficiency of the purging step was evaluated and the parameters affecting the purge and trap processes were optimized. The method was applied to the determination of volatile selenium compounds in lake water. Relative detection limits of 2ng/l for dimethylselenide and dimethyldiselenide, corresponding to an absolute detection limit of 10 pg, were achieved.     

Si-E (E = N, O, F) bonding in a hexacoordinated silicon complex: new facts from experimental and theoretical charge density studies

The concept of hypervalency in molecules, which hold more than eight valence electrons at the central atom, still is a topic of constant debate. There is general interest in silicon compounds with more than four substituents at the central silicon atom. The dispute, whether this silicon is hypervalent or highly coordinated, is enlightened by the first experimental charge density determination and subsequent topological analysis of three different highly polar Si-E (E = N, O, F) bonds in a hexacoordinated compound. The experiment reveals predominantly ionic bonding and much less covalent contribution than commonly anticipated. For comparison gas-phase ab initio calculations were performed on this compound. The results of the theoretical calculations underline the findings of the experiment.     

Synthesis and Crystal Structure of the Hydrogen Polyphosphide Bis(Tetraphenylphosphonium) hydrogenheptaphosphide‐ammonia(1/3) (PPh4)2HP7 · 3NH3

(PPh₄)₂HP₇ · 3NH₃ was prepared by the reaction of K₃P₇ with a proton‐charged ion exchange resin in the presence of (PPh₄)Br in liquid ammonia, and characterized by low temperature X‐ray structure analysis. The thermally very unstable compound contains the hydrogenheptaphosphide anion HPequation/tex2gif-stack-1.gif, the nortricyclane‐like cage of which is slightly distorted by the attachment of the hydrogen atom.     

Cytotoxicity and Antiproliferative Effect of Hypericin and Derivatives after Photosensitization

The toxicity on three human tumor cell lines (A431, HeLa and MCF7) of five phenanthroperylenequinones (hypericin and derivatives) and two perylenequinones (cercosporin and calphostin C) was investigated after photosensitization (4 J/cm²). Furthermore, the antiproliferative effect on HeLa cells was studied for the phenanthroperylenequinones. Hypericin, 2,5-dibromohypericin, 2,5,9,12-tetrabromohypericin and perylenequinones displayed a potent cytotoxic and antiproliferative effect in the nanomolar range. Hypericin dicarboxylic acid exhibited no photoactivity. In general, the antiproliferative activity correlated well with the photocytotoxicity. However, the nonphotocytotoxic compound hexamethylhypericin showed potent antiproliferative activity in the nanomolar range, probably exerting its action by protein kinase C inhibition. Without light irradiation, no cytotoxic and antiproliferative effect was observed for any photocytotoxic phenanthroperylenequinone compound. Furthermore, confocal laser microscopy revealed that the subcellular localization in A431 cells was similar for the photoactive compounds; the photosensitizers were mainly concentrated in the perinuclear region, probably corresponding with the Golgi apparatus and the endoplasmic reticulum. In addition, the accumulation of the photosensitizers in HeLa cells was investigated. All compounds except hypericin dicarboxylic acid were found to concentrate to a large extent in the cells. The compound 2,5,9,12-tetrabromohypericin seemed intrinsically more effective than hypericin since the intracellular concentration of the bromoderivative was a magnitude of order lower than that of hypericin although both compounds showed similar photobiological activity.     

Laser-induced alignment and anti-alignment of rotationally excited molecules

We numerically investigate the post-pulse alignment of rotationally excited diatomic molecules upon nonresonant interaction with a linearly polarized laser pulse. In addition to the simulations, we develop a simple model which qualitatively describes the shape and amplitude of post-pulse alignment induced by a laser pulse of moderate power density. In our treatment we take into account that molecules in rotationally excited states can interact with a laser pulse not only by absorbing energy but also by stimulated emission. The extent to which these processes are present in the interaction depends, on the one hand, on the directionality of the molecular angular momentum (given by the M quantum number), and on the other hand on the ratio of transition frequencies and pulse duration (determined by the J number). A rotational wave packet created by a strong pulse from an initially pure state contains a broad range of rotational levels, over which the character of the interaction can change from non-adiabatic to adiabatic. Depending on the laser pulse duration and amplitude, the transition from the non-adiabatic to the adiabatic limit proceeds through a region with dominant rotational heating, or alignment, for short pulses and a large region with rotational cooling, and correspondingly preferred anti-alignment, for longer pulses.     

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.