Copper-doping effects in electronic structure and spectral properties of SmNi₅

The electronic structure and optical properties of the SmNi₅₋Cux (x = 0, 1, 2) compounds are studied. The band spectra of the studied intermetallics were calculated with LDA+U+SO method supplementing the local density approximation with a correction for strong electron interaction on the shell of the rare-earth element. Optical properties were studied by ellipsometry method in the wide wavelength range. It was found that the substitution of copper for nickel leads to local changes in the optical conductivity spectra. Both the spectroscopic measurements and theoretical calculations demonstrate the presence of a broad absorption band around 4 eV associated with the Cu 3d → Ni 3d electron transitions and increasing with the grown of copper content. The experimental dispersion curves of optical conductivity in the interband absorption region were interpreted using the results of the calculations

QSAR analysis of the toxicity of nitroaromatics in Tetrahymena pyriformis : structural factors and possible modes of action

The Hierarchical Technology for Quantitative Structure - Activity Relationships (HiT QSAR) was applied to 95 diverse nitroaromatic compounds (including some widely known explosives) tested for their toxicity (50% inhibition growth concentration, IGC50) against the ciliate Tetrahymena pyriformis. The dataset was divided into subsets according to putative mechanisms of toxicity. Classification and Regression Trees (CART) approach implemented within HiT QSAR has been used for prediction of mechanism of toxicity for new compounds. The resulting models were shown to have ~80% accuracy for external datasets indicating that the mechanistic dataset division was sensible. Then, Partial Least Squares (PLS) statistical approach was used for the development of 2D QSAR models. Validated PLS models were explored to (i) elucidate the effects of different substituents in nitroaromatic compounds on toxicity; (ii) differentiate compounds by probable mechanisms of toxicity based on their structural descriptors; (iii) analyze the role of various physical-chemical factors responsible for compounds’ toxicity. Models were interpreted in terms of molecular fragments promoting or interfering with toxicity. It was also shown that mutual influence of substituents in benzene ring plays the determining role in toxicity variation. Although chemical mechanism based models were statistically significant and externally predictive (R2ext=0.64 for the external set of 63 nitroaromatics identified after all calculations have been completed), they were also shown to have limited coverage (57% for modeling and 76% for external set)