Prediction of the Atomization Energy of Molecules Using Coulomb Matrix and Atomic Composition in a Bayesian Regularized Neural Networks

Exact calculation of electronic properties of molecules is a fundamental step for intelligent and rational compounds and materials design. The intrinsically graph-like and non-vectorial nature of molecular data generates a unique and challenging machine learning problem. In this paper we embrace a learning from scratch approach where the quantum mechanical electronic properties of molecules are predicted directly from the raw molecular geometry, similar to some recent works. But, unlike these previous endeavors, our study suggests a benefit from combining molecular geometry embedded in the Coulomb matrix with the atomic composition of molecules. Using the new combined features in a Bayesian regularized neural networks, our results improve well-known results from the literature on the QM7 dataset from a mean absolute error of 3.51 kcal/mol down to 3.0 kcal/mol.Comment: Under review ICANN 201

Nucleation mechanism for the direct graphite-to-diamond phase transition

Graphite and diamond have comparable free energies, yet forming diamond from graphite is far from easy. In the absence of a catalyst, pressures that are significantly higher than the equilibrium coexistence pressures are required to induce the graphite-to-diamond transition. Furthermore, the formation of the metastable hexagonal polymorph of diamond instead of the more stable cubic diamond is favored at lower temperatures. The concerted mechanism suggested in previous theoretical studies cannot explain these phenomena. Using an ab initio quality neural-network potential we performed a large-scale study of the graphite-to-diamond transition assuming that it occurs via nucleation. The nucleation mechanism accounts for the observed phenomenology and reveals its microscopic origins. We demonstrated that the large lattice distortions that accompany the formation of the diamond nuclei inhibit the phase transition at low pressure and direct it towards the hexagonal diamond phase at higher pressure. The nucleation mechanism proposed in this work is an important step towards a better understanding of structural transformations in a wide range of complex systems such as amorphous carbon and carbon nanomaterials

THE METABOLIC DISTURBANCES AS THE INDICATOR OF THE HARMFUL ACTION OF THE INDUSTRIAL POISONS IN THE PROBLEM OF THE PROPHYLACTIC TOXICOLOGY

The objects of investigation: 17 chemical substances, relating to the different classes of the compounds (the derivatives of hydrazine, amino butane acid, amino nitriles and others) in the experiments performed on the minor laboratory animals. The work is aimed at studying the biological role of the xenobiotics metabolism processes in the development of the pathology and formation of the organism adaptation reactions for the needs of the theory and practice of hygiene. For the first time, the conception about the obligatory interaction (direst or indirect) of the most of chemical substances, getting in the organism with the system of the microsomal MOG, has been formulated. Theoretically and experimentally justified has been the role of the microsomal oxydation as the most important mechanism of the biochemical adaptation to the poison effect. The obtained results contribute to the objective evaluation of the industrial poisons and medicine means real danger with its acute and chronic entering the organism, they allow to consider and prognose the character of its combined action. The materials have been used in justification of the hygienic regulations. The MPC for the operating zone air for 13 chemical substances, the methodical recommendations have been justified and approved by the USSR Health Ministry. The field of application: the medicine, sanitary, the chemical and pharmacological industryAvailable from VNTIC / VNTIC - Scientific & Technical Information Centre of RussiaSIGLERURussian Federatio