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A. N. Ryzhov

Researcher at Russian Academy of Sciences

Publications -  21
Citations -  102

A. N. Ryzhov is an academic researcher from Russian Academy of Sciences. The author has contributed to research in topics: Oil shale & Octane. The author has an hindex of 4, co-authored 21 publications receiving 91 citations. Previous affiliations of A. N. Ryzhov include Samara State Technical University.

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Taxol: Synthesis, bioactive conformations, and structure-activity relationships in its analogs

TL;DR: The review describes the syntheses and probable biologically active conformations of taxol, a natural antitumor agent, and systematizes published data on the structure-activity relations in the series ofTaxol analogs.
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Cetane numbers of hydrocarbons: calculations using optimal topological indices

TL;DR: In this article, the QSPR problem for cetane numbers of hydrocarbons, a key property of oil fuels, was considered for the first time, and calculations have been carried out and relations derived for prediction of the Cetane number of alkanes and cycloalkanes.
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Octane numbers (ONs) of hydrocarbons: a QSPR study using optimal topological indices for the topological equivalents of the ONs

TL;DR: In this paper, a transition from numerical values to topological equivalents (TEs) of physicochemical properties of chemical compounds is proposed for solving QSPR tasks, where the TEs are unambiguously related to corresponding properties; for n-alkanes, they are linear functions of the number of carbon atoms.
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Ad hoc optimal topological indices for QSPR

TL;DR: In this paper, the optimal topological indices for particular physicochemical properties can be designed using the chemical structure matrix, taking the alkane boiling points as examples, and the advantages of the new indices are shown.
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Modeling the octane numbers of alkenes by the inverse function method

TL;DR: In this paper, the octane number of alkenes has been simulated with the use of optimal topological indices and the results suggest the maximum attainable (within linear QSPR approaches) accuracy of calculation, which exceeds by a few orders of magnitude that of previously known procedures.