Electronically Excited States in Model Complexes of Noble Metal Clusters with Carbon Nanodots

Russian Physics Journal - Theoretical calculations of excited states in the complexes of gold and silver three-atom nanoclusters with carbon quantum nanodots are performed using the M062X...     

Energy contribution of heterocyclic sulfur and a disulfide bond in solid and gaseous phase

Structural Chemistry - In the present work, the energy contribution of the sulfur atom in a heterocycle and in a disulfide bond in solid and gas phases was calculated. To achieve this goal,...     

Synthesis,Molecular Docking,and Hemorheological Activity of New 4-(Thien-2-yl)-3-aminopyridine-2(1H)-one Derivatives

Russian Journal of General Chemistry - On the basis of 4-(thien-2-yl)-3-aminopyridine-2(1H)-one, the corresponding chloroacetamide and condensed 1H-pyrido[2,3-b][1,4]oxazine-2(3H)-one were...     

Separation,Preconcentration, and Determination of Lead,Cadmium, and Iron Using Cloud Point Extraction with Flame Atomic Absorption Spectrometry

Journal of Applied Spectroscopy - The concentration of heavy metals in drinking water is an important standard for water quality evaluation and water pipeline corrosion detection. This research...     

Dislocation Structure Evolution in Low-Stability States of Solid Solutions of Alloys Under Their Deformation

Russian Physics Journal - The results of a study of the dislocation structure evolution in polycrystals of homogeneous solid solutions in low-stability states in Cu-Mn-based alloys with FCC crystal...     

Alpha-gamma decay studies of $$^{247}$$ Md

The European Physical Journal A - The goal of the present paper is twofold. First, a novel expansion many-body method applicable to superfluid open-shell nuclei, the so-called Bogoliubov in-medium...     

Application of Machine Learning for Tool Condition Monitoring in Turning

The machining process is primarily used to remove material using cutting tools. Any variation in tool state affects the quality of a finished job and causes disturbances. So, a tool monitoring scheme (TMS) for categorization and supervision of failures has become the utmost priority. To respond, traditional TMS followed by the machine learning (ML) analysis is advocated in this paper. Classification in ML is supervised based learning method wherein the ML algorithm learn from the training data input fed to it and then employ this model to categorize the new datasets for precise prediction of a class and observation. In the current study, investigation on the single point cutting tool is carried out while turning a stainless steel (SS) workpeice on the manual lathe trainer. The vibrations developed during this activity are examined for failure-free and various failure states of a tool. The statistical modeling is then incorporated to trace vital signs from vibration signals. The multiple-binary-rule-based model for categorization is designed using the decision tree. Lastly, various tree-based algorithms are used for the categorization of tool conditions. The Random Forest offered the highest classification accuracy, i.e., 92.6%.

     

Intermetallic Compounds CsnMk (М = Na,K, Rb,Pt, Au,Hg, Te): Geometrical and Topological Analysis,Cluster Precursors,and Self-Assembly of Crystal Structures

Crystallography Reports - A geometrical and topological analysis has been performed, and self-assembly of the crystal structures of intermetallic compounds CsnMk (М = Na, K, Rb, Pt, Au, Hg,...     

Filtration with Multiple Species of Particles

Transport in Porous Media - Membrane filtration of feed containing multiple species of particles is a common process in the industrial setting. In this work, we propose a model for filtration of a...