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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
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Towards atomistic modelling of solid Pb-O formation and dissolution in liquid lead coolant: Interatomic potential development

Journal of Nuclear Materials. 2024. Vol. 594. Article 155016.
Khnkoian G. V., Nikolaev V. S., Stegailov V.

Microscopic description of solid Pb-O formation and dissolution in liquid lead coolant is important for the modelling of fast neutron reactors. For this purpose, in this work we develop interatomic potential models for lead melt with dissolved oxygen. Potentials fitting is based on \textit{ab initio} density functional theory (DFT) calculations and quantum molecular dynamics. Two different potential models are trained on the DFT data using the force-matching method: a computationally cheap embedded atom method (EAM) potential and a computationally expensive machine-learned moment tensor potential (MTP) that allows reproducing DFT data very accurately. The potentials are further validated to reproduce the properties of lead melt and the coordination of oxygen atoms in molten lead. The diffusion coefficient for oxygen in molten lead is calculated and compared with the available experimental data. We analyse how these interatomic potential models describe the crystal structure of the solid lead oxide to consider PbO nucleation and dissolution in molten lead. We extensively discuss the arising problems with the description of long-range electrostatic interactions. The possibility of matching the experimental data on the oxygen solubility limit by tuning the EAM potential is shown.

Research target: Physics Computer Science Chemistry
Language: English
Full text
DOI
Keywords: диффузияSolubilityРастворимостьDiffusionInteratomic potentialмежатомный потенциалFast-neutron reactorsPb-OMolten leadSolvate shellPb-OРасплавленный свинецСольватная оболочкаРеакторы на быстрых нейтронах
Publication based on the results of:
Supercomputer molecular modeling in material science (2024)
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