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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.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Band-Gap Engineering of High-Entropy Fluorite Metal Oxide Nanoparticles Facilitated by Pr3+ Incorporation by Gel Combustion Synthesis

Gels. 2025. Vol. 11. No. 2. Article 117.
Anandkumar M., Kesavan K. P., Sudarsan S., Zaitseva O. V., Ostovari Moghaddam A., Iarushina D. V., Трофимов Э.

Tailoring the bandgap of a material is necessary for improving its optical properties. Here, the optical bandgap of high-entropy oxide Ce0.2Gd0.2Sm0.2Y0.2Zr0.2O2-δ (HEO) nanoparticles was modified using Pr3+. Various concentrations of Pr3+ (x = 0, 0.01, 0.02, 0.05, 0.075, 0.1, 0.15) were incorporated into the host high-entropy oxide using a gel combustion synthesis. After the gel combustion step, the powders were heat-treated at various temper-
atures (650 ◦C, 800 ◦C, 950 ◦C) for 2 h. The obtained Pr3+-incorporated HEO powders were characterized using X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), and UV–visible spectroscopy. The results indicate that, when the samples are calcined at 950 ◦C, a single-phase cubic fluorite structure is obtained without any phase separation or impurity. The optical absorbance red-shifts to higher wavelengths when the
concentration of Pr3+ is increased. This reduces the bandgap of the material from 3.15 eV to 1.87 eV for Pr3+ concentrations of x = 0 (HEO-0) and x = 0.15 (HEO-6), respectively. The obtained HEOs can be suitable candidates for photocatalytic applications due to their absorbance in the visible region.

Research target: Materials Technologies Chemical Technologies
Language: English
Full text
DOI
Keywords: поглощениетвердый растворband gapSolid solutionHigh-entropy oxidesВысокоэнтропийный оксидgel combustionabsorbancefluorite oxideгорение гелязапрещенная зонаоксид флюорита
Publication based on the results of:
Advanced materials and technologies (2025)
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