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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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Selective area epitaxy of gallium phosphide-based nanostructures on microsphere lithography-patterned Si wafers for visible light optoelectronics

Materials Research Bulletin. 2025. Vol. 182. Article 113126.
Dvoretckaia L. N., Fedorov V. V., Pavlov A., Sergey D. Komarov, Eduard I. Moiseev, Miniv D. V., Kaveev A. K., Smirnov A. G., Kirilenko D. A., Mozharov A. M., Mukhin I. S.

In this study, we present the selective area plasma-assisted molecular beam epitaxial growth of GaP-based nanoheterostructures (nanostubs), incorporating direct bandgap GaAsP or GaPN segments, on patterned SiO2/ Si(001) wafers. A microsphere optical lithography and anisotropic Si wet-etching techniques were employed for wafer-scale surface patterning through SiO2 growth mask, allowing to obtain either planar or pyramidal pit nucleation site morphologies. X-ray diffraction reciprocal space mapping and Raman microspectroscopy studies confirm compositional homogeneity of the nanostub arrays. The dilute nitride nanostubs display the narrowest and most intense visible red photoluminescence response at room temperature, which is an order of magnitude higher compared to the GaAsP ones. The formation of the nitrogen sub-band in GaPN alloy was confirmed in the framework of density functional theory, providing insights for interpreting the experimental results. These findings demonstrate the feasibility of the proposed approach for fabricating the ordered arrays of nanoscale visible light emitters on silicon.

Research target: Physics Nanotechnologies
Language: English
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Keywords: DFTIII-V on Sinanoheterostructuresselective area growthdilute nitride semiconductorsнаногетероструктурынизкоразмерные нитридные полупроводникиизбирательный ростIII-V на Siтеория функционала плотности
Publication based on the results of:
Study of disk microlasers and photonic integrated circuits for optical switching and sensing elements (2025)
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