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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?
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Thermal stability of monolayer fullerene networks: A molecular dynamics study with machine-learning potential

Computational Materials Science. 2025. Vol. 248. P. 113572–0.
Logunov M., Lazarev M.

Two-dimensional C60 carbon allotropes have gained much attention since their first synthesis in 2022, but many of their thermophysical and mechanical properties remain unreported in the literature. In this article, we performed a high-temperature molecular dynamics study of quasi-hexagonal (qHP) and quasi-tetragonal (qTP) C60 phases using the modern machine-learning interatomic potential GAP-20. We show that, contrary to previous calculations, at T>1200 K, both phases are unstable and decompose into individual C60 molecules. A low bending modulus indicates the possibility of nanoripple excitation at high temperatures, similar to those in graphene. We also demonstrate the crucial role of interatomic potential verification for MD analysis of previously unexplored carbon allotropes.

Research target: Physics
Language: English
DOI
Keywords: phase transitionscarbonhigh temperature molecular dynamicsFullerene
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