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November 10, 2026
Physicists Train AI to Optimise Particle Beams in Accelerators
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science and the Budker Institute of Nuclear Physics at the Siberian Branch of the Russian Academy of Sciences have developed RLABC (Reinforcement Learning for Accelerator Beamline Control), a framework that uses reinforcement learning to identify optimal settings for a particle accelerator. In a computer simulation, RLABC optimised the accelerator's parameters to achieve a particle transmission rate of 70%. The study has been published in Computer Physics Communications.
November 9, 2026
'Organ-on-a-Chip Technology Could Eliminate the Need for Animal Testing'
The Laboratory of Molecular Physiology at the HSE Faculty of Biology and Biotechnology investigates how molecular regulators known as microRNAs control gene expression and contribute to the development of diseases, including cancer, viral and inflammatory conditions, and pregnancy complications. At HSE University, researchers develop organ-on-a-chip models: miniature devices containing living cells that mimic the functions of human organs, such as the placenta and intestines. These models help researchers understand how diseases develop and how drugs affect them. HSE News Service spoke with Evgeny Knyazev, Head of the Laboratory.
November 9, 2026
Flattened Terrain Models Underestimate Vehicle-to-Vehicle Communication Outages
Researchers at HSE MIEM have shown that widely used simulators of vehicle-to-vehicle communication significantly overestimate its reliability because they assume flat terrain. When terrain features, bridges, and tunnels are taken into account, the outage rate on a mountain serpentine road rises from 21% to 30%, on an overpass from 20% to 33%, and in a tunnel from 0% to 80%. The results have been published in Future Transportation.

 

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Molecular-level insights to structure and hydrogen bonds network of 1,4-dioxane aqueous solution

Journal of Molecular Liquids. 2024. Vol. 393. Article 123523.
Bakulin I., Kopanichuk I., Kondratyuk N.

We investigate aqueous 1,4-dioxane solution structure via molecular dynamics approach for the force fields by Smith et al. and OPLS-AA/CM1A with water model TIP4P. The overestimation of enthalpy of mixing is linked with the lower numbers of water-water and higher numbers of dioxane-water hydrogen bonds. The results provide the total number of hydrogen bonds per oxygen atom, as well as specific numbers of hydrogen bonds for water-water and dioxane-water pairs in solution. We show that specific quantities are required to observe the difference in the solution structure across the employed force fields, such as the hydrogen bond network percolation and the cluster analysis of dioxane molecules in solution. It is shown that for lower numbers of water-water hydrogen bonds the average dioxane cluster size is also lower. Total number of hydrogen bonds per oxygen atom and dioxane cluster sizes are in good agreement with X-Ray experiments by Takamuku et al. The water hydrogen bond network analysis adequately reproduces the experimental percolation thresholds by Hernandez et al.

Research target: Physics Computer Science
Language: English
DOI
Keywords: hydrogen bonds molecular dynamics solution structure
Publication based on the results of:
Supercomputer molecular modeling in material science (2024)
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