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News
October 19, 2026
'Cultural Studies Seeks to Understand What Lies Beneath the Surface of Everyday Things'
Maxim Zhiganov has been exploring different aspects of sound for many years—first in relation to his native Perm and then on a broader, global scale. In this interview for the HSE Young Scientists project, he talks about sound maps, the special issue of the journal Logos, and why it is important to make the familiar less clear and obvious.
October 14, 2026
At HSE University–St Petersburg, Experts Discuss How AI Changes Tourist Routes and Cultural Heritage
Neural networks are no longer simple travel assistants; now they decide what to include on the route and what to skip. Artificial intelligence changes how people perceive a place and shapes the image of tourist centres. At the II International Scientific and Practical Conference ’Information Technologies in the Preservation and Promotion of Cultural Heritage,’ researchers discussed who controls algorithmic solutions and in what ways, and whether authentic traditions get lost in them.
October 12, 2026
Road Injuries Leading Cause of Death Among Men Aged 10 to 39
Worldwide, road injuries are the leading cause of death among males aged 10–39. An international team of researchers reached this conclusion as part of the Global Burden of Disease Study 2023, analysing data from 204 countries between 1990 and 2023. Their findings have been published in The Lancet Public Health, with HSE University Professor Vasily Vlassov listed among the collaborators.

 

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Molecular dynamics and machine learning insights into oil-brine interfacial tension: Uncovering roles of dissolved gases and salinity

Journal of Colloid and Interface Science. 2026. Vol. 718. Article 140444.
Nikitiuk B., Lenev D., Pisarev V., Kopanichuk I., Khlyupin A., Kondratyuk N., Gerke K.

Hypothesis:Accurate determination of interfacial tension values is crucial for many modeling applications in the oil and gas industry. However, many of the presently used empirical and theoretical models show poor prediction accuracy and do not allow for direct consideration of the concentrations of gases and salts dissolved in the system as well as the specific composition of the oil. Molecular dynamics methods allow one to directly model the oil-brine interface and may provide a pathway to build more precise and complete interfacial tension models.

Simulations:We adapt a multi-component molecular model consisting of 17 representative hydrocarbons to qualitatively match the experimental oil composition of a specific reservoir. We perform molecular dynamics simulations to assess the effect of temperature, pressure, salt concentration in water and gas contents in oil within experimentally observed ranges on the interfacial tension. Using the robust statistics collected over 10 μs of molecular dynamics simulations, a machine-learning model is trained to reproduce the interfacial tension with mean absolute percentage error of 0.9%.

Findings:We obtain linear dependencies of interfacial tension on the considered parameters and show that concentrations of salts and gases dissolved in the system exert the largest influence on the interfacial tension value. The asphaltenes contained within the oil phase act as surfactants, decreasing the interfacial tension, with the effect further enhanced by the concentration of the dissolved gases on the interface. The molecular model was verified against experimental data. The resulting ML model shows excellent agreement with simulation data. Our results provide a pathway towards building a scalable and physically grounded framework for predicting oil-brine interfacial tension across wide thermodynamic and compositional ranges to enable reliable reservoir-scale modeling.

Research target: Physics Computer Science
Language: English
DOI
Keywords: oilmolecular dynamicsmulti-phase flowInterfacial tensionMachine-learningOil-brine
Publication based on the results of:
Advanced materials and technologies (2025)
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