Today computer simulation methods (molecular dynamics simulation, Monte Carlo quantum chemistry), theoretical methods (self-consistent field theory, field-theoretic approaches, classical density functional theory and integral equation theory), as well as deep machine learning techniques have turned into powerful tools for studying molecular liquids and solutions along with experimental approaches. These methods are normally applied to describe thermodynamic, mechanical, rheological and transport properties of molecular systems in bulk and in confinement and to predict new materials by neural network processing of big physicochemical data.
The Department's research is aimed at application and development of the modern methods of computer simulation of molecular liquids and solutions in bulk and at the interphase boundary based on achievements of modern theoretical physics and applied mathematics, first and foremost on the methods of statistical physics of molecular liquids and solutions (classical density functional theory, self-consistent field theory, integral equation theory), molecular dynamics, quantum chemistry and deep machine learning.
- University of Regensburg (Germany);
- Institut für Nichtklassische Chemie (Leipzig, Germany);
- Federal University of Rio de Janeiro (Brazil);
- N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences;
- Landau Institute for Theoretical Physics (Chernogolovka);
- National Research University "Higher School of Economics".
1. Budkov Y., Kolesnikov A., Goodwin Z., Kiselev M., Kornyshev A. Theory of electrosorption of water from ionic liquids // Electrochimica Acta. - 2018. - V. 284. - P. 346-354. DOI: 10.1016/j.electacta.2018.07.139.
2. Budkov Y., Kalikin N. Macroscopic forces in inhomogeneous polyelectrolyte solutions // Physical Review E - Statistical, Nonlinear, and Soft Matter Physics. - 2023. - V. 107. – Art. 024503. DOI: 10.1103/PhysRevE.107.024503.
3. Gurina D.L., Odintsova E.G., Kolesnikov A., Budkov Y.A., Kiselev M.G. Disjoining pressure of room temperature ionic liquid in charged slit carbon nanopore: Molecular dynamics study // Journal of Molecular Liquids . - 2022. - V. 366. - Art. 120307. DOI: 10.1016/j.molliq.2022.120307.
4. Makarov D.M., Fadeeva Y.A., Shmukler L.E., Tetko I.V. Machine learning models for phase transition and decomposition temperature of ionic liquids // Journal of Molecular Liquids. - 2022. - V. 366. – Art. 120247. DOI: 10.1016/j.molliq.2022.120247.
5. Budkov Y.A, Kolesnikov A.L. Electric double layer theory for room temperature ionic liquids on charged electrodes: Milestones and prospects // Current Opinion in Electrochemistry. - 2022. - V. 33. - Art. 100931. DOI: 10.1016/j.coelec.2021.100931.
6. Odintsova E.G., Petrenko V.E., Kolker A.M., Borovkov N.Y. Molecular origin of structural defects in the zinc phthalocyanine film // Physical Chemistry Chemical Physics. - 2022. - V. 24. - P. 19956-19964. DOI: 10.1039/D2CP01221A.
7. Budkov Y.A., Kalikin N.N., Kolesnikov A.L. Electrochemistry meets polymer physics: polymerized ionic liquids on an electrified electrode // Physical Chemistry Chemical Physics. - 2022. - V. 24. - P.1355-1366. DOI: 10.1039/D1CP04221A.
8. Antipova M.L., Petrenko V.E., Odintsova E.G., Bogdan T.V. Study of solvation of substituted propylbenzene in ethanol-water solutions under subcritical conditions by molecular dynamics // The Journal of Supercritical Fluids. - 2020. - V. 155. - P. 104649(1-7). DOI: 10.1016/j.supflu.2019.104649
9. Kruchinin S.E., Kislinskaya E.E., Chuev G.N., Fedotova M.V. Protein 3D-hydration: A case of bovine pancreatic trypsin inhibitor // The International Journal of Molecular Sciences. - 2022. - Vol. 23(23). - Art. 14785. DOI: 10.3390/ijms232314785.
10. Valiev M., Chuev G.N., Fedotova M.V., CDFTPY: A python package for performing classical density functional theory calculations for molecular liquids // Computer Physics Communications. – 2022. - V. 276. - Art. 108338. DOI: 10.1016/j.cpc.2022.108338.
