works on

From the 1 of 9 linked papers with an AI index.

activity
20242026
collaborators

9 papers

cond-mat.mtrl-sci2026

Integrating moment tensor potentials with finite-element modeling for heat transfer prediction in FLiBe-based molten salt systems

Mikhail Polovinkin, Ksenia Abramova, Oksana Rahmanova +8

The paper presents a multiscale framework that combines machine‑learning‑trained atomistic potentials with finite‑element simulations to predict heat‑transfer performance of FLiBe‑…

physics.chem-ph2026

Active learning and explicit electrostatics enable accurate modeling of electrolytes

Olga Chalykh, Mikhail Polovinkin, Dmitry Korogod +2

Machine learning interatomic potentials (MLIPs) offer near-\textit{ab initio} accuracy with the efficiency of classical force fields, making them attractive for modeling electrolyt…

cond-mat.mtrl-sci2026

Thermal Conductivity and Temperature-Induced Band Gap Renormalization in Crystalline and Amorphous GaO

Rustam Arabov, Jiaxuan Li, Xiaotong Chen +2

The lattice thermal conductivity (LTC) and electron-phonon interactions in crystalline and amorphous gallium oxide are herein determined by coupling a machine-learned interatomic p…

cond-mat.mtrl-sci2026

Tuning Thermal Conductivity and Electron-Phonon Interactions in Carbon and Boron Nitride Moiré Diamanes via Twist Angle Manipulation

Rustam Arabov, Nikita Rybin, Victor Demin +4

We have investigated the effect of interlayer twist angle on lattice thermal conductivity (LTC) and band gap renormalization in boron nitride and carbon Moiré diamanes. Moment ten…

cond-mat.mtrl-sci2026

Machine-Learned Interatomic Potentials for Predicting Physicochemical Properties of Molten Metal-Salt Systems for Calcium Electrolysis

M. Polovinkin, N. Rybin, D. Maksimov +5

The design of efficient electrolysis devices for pure metal production requires accurate data on the properties of the melts used in the process. This work focuses on two key syste…

math.OC2026

Global Optimization of Atomic Clusters via Physically-Constrained Tensor Train Decomposition

Konstantin Sozykin, Nikita Rybin, Andrei Chertkov +5

The global optimization of atomic clusters represents a fundamental challenge in computational chemistry and materials science due to the exponential growth of local minima with sy…