Ivan V Dudakov

collaborators

3 papers

physics.chem-ph2025

XMCQDPT2-Fidelity Transfer-Learning Potentials and a Wavepacket Oscillation Model with Power-Law Decay for Ultrafast Photodynamics

Ivan V. Dudakov, Pavel M. Radzikovitsky, Dmitry S. Popov +5

A central pursuit in theoretical chemistry is the accurate simulation of photochemical reactions, which are governed by nonadiabatic transitions through conical intersections. Mach…

physics.chem-ph2025

Machine Learning Photodynamics Unveils a Controlled H $_{2}$ Loss Channel in Methaniminium Cation

Daniil N. Chistikov, Pavel M. Radzikovitsky, Dmitry S. Popov +4

The methaniminium cation, CH $_{2}$ NH $_{2}^{+}$ , plays an important role in Titan's N $_{2}$ --CH $_{4}$ atmospheric chemistry. As the simplest protonated Schiff base (PSB), it also serves as a…

cond-mat.mtrl-sci2025

Enhancing composition-based materials property prediction by cross-modal knowledge transfer

Ivan Rubtsov, Ivan Dudakov, Yuri Kuratov +1

Crystal graph neural networks are widely applicable in modeling experimentally synthesized compounds and hypothetical materials with unknown synthesizability. In contrast, structur…

XMCQDPT2-Fidelity Transfer-Learning Potentials and a Wavepacket Oscillation Model with Power-Law Decay for Ultrafast Photodynamics

Machine Learning Photodynamics Unveils a Controlled H2​ Loss Channel in Methaniminium Cation

Enhancing composition-based materials property prediction by cross-modal knowledge transfer

Machine Learning Photodynamics Unveils a Controlled H $_{2}$ Loss Channel in Methaniminium Cation