معرفی
Dmitry Aksenov serves as an Assistant Professor at Skolkovo Institute of Science and Technology (Skoltech), leading the computational materials group within the Center for Energy Science and Technology. His research focuses on computational studies of next-generation metal-ion batteries, with emphasis on electrode/electrolyte interfaces and high-throughput materials modeling. He develops specialized software (SIMAN) for automating quantum-mechanical calculations and maintains close collaboration with experimental research teams.
His educational background includes:
- 2006–2011: Specialist in Physics and Engineering from Belgorod State University
- 2011–2014: Candidate of Sciences in Condensed Matter Physics from Belgorod State University
Aksenov's research spans computational materials science with specialization in density functional theory (DFT) and high-throughput screening of battery materials. His work targets fundamental mechanisms at electrode/electrolyte interfaces in Li-ion, Na-ion, K-ion, and Li-air systems, aiming to design stable interfaces with low ionic resistivity. He investigates structure-property relationships to enhance battery safety, lifespan, and energy density through atomic-level simulations of cathode/anode materials, defect chemistry, and ion transport phenomena. His methodology combines DFT calculations with machine learning to accelerate materials discovery.
Analysis of his 15 most recent publications (2022–2024) reveals dominant themes in sodium-ion battery cathodes (NaVOPO4, NaGaPO4F), lithium-ion electrode modifications (NMC, Li-rich systems), and computational reviews of ionic conductivity mechanisms. Key trends include high-throughput screening of NH4+-based frameworks, defect engineering in olivine structures, and interfacial phenomena in solid-state batteries. His work consistently bridges computational predictions with experimental validation through extensive collaborations.
No scientific awards were documented in the provided materials.
Aksenov leads the computational materials group at Skoltech's Center for Energy Science and Technology, directing the SIMAN software development for automated materials calculations. His research is funded through institutional support at Skoltech with strong industry-academia partnerships focused on commercializing battery materials. The group maintains tight integration with experimental teams at Skoltech and international collaborators including Max Planck Institutes.
The computational materials group operates within Skoltech's Center for Energy Science and Technology, utilizing high-performance computing resources for large-scale DFT simulations. They specialize in simulating metal-ion battery interfaces and developing machine learning workflows through the SIMAN platform. Current projects focus on designing stable electrolyte formulations and high-capacity electrode materials for next-generation batteries.
