Dr. Alexey Rulev received his Master’s degree and Ph.D. in Solid-State Chemistry and Electrochemistry from Moscow State University, with an internship at the Institute of Electrochemistry, Ulm University, where he specialized in ab initio simulations. His early research focused on lithium metal anodes, leading to the development of a comprehensive mechanism of lithium whisker growth that integrates electrochemical processes, mechanical stress, and solid-state lithium transport.
He has extensive experience in synchrotron and neutron scattering techniques and has contributed to the development of operando characterization methods for lithium-based electrochemical systems. Currently, Dr. Rulev is a postdoctoral researcher at Empa (Swiss Federal Laboratories for Materials Science and Technology), where he works on synchrotron-based operando metrology for lithium-ion batteries and on the theoretical framework of fast ion transport in oxides, emphasizing ion–phonon coupling. His research interests include the integration of first-principles simulations with experimental data analysis, mechanistic modeling, and the development of physics-aware machine learning approaches for materials design and understanding.
Dr. Alexey Rulev received his Master’s degree and Ph.D. in Solid-State Chemistry and Electrochemistry from Moscow State University, with an internship at the Institute of Electrochemistry, Ulm University, where he specialized in ab initio simulations. His early research focused on lithium metal anodes, leading to the development of a comprehensive mechanism of lithium whisker growth that integrates electrochemical processes, mechanical stress, and solid-state lithium transport.
He has extensive experience in synchrotron and neutron scattering techniques and has contributed to the development of operando characterization methods for lithium-based electrochemical systems. Currently, Dr. Rulev is a postdoctoral researcher at Empa (Swiss Federal Laboratories for Materials Science and Technology), where he works on synchrotron-based operando metrology for lithium-ion batteries and on the theoretical framework of fast ion transport in oxides, emphasizing ion–phonon coupling. His research interests include the integration of first-principles simulations with experimental data analysis, mechanistic modeling, and the development of physics-aware machine learning approaches for materials design and understanding.