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Personal profile

Research interests

Ab initio electronic-structure methods (quantum chemistry, DFT); ab initio atomistic thermodynamics; first-principles multiscale methods (kinetic Monte Carlo); interactions of atoms and molecules at surfaces; computational heterogeneous catalysis and electrochemistry; defects at surfaces and interfaces; polarons; artificial intelligence for materials science; conversion of methane and carbon dioxide; polar surfaces; ferroelectric materials; batteries.

Entrepreneurship and Innovation activities

Code development (FHI-aims)

Academic Reputation and Societal Impact

Sergey V. Levchenko is internationally well-known in the area of computational chemistry and materials science. He has organized several international conferences (Big Data of Materials Science -- Critical Next Steps” CECAM-HQ-EPFL, Lausanne, Switzerland, December 2015; “White nights of materials science: From physics and chemistry to data analysis, and back”, Saint Petersburg, Russia, June 2014; “Agile Design of Electronic Materials: Aligned Computational and Experimental Approaches”, Electronic Materials and Applications 2020, Orlando, FL, USA, January 2020). He is also regularly invited to international conferences (see the list in Section III.b). S. V. Levchenko collaborates with scientific groups in Germany, Spain, China, India, and Japan. He is a leader of the working group “Surfaces and interfaces” within Psi-k, a Europe-based, worldwide network of researchers working on the advancement of first-principles computational materials science.

My research is focused on interface chemical reactions and heterogeneous catalysis, in particular on designing better catalytic materials for conversion of methane to higher hydrocarbons, and conversion of CO2 to fuels. This is important for increasing effiency of energy conversion, as well as for preservation of environment and preventing an undesirable climate change. Using theoretical calculations for materials design allows to reduce the cost and time for developing and employing new materials in industry. Moreover, I develop artificial intelligence methods that allow for a fast screening of a large number of candidate materials for any particular application. The methods are aimed at fnding correlations between properties that are simple to calculate (descriptors) and complex target properties such as catalytic activity and selectivity.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 13 - Climate Action


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